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Comprehensive Modeling of Special Nuclear Materials Detection Using 3-D Deterministic and Monte Carlo Methods

Permanent Link: http://ufdc.ufl.edu/UFE0022654/00001

Material Information

Title: Comprehensive Modeling of Special Nuclear Materials Detection Using 3-D Deterministic and Monte Carlo Methods
Physical Description: 1 online resource (221 p.)
Language: english
Creator: Ghita, Gabriel
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: detection, deterministic, mcnp, neutron, nuclear, radiation, snm, transport
Nuclear and Radiological Engineering -- Dissertations, Academic -- UF
Genre: Nuclear Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Our study aim to design a useful neutron signature characterization device based on 3He detectors, a standard neutron detection methodology used in homeland security applications. Research work involved simulation of the generation, transport, and detection of the leakage radiation from Special Nuclear Materials (SNM). To accomplish research goals, we use a new methodology to fully characterize a standard ?1-Ci? Plutonium-Beryllium (Pu-Be) neutron source based on 3-D computational radiation transport methods, employing both deterministic SN and Monte Carlo methodologies. Computational model findings were subsequently validated through experimental measurements. Achieved results allowed us to design, build, and laboratory-test a Nickel composite alloy shield that enables the neutron leakage spectrum from a standard Pu-Be source to be transformed, through neutron scattering interactions in the shield, into a very close approximation of the neutron spectrum leaking from a large, subcritical mass of Weapons Grade Plutonium (WGPu) metal. This source will make possible testing with a nearly exact reproduction of the neutron spectrum from a 6.67 kg WGPu mass equivalent, but without the expense or risk of testing detector components with real materials. Moreover, over thirty moderator materials were studied in order to characterize their neutron energy filtering potential. Specific focus was made to establish the limits of He-3 spectroscopy using ideal filter materials. To demonstrate our methodology, we present the optimally detected spectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials. Finally, using knowledge gained from previous studies, the design of a He-3 spectroscopy system neutron detector, simulated entirely via computational methods, is proposed to resolve the spectra from SNM neutron sources of high interest. This was accomplished by replacing ideal filters with real materials, and comparing reaction rates with similar data from the ideal material suite.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gabriel Ghita.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Sjoden, Glenn E.
Local: Co-adviser: Baciak, James.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022654:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022654/00001

Material Information

Title: Comprehensive Modeling of Special Nuclear Materials Detection Using 3-D Deterministic and Monte Carlo Methods
Physical Description: 1 online resource (221 p.)
Language: english
Creator: Ghita, Gabriel
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: detection, deterministic, mcnp, neutron, nuclear, radiation, snm, transport
Nuclear and Radiological Engineering -- Dissertations, Academic -- UF
Genre: Nuclear Engineering Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Our study aim to design a useful neutron signature characterization device based on 3He detectors, a standard neutron detection methodology used in homeland security applications. Research work involved simulation of the generation, transport, and detection of the leakage radiation from Special Nuclear Materials (SNM). To accomplish research goals, we use a new methodology to fully characterize a standard ?1-Ci? Plutonium-Beryllium (Pu-Be) neutron source based on 3-D computational radiation transport methods, employing both deterministic SN and Monte Carlo methodologies. Computational model findings were subsequently validated through experimental measurements. Achieved results allowed us to design, build, and laboratory-test a Nickel composite alloy shield that enables the neutron leakage spectrum from a standard Pu-Be source to be transformed, through neutron scattering interactions in the shield, into a very close approximation of the neutron spectrum leaking from a large, subcritical mass of Weapons Grade Plutonium (WGPu) metal. This source will make possible testing with a nearly exact reproduction of the neutron spectrum from a 6.67 kg WGPu mass equivalent, but without the expense or risk of testing detector components with real materials. Moreover, over thirty moderator materials were studied in order to characterize their neutron energy filtering potential. Specific focus was made to establish the limits of He-3 spectroscopy using ideal filter materials. To demonstrate our methodology, we present the optimally detected spectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials. Finally, using knowledge gained from previous studies, the design of a He-3 spectroscopy system neutron detector, simulated entirely via computational methods, is proposed to resolve the spectra from SNM neutron sources of high interest. This was accomplished by replacing ideal filters with real materials, and comparing reaction rates with similar data from the ideal material suite.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gabriel Ghita.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Sjoden, Glenn E.
Local: Co-adviser: Baciak, James.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022654:00001


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1 COMPREHENSIVE MODELING OF S PECIAL NUCLEAR MATERIALS DETECTION USING 3 D DETERMINISTIC AND MONTE CARLO METHODS By GABRIEL M. GHITA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULF ILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

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2 2008 Gabriel M. Ghita

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3 To my family who shared with me the sacrifices required to complete it. My wife, Monica, who supported me through this acad emic journey in more ways than one and my daughter, Gabriela Livia, who seems to be growing into a wonderful human being, in spite of the fact her father was less available than he should.

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4 ACKNOWLEDGMENTS This project was made possible through the support of National Nuclear Security Ad ministration (NNSA), Program DE SC04 04NA25441, Contract NA25685 ROA04. I would like to thank my advisor and the chair of my committee, Dr. Glenn Sjoden, for affording me the opportunity to study under his direction. I am indebted to him for his guidance, encouragement, and patience. His advice regarding my dissertation, my career plans, or other matters, were consistently insightful. My gratitude is extended to my co advisor and co chair of my committee, Dr. James Bac iak for his support in all stages of my research work. I would also like to express my appreciation for the numerous suggestions provided by the committee members, Dr. Jess Gehin and Dr. Jacob Chung. My special thanks go to Professor Alireza Haghighat for serv ing on my supervisory committee and for all of the opportunities, advice, and encouragement during my time at the Nuclear and Radiological Engineering Department. Having him as a Professor was a great fortune and pleasure which decisively influenced my scientific development. I would like to thank to my colleagues Scotty Walker and Spring Cornelison for assisting me during the laboratory work. I owe more than words can ever fully express to my dear colleague, friend and wife for many years Monica. Sh e knows the best and worst of me, and continues to stick by me anyway. T hank you for the countless ways in which you have supported me during this and other endeavors. You have my unending admiration and affection. No study of this nature and complexity ca n be accomplished without the help, support, and cooperation of many others. I am grateful to all of them.

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5 It has been a great privilege to spend several years in the Nuclear and Radiological Engineering Department at University of Florida and its members will always remain dear to me.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ........... 4 LIST OF TABLES ................................ ................................ ................................ ...................... 8 L IST OF FIGURES ................................ ................................ ................................ .................. 10 ABSTRACT ................................ ................................ ................................ ............................. 20 CHAPTER 1. INTRODUCTION ................................ ................................ ................................ ............. 22 1.1 Mot ivation ................................ ................................ ................................ .................... 22 1.2 Study Overview ................................ ................................ ................................ ............ 22 2. BACKGROUND AND LITERATURE REVIEW ................................ .............................. 25 2.1 The Pu Be Capsule and Special Nuclear Materials ................................ ....................... 25 2.2 Detection of Special Nuclear Materials ................................ ................................ ......... 27 2.3 Computational T ransport Methods ................................ ................................ ................ 32 2.3.1 The PENTRAN S N Transport Code System ................................ ........................ 33 2.3.2 The MCNP5 Monte Carlo Code and SCALE5.1 Code Systems .......................... 34 2.4 Cross Section Library Considerations ................................ ................................ ........... 35 3. COMPUTATIONAL PROCEDURES ................................ ................................ ............... 39 3.1 Forward versus Adjoint Transport Calculation Procedures ................................ ............ 39 3.1.1 Computational Approach ................................ ................................ .................... 39 3.1.2 Comparison of Fo rward, Adjoint, and Monte Carlo Results ................................ 41 3.2 The 3 D Parallel S N Computational Performance ................................ .......................... 45 3.3 Total Source as a Function o f Energy ................................ ................................ ........... 47 4. METHODOLOGY FOR EXPERIMENTAL AND 3 D COMPUTATIONAL RADIATION TRANSPORT ASSESSMENT OF PU BE NEUTRON SOURCES ............. 54 4.1 The Pu Be Source Capsule Description ................................ ................................ ........ 55 4.2 Estimation of the Neutron Emission ................................ ................................ ............. 56 4.3 Plutonium Age Estimation ................................ ................................ ............................ 57 4.4 Calculation of the Effective Dose ................................ ................................ ................. 58 4.5 Benchmark Problem MCNP5 Simulations vs. Experimental Results .......................... 59 4.6 Comparing the Leakage Spectra Using Monte Carlo and S N Transport Methods ........... 61

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7 5. THE SNM NEUTRON SOURCE ASSESSMENTS ................................ ........................... 83 5.1 Plutonium Sources ................................ ................................ ................................ ........ 84 5.1.1 The PWR Generated Plutonium ................................ ................................ .......... 85 5.1.2 The CANDU Generated Plutonium ................................ ................................ .... 87 5.2 Enriched Uranium Fuel ................................ ................................ ................................ 89 5.3 Monte Carlo (MCNP5) Versus S N (PENTRAN/BUGLE 96) Leakage .......................... 91 6. COMPUTATIONAL AND EXPERIMENTAL VALIDATION OF A WGPU NEUTRON LEAKAGE SOURCE USING A SHIELDED PU BE NEUTRON SOURCE ................................ ................................ ................................ ......................... 127 6.1 Computational Simulations ................................ ................................ ......................... 127 6.2 Experimental Validation ................................ ................................ ............................. 131 6.2.1 Materials and Procedures ................................ ................................ .................. 131 6.2.2 Results and Analysis ................................ ................................ ......................... 133 7. DETECTION OF SPECIAL NUCLEAR MATERIALS ................................ .................. 151 7.1 Moderator Study ................................ ................................ ................................ ......... 151 7.1.1 Moderator Properties ................................ ................................ ........................ 151 7.1.2 Energy Band Separation in Polyethylene ................................ .......................... 154 7.2 Spectral Det ection Analysis Using Ideal Filters ................................ .......................... 156 7.2.1 Diluted 3 He Approximation throughout the Moderator ................................ ...... 156 7.2.2 Reference (without Fi ltering) SNM Detection ................................ ................... 157 7.2.3 Strategy for Improving the Spectral Detection Using Filter Materials ............... 157 7.3 Filtration Effect Study ................................ ................................ ................................ 159 7.4 Detection Device Proposal ................................ ................................ .......................... 161 8. CONCLUSIONS AND FUTURE WORK ................................ ................................ ........ 214 LIST OF REFERENCES ................................ ................................ ................................ ........ 217 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ... 221

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8 LIST OF TABLES Table page 2 1. Upper energies of neutron energy groups in BUGLE 96. ................................ ............... 37 2 2. Upper energies of photon energy groups in BUGLE 96. ................................ ................ 37 3 1. Comparison of Reaction Rates in Each 3 He Tube bank using Forward S N Adjoint S N and Monte Carlo results for a 4kg Spherical Pu metal neutron leakage source ............... 51 3 2. Comparison of PENTRA N performance based on different decomposition strategy. ..... 51 4 1. Sensitivity of the Pu Be source with the variation of the isotopic composition ............... 64 5 1. Isotopic Values of PWR 3 ) ........................... 95 5 2. Mass Values of PWR 3 ) ................... 95 5 3. Mass Values of PWR Generated PuO 2 3 ) ............................ 95 5 4. Molecular Weight, Intrinsic Source Strength and Neutron Multipl ication eigenvalue (k eff ) of PWR 3 ) ................................ 95 5 5. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of PWR Ge nerated PuO 2 3 ) ................................ ......... 96 5 6. Isotopic Values of CANDU 3 ) ...................... 96 5 7. Mass Values of CANDU 3 ) .............. 96 5 8. Mass Values of CANDU Generated PuO 2 3 ) ...................... 96 5 9. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of CANDU 3 ) .......................... 96 5 10. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of CANDU Generated PuO 2 3 ) ................................ ... 97 5 11. Isotopic Values of Enriched Uranium s pheres ................................ ................................ 97 5 12. 3 ) ........................ 97 5 13. Mass Values of Enriched UO 2 10 3 ) ................................ ....... 97 5 14. 3 ) ........................ 98 5 15. Mass Value s of Enriched UO 2 3 ) ................................ ....... 98

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9 5 16. 3 ) ........................ 98 5 17. Mass Values of Enriched UO 2 3 ) ................................ ....... 98 5 18. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Uranium me 3 ) ................................ ..... 99 5 19. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Enriched UO 2 3 ) ................................ ..... 99 5 20. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff 3 ) ................................ ..... 99 5 21. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Enriched UO 2 3 ) ................................ ..... 99 5 22. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff 3 ) ................................ ... 100 5 23. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Enriched UO 2 3 ) ................................ ... 100 6 1. Relative difference between the amplitude of the peaks, comparing WGPu leakage to final Surrogate Shield design leakage. ................................ ................................ .......... 136 7 1. Moderator performance study, using PuBe, PuO 2 and Pu metal n source spectrum transmitted through 12 cm of moderator, 67 Group n BUGLE 96 cross section library. ................................ ................................ ................................ ......................... 166 7 2. The R obtained using real filter materials and Pu (frontal placed) neutron sources. ...... 171 7 3. The R obtained using real filter materials for U (frontal placed) neutron sources. ......... 171 7 4. The R obtained using real filter materials for Pu (central placed) neutron sources. ....... 171 7 5. The R obtained using real filter materials for U (central placed) neutron sources. ......... 171 7 6. The R obtained using real filter materials for Pu Be and Surrogate WGPu (central placed) neutron sources. ................................ ................................ .............................. 171 7 7. Relative Ratios of the R produced using SNM neutron sources*. ................................ 171

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10 LIST OF FIGURES Figure page 2 1. The MCNP model of a typical construction for Pu Be sources. ................................ ...... 37 2 2. Common reaction s used for slow neutrons detection. ................................ ..................... 38 3 1. Moderated 3 He Tube Bank models. A) PENTRAN model, B) MCNP5 Model. .............. 51 3 2. Comparis on of Reaction Rates in Each 3He Tube bank using Forward S N Adjoint S N and Monte Carlo Results for a Pu Metal Neutron Source. ................................ ......... 52 3 3. iency. ................................ ...... 52 4 1. The PENTRAN model of a typical construction for Pu Be sources.. .............................. 64 4 2. Neutron leakage profile for 1 Ci Pu Be source, computed using MCNP5 (1 ). A) as a function of energy, B) as a function of energy group. ................................ .................. 65 4 3. Photon leakage profile for 1 Ci Pu Be source computed using MCNP5 (1 ). A) as a fu nction of energy, B) as a function of energy group. ................................ ..................... 66 4 4. Be source over time. ... 67 4 5. Increase of the ( Be source over time. ......................... 67 4 6. The Pu age estimation algorithm. ................................ ................................ ................... 68 4 7. Increase in the intri Be neutron source over time due to 241 Am. ................................ ................................ ................................ ......... 68 4 8. The ORIGEN ARP rendered intrinsic s.f. vs. ( Be source as a function of ene rgy for year 1971. ................................ ................................ ............ 69 4 9. Be source, using ORIGEN ARP, as a function of energy, at snapshots in time. ................................ ................................ ........ 69 4 10. Be source, using ORIGEN ARP, as a function of energy, at snapshots in time. ................................ ................................ ...................... 70 4 11. A) Neutron response function data for pha ntom related dose B) photon response function data for phantom related dose. ................................ ................................ ......... 70 4 12. Be source(1 ). A) neutron energy f luence. B) photon energy fluence. ................................ 71 4 13. Experimental 3 ...... 72

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11 4 14. The MCNP5 simulated 3 moderator. ................................ ................................ ................................ ..................... 73 4 15. View of the capsule in the vertical position. A) MCNP5 benchmark simulation, B) experim ental design. ................................ ................................ ................................ ...... 73 4 16. View of the capsule in the horizontal bottom closer position. A) MCNP5 benchmark simulation, B) experimental design. ................................ ................................ ............... 74 4 17. View of the capsule in the horizontal top closer position. A) MCNP5 benchmark simulation, B) experimental design. ................................ ................................ ............... 74 4 18. Experiment vs. MCNP5 (1 moderator. ................................ ................................ ................................ ..................... 75 4 19. Experiment vs. MCNP5 (1 moderator. ................................ ................................ ................................ ..................... 75 4 20. Experiment vs. MCNP5 (1 top polyethylene moderator. ................................ ................................ ................................ 76 4 21. Experiment vs. MCNP5 (1 ): the caps top paraffin moderator. ................................ ................................ ................................ ........ 76 4 22. Experiment vs. MCNP5 (1 bottom polyethylene moderator. ................................ ................................ ................................ 77 4 23. Experiment vs. MCNP5 (1 bottom paraffin moderator. ................................ ................................ ................................ ........ 77 4 24. PENTRAN BUGLE 96 vs. MCNP5 (1 ): Neutron leakage profile (shielding calculation, no multiplication), 1 Ci Pu Be neutron source capsule. A) as a function of energy, B) as a function of energy group. ................................ ................................ .. 78 4 25. The MCNP5 / PENTRAN BUGLE 96 (1 ): Neutron leakage (shielding calculation, no multiplication), 1 Ci Pu Be neutron source capsule. A) as a function of neutron energy, B) as a function of energy group. ................................ ................................ ....... 79 4 26. PENTRAN BUGLE 96 versus MCNP5 (1 ): Neutron leakage profile (with multiplication), 1 Ci Pu Be neutron source capsule. A) as a function of neutron energy, B) as a function of energy group. ................................ ................................ ....... 80 4 27. PENTRAN BUGLE 96 versus MCNP5 (1 ): Photon leakage, 1 Ci Pu Be neutron source capsule. A) as a function of photon energy, B) as a function of energy group. ..... 81 4 28. The MCNP5 / P ENTRAN BUGLE 96 (1 ) Photon leakage ratio (shielding calculation, no multiplication), 1 Ci Pu Be capsule. A) as a function of energy, B) as a function of energy group. ................................ ................................ ............................ 82

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12 5 1. Variation in isotopic Pu content versus burnup in PWR fuel. ................................ ....... 100 5 2. metal intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source. ................................ .................... 101 5 3. The PWR generated 4 kg PuO 2 intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source. ................................ ................................ 102 5 4. Typical neutron intrinsic source components for Pu metal (s.f. neutrons). .................... 103 5 5. Typical neutron intrinsic source components for PuO 2 [s.f. and ( ) neutrons]. ........... 103 5 6. The 4 kg spherical Pu Metal neutron intrinsic source versus 4 kg spherical PuO 2 neutron intrinsic source. ................................ ................................ ............................... 104 5 7. Comparison of source strengths from PWR fuel derived plutonium, 4 kg sphere A) neutrons, B) photons. ................................ ................................ ................................ ... 104 5 8. Variation of k eff in PWR fuel, 4kg sphere, determined using MCNP5 ( .................. 105 5 9. Variation in isotopic Pu content vs. burnup in CANDU fuel ................................ ........ 106 5 10. The CANDU generated 4 kg Pu metal intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source. ................................ .................... 106 5 11. The CANDU generated 4 kg PuO 2 intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source ................................ ..................... 107 5 12. Variation of k eff ............. 108 5 13. Comparison of source strengths from CANDU fuel derived plutonium, 4 kg sphere. A) neutrons, B) photons. ................................ ................................ .............................. 109 5 14. The 10 kg U metal intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source. ................................ ................................ ............... 110 5 15. The 10 k g UO 2 intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source. ................................ ................................ ........................... 111 5 16. The 30 kg U metal intrinsic source as a function of energy. A) Neutron intr insic source, B) Photon intrinsic source. ................................ ................................ ............... 112 5 17. The 30 kg UO 2 intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source. ................................ ................................ ........................... 113 5 18. The 50 kg U metal intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source. ................................ ................................ ............... 114

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13 5 19. The 50 kg UO 2 i ntrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source. ................................ ................................ ........................... 115 5 20. Variations in U Metal source strength. A) neutrons, B) photons. ................................ .. 116 5 21. Variations in UO 2 source strength. A) neutrons, B) photons. ................................ ........ 117 5 22. The U metal k eff values versus HEU enrichment computed using MCNP ........... 118 5 23. The UO 2 k eff ................................ ........ 118 5 24. The 4 kg Pu metal ball in air projected on S N 1/8 symmetry mesh A) PENTRAN th th view). ................................ ................................ ................................ .......................... 119 5 25. PENTRAN BUGLE 96 vs. MCNP5 (1 ): Neutron leakage profile (shielding calculation, no multiplication), 4 kg Pu metal. A) as a function of energy, B) as a function of energy group. ................................ ................................ ............................. 120 5 26. The MCNP5 / PENTRAN BUGLE 96 (1 ): Neutron leakage (shielding calculation, no multiplication), 4 kg WGPu metal. A) as a function of energy, B) as a function of energy group. ................................ ................................ ................................ ............... 121 5 27. PENTRAN BUGLE 96 vs. MCNP5 (1 ): Photon leakage profile (shielding calculation, no multiplication), 4 kg WGPu metal. A) as a function of energy, B) as a function of energy group. ................................ ................................ ............................. 122 5 28. The MCNP5 / PENTRAN BUGLE 96 (1 ) Photo n leakage ratio (shielding calculation, no multiplication), 4 kg WGPu metal. A) as a function of energy, B) as a function of energy group. ................................ ................................ ............................. 123 5 29. Neutron leakage profile for 4 kg WGPu meta l source, computed using MCNP5 (1 ). A) as a function of energy, B) as a function of energy group. ................................ ....... 124 5 30. Photon leakage profile for 4 kg WGPu metal source computed using MCNP5 (1 ). A) as a function of energy, B) as a f unction of energy group. ................................ ....... 125 5 31. PENTRAN BUGLE 96 versus MCNP5 (1 ): Neutron leakage profile (with multiplication) for 4 kg WGPu metal neutron source. A) as a function of energy, B) as a fu nction of energy group. ................................ ................................ ...................... 126 6 1. The Pu Be Shielded Source Assembly. A) MCNP simulation, B) Experimental Design. ................................ ................................ ................................ ........................ 136 6 2. The MCNP5 computed normalized leakage spectra of Pu metal and Pu Be neutron .................. 137

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14 6 3. Total neutron absorption cross sections of Nickel, Lead, Sil icon, Aluminum, Iron, Magnesium, Manganese, and Carbon. ................................ ................................ .......... 138 6 4. Total neutron absorption cross section of Indium, Silver, Cadmium, and Hafnium. ...... 138 6 5. Source Material MCNP5 model set up. ................................ ................................ ....... 139 6 6. 12 cm Iron for filtering the Pu Be spectrum compared to initial Pu Be spectru (red). ... 139 6 7. The MCNP5 computed 12 cm Graphite for filtering the Pu Be spectrum compared to initial Pu Be spectru (red). ................................ ................................ ................................ ........................... 140 6 8. leakage spectrum (green) obtained using 12 cm Copper for filtering the Pu Be spectrum compared to initial Pu Be spectrum (red). ................................ ................................ ................................ ........................... 140 6 9. Transformation of the Pu Be neutron spectrum in Pu me tal spectrum [MCNP5 ... 141 6 10. cm Nickel composite alloy material for filtering the Pu Be spectrum compared to initial Pu Be spectrum (red). ................................ ................................ ........................ 141 6 11. The MCNP5 computed neutron spectrum profiles obtained with a cylindric al ................................ ....... 142 6 12. Detailed geometry of the Nickel composite alloy shielded source. A) computed dimensions of the shield. B) The VISED s imulated design. ................................ .......... 142 6 13. The MCNP5 computed Pu Be versus Surrogate Shielded neutron sources as a spectra. ................................ ................................ ................................ ........................ 143 6 14. Normalized neutron leakage comparison between Surrogate Shielded Source and WGPu source. ................................ ................................ ................................ ............. 144 6 15. Source Detector exper imental set up. A) Bare Source. B) Filtered Source. .................. 145 6 16. Source Detector experimental set up. A) Bare Source and small Cd shielding below. B) No Source and large Cd shielding below. C) B are Source, small Cd below, and large Cd shielding beside. ................................ ................................ ............................ 146 6 17. Experimental Reaction Rate versus Moderator Thicknesses with Varying Cd Shielding for A) the Bare Source, B) Shielded Sour ce. ................................ ................. 147

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15 6 18. Reaction Rate versus Moderator Thicknesses for Bare and Shielded Sources. A) Small Cd Floor Shielding, B) Large Cd Floor Shielding, C) Small Cd Floor Shielding and Large Cd Stan ding Shielding ................................ ................................ 148 6 19. obtained using MCNP models. ................................ ................................ .................... 150 6 20. experimentally obtained. ................................ ................................ .............................. 150 7 1. The 3 He cross section, BUGLE 96, groups 1 47. ................................ ......................... 172 7 2. Source moderator (polyethylene) block problem. A) Set up. B) Flux from fast neutron (9 th energy group). C) Flux from epithermal neutrons (30 th energy group). D) Flux from thermal neutrons (47 th energ y group). ................................ .......................... 172 7 3. The MCNP5 results for R in 3 He [less than 1% statistical relative error (1 ) for every value], as a function of energy group and the distance in polyethylene horizontal approach. ................................ ................................ ................................ .... 173 7 4. Th e MCNP5 results for R in 3 He as a function of energy group and the thickness of polyethylene moderator using SNM neutron sources [less than 1% statistical relative error (1 ) for every value]. ................................ ................................ .......................... 174 7 5. The SNM neutron spectra as a function of energy group [MCNP5 (1 ) calculations]. 175 7 6. Normalized to maximum R curves in 3 He using SNM sources and HDPE moderator [MCNP5 calcul ations, less than 0.5% statistical relative error (1 )]. ........................... 175 7 7. The normalized to maximum R curves for different distances of the first row of 3 He detectors compared with infinitely dilute d 3 He gas in polyethylene moderator [MCNP5 calculations, less than 0.5% statistical relative error (1 )]. ........................... 176 7 8. The 3 He (green) detector positions in moderator (blue) corresponding to upp er region of the reaction rate curve. A) 2.5 cm HDPE/ 3 He detector/9.5 cm HDPE, B) 3 cm HDPE / 3 He detector/9 cm HDPE, C) 3.5 cm HDPE / 3 He detector/8.5 cm HDPE, D) 4 cm HDPE / 3 He detector/8 cm p HDPE. ................................ ................................ ..... 176 7 9. The MCNP5 computed normalized leakage spectra of Pu metal and PuO 2 neutron ................................ ................................ .. 177 7 10. The MCNP5 computed normalized leakage spectra of U metal and UO 2 neutron ................................ ................................ .. 178 7 11. Difference in detection of Pu metal and PuO 2 [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ....................... 178

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16 7 12. Diff erence in detection of U metal and UO 2 [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ....................... 179 7 13. Difference in detection of Pu [MCNP5 calculations, less than 1% statistical relative error (1 )]. .............................. 179 7 14. Capture of the four bands of spectra using ideal filters [MCNP5 calculations, less than 1% statistical rel ative error (1 )] ................................ ................................ ......... 180 7 15. Normalized to maximum Pu Be neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% statist ical relative error (1 )] ................................ ................................ ....................... 181 7 16. Normalized to maximum Pu metal neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ....................... 181 7 17. Normalized to maximum PuO 2 neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, le ss than 1% statistical relative error (1 )] ................................ ................................ ....................... 182 7 18. Normalized to maximum U metal neutron source leakage spectrum (blue) and the ideal case detection processed results (red) [MCNP5 calcula tions, less than 1% statistical relative error (1 )] ................................ ................................ ....................... 182 7 19. Normalized to maximum UO 2 neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 c alculations, less than 1% statistical relative error (1 )] ................................ ................................ ....................... 183 7 20. and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ................. 183 7 21. Difference in detection of Pu metal and PuO 2 using ideal filter [MCNP5 calculations, less than 1% s tatistical relative error (1 )] ................................ .............. 184 7 22. Difference in detection of U metal and UO 2 using ideal filter [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ .. 184 7 23. Difference in detection of PuBe and surrogate source using ideal filter [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ .............. 185 7 24. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) air [MCNP5 calculations, less than 1% statistical relative error (1 )]. ............. 185 7 25. Mod ification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) polyurethane. [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ................................ ............................... 186

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17 7 26. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Dow foam. [MCNP5 calculations, less than 1% statistical relative error (1 )] 186 7 27. Modification of a flat spec trum profile (blue) moderated by 6 cm (red) and 12 cm (green) helium gas. [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ................................ ............................... 187 7 28. Modification of a flat spectrum profile (blue) moderated by Cadmium [MCNP5 calculations, less than 1% statistical relative error (1 )] A) 1 mm (red) and 2 mm (green) Cadmium. B) 6 cm (red) and 12 cm (green) Cadmium. ................................ .... 187 7 29. Mo dification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Tantalum. [MCNP5 calculations, less than 1% statistical relative error (1 )] .. 188 7 30. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Gold. [MCNP5 calculations, less than 1% statistical relative error (1 )] ......... 189 7 31. Modification of a flat spectrum pr ofile (blue) moderated by 6 cm (red) and 12 cm (green) Indium. [MCNP5 calculations, less than 1% statistical relative error (1 )] ...... 189 7 32. Modification of a flat spectrum profile (blue) mod erated by 6 cm (red) and 12 cm (green) Hafnium. [MCNP5 calculations, less than 1% statistical relative error (1 )] ... 190 7 33. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Copper. [MCNP5 calculations, less than 1% statistical relative error (1 )] ...... 190 7 34. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Iron. [MCNP5 calculations, less than 1% statistical relative error (1 )] ........... 191 7 35. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Cesium. [M CNP5 calculations, less than 1% statistical relative error (1 )] ..... 191 7 36. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Iodine. [MCNP5 calculation s, less than 1% statistical relative error (1 )] ....... 192 7 37. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Silver. [MCNP5 calculations, less than 1% statistical relative error (1 )] ........ 192 7 38. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Stainless Steel. [MCNP5 calculations, less than 1% statist ical relative error (1 )] ................................ ................................ ................................ ........................... 193 7 39. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Nickel. [MCNP5 calculations, less than 1% statistical relative er ror (1 )] ....... 193 7 40. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Lead. [MCNP5 calculations, less than 1% statistical relative error (1 )] ......... 194

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18 7 41. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Vanadium. [MCNP5 calculations, less than 1% statistical relative error (1 )] 194 7 42. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Cobalt. [MCNP5 calculations, less than 1% statistical relative error (1 )] ....... 195 7 43. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Manganese. [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ................................ ............................... 195 7 44. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Graphite. [MCNP5 calculations, less than 1% statistical relative error (1 )] .... 196 7 45. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) BeO. [MCNP5 calculations, less than 1% statistical relative error (1 )] .......... 196 7 46. Modificat ion of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Teflon. [MCNP5 calculations, less than 1% statistical relative error (1 )] ....... 197 7 47. Modification of a flat sp ectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Aluminum. [MCNP5 calculations, less than 1% statistical relative error (1 )] 197 7 48. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Celotex. [MCNP5 calculations, less than 1% statistical relative error (1 )] ..... 198 7 49. Modification of a flat spectrum profile (blue) moderat ed by 6 cm (red) and 12 cm (green) ABS fm160. [MCNP5 calculations, less than 1% statistical relative error (1 )] ................................ ................................ ................................ ............................... 198 7 50. Modification of a flat spectrum profile (blue) moderated by 6 cm (r ed) and 12 cm (green) Concrete. [MCNP5 calculations, less than 1% statistical relative error (1 )] ... 199 7 51. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) PVC. [MCNP5 calculations, less than 1% statistical relative error (1 )] .......... 199 7 52. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green). [MCNP5 cal culations, less than 1% statistical relative error (1 )] A) Polyethylene. B) Polyethylene with thermal neutrons removed ................................ .... 200 7 53. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Paraffin. B) Paraffin with thermal neutrons removed. ................................ .................. 201 7 54. Modification of a flat spect rum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Kynar. B) Kynar with thermal neutrons removed. ................................ ................................ ... 202

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19 7 55. Mo dification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Nylon. B) Nylon with thermal neutrons removed. ................................ ................................ ... 203 7 56. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) PVT. B) PVT with thermal neutrons removed. ................................ ................................ ...... 204 7 57. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Lexan. B) Lexan with thermal neutrons removed. ................................ ................................ ... 205 7 58. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) ABS Plastic. B) ABS Plas tic with thermal neutrons removed. ................................ .............. 206 7 59. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative er ror (1 )] A) Plexiglas. B) Plexiglas with thermal neutrons removed. ................................ ............... 207 7 60. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Asphalt. B) Asphalt with thermal neutrons removed. ................................ ................... 208 7 61. Targeting Energy Band IV by using 3 cm Cd and 1 cm Hf filter materials. .................. 209 7 62. Targeting Energy Band III by using 1 cm In and 0.5 cm Ta filter materials. ................. 209 7 63. Targeting Energy Band II by using 16 cm Concrete and 1 cm Hf filter materials. ........ 210 7 64. Targeting Energy Band I by using 13 cm Asphalt and 1 mm Cd filter materials. .......... 210 7 65. Block I: 13 cm Asphalt, 1 mm Cd filter materials, 12 cm HDPE moderator. ................ 211 7 66. Block II: 16 cm Concrete, 1 cm Hf filter materials, 12 cm HDPE. ............................... 2 11 7 67. Block III: 1 cm In and 0.5 cm Ta filter materials, 12 cm HDPE. ................................ .. 211 7 68. Block IV: 3 cm Cd, 1 cm Hf filter materials, 12 cm HDPE. ................................ ......... 211 7 69. Relative difference between Pu metal and PuO 2 generated reaction rates using ideal filtering (red line) and real materials (blue line) frontal source, and real materials (green line) central source. ................................ ................................ ........................ 212 7 70. Relative difference between U metal and UO 2 generated reaction rates using ideal filtering (red line) and real materials (blue line) frontal source, and real materials (green line) cen tral source. ................................ ................................ ........................ 212 7 71. Detection device Assembly. ................................ ................................ ......................... 213

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20 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy COMPREHENSIVE MODELING OF S PECIAL NUCLEAR MATERIALS DETECTION USING 3 D DETERMINISTIC AND MONTE CARLO METHODS By Gabriel M. Ghita August 2008 Chair: Glenn Sjoden Cochair: James Baciak Major: Nuclear Engineering Sciences Our study aim to design a useful neutron signature characterization device based on 3 He detectors, a standard neutron detection methodology used in homeland security applications. Research work involved si mulation of the generation, transport, and detection of the leakage radiation from Special Nuclear Materials (SNM). To accomplish research goals, we use a new methodology to fully characterize a standard Beryllium (Pu Be) neutron source ba sed on 3 D computational radiation transport methods, employing both deterministic S N and Monte Carlo methodologies. Computational model findings were subsequently validated through experimental measurements. Achieved results allowed us to design build, and laboratory test a Nick el composite alloy shield that enable s the neutron leakage spectrum from a standard Pu Be source to be transformed, through neutron scattering interactions in the shield, into a very close approximation of the neutron spectrum lea king from a large, subcritical mass of W eapons G rade P l u tonium (WGPu) metal. This source will make possible testing with a nearly exact reproduction of the neutron spectrum from a 6.67 kg WGPu mass equivalent, but without the expense or risk of testing det ector components with real materials.

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21 Moreover, over thirty moderator materials were studied in order to characterize their neutron energy filtering potential. Specific focus was made to establish the limits of He 3 spectroscopy using ideal filter materi als To demonstrate our method ology we present the optimally detected spectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials. Finally, using knowledge gained from previous studies, the design of a He 3 spectroscopy system neutron detector, simulated entirely via computational methods, is proposed to resolve the spectra from SNM neutron sources of high interest. This was accomplished by replacing ideal filters with real materials, and comparing rea ction rates with similar data from the ideal material suite.

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22 CHAPTER 1 INTRODUCTION 1.1 Motivation C ontinuing threats to national security have placed renewed emphasis on the need for the development of efficient, accurate nuclear material interrogatio n methods, with emphasis on the need to detect Special Nuclear Materials (SNM). Therefore, a ctive and passive interrogation techniques for the detec tion of SNM are being investigated for many applications in the areas of nuclear safeguards, nuclear nonprol iferation, and homeland security 1,2,3 Screening systems designed to detect certain classes of SNM face highly competing goals; Hence, the probability of detection f or any dedicated screening system must be maximized. Optimal performance for detection systems can be readily designed into any system under development using computational methodologies. We incorporate a unique ability to effectively perform large scale 3 D forward, adjoint, and Monte Carlo radiation transport simulations for SNM detection using parallel computing methods for robust simulations as well as experimental validation of the computational models. This work directly supports National Nuclea r Se curity Administration (NNSA) and Department of Energy (DoE) initiatives to verify treaties and detect nuclear related activities, since the goals of this research project are related to modeling and validation of the generation, transport, and detection of the leakage radiation from SNM. 1.2 Study Overview Our primary research objectives of the work performed under the auspices Florida Institute of Nuclear Detection and Security (FINDS) can be summarized as follows: Development of a procedure for total sou rce construction employed in the SNM computational modeling 4

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23 This procedure will be used throughout the research work for characterization of neutron sources. Validation of the adjoint coupling approach through reaction rate calculations using forward an d adjoint S N and forward Monte Carlo computational methods 5 C omparative results of the three computational proce dures are presented for an isotropic volumetric source folded with a scalar adjoint function Using several neutron adjoint 3 D parallel compu tations the efficiency of the PENTRAN code 6 with various decomposition strategies is also demonstrated. Design of a viable model for the P l u tonium Be ryllium (Pu Be) neutron source capsule for complete characterization of Pu Be leakage spectrum using dete rministic and Monte Carlo computational techniques and experimental validation of the model. 7 We present a new methodology developed for the 3 D computational radiation transport assessment s of a Pu Be neutron source using the procedure for source term c onstruction previously described, validated through experimental measurements. Generation, design and spectral characterization of SNM neutron sources using deterministic and Monte Carlo computational techniques. 8 Laborious work to construct several SNM sources based on the methodology developed and validated for the Pu Be source is described along with a comprehensive comparison between the metal and oxide types of sources. Design of a shield for the Pu Be neutron source capsule to emulate a W eapons G rad e P l u tonium (WGPu) neutron spectrum. 9 We present our patented invention of a unique shield design that transforms the complex neutron spectrum from a harder Pu Be neutron source into a very close reproduction of a fission spectrum signature leaking from a sphere of WGPu metal with the experimental validation. 10,11 Detection of SNM.

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24 This part of the research includes our efforts to develop a useful neutron detection device using 3 He detectors, a standard neutron detection methodology widely used in homelan d security applications. To accomplish this goal, we thoroughly studied over thirty moderator materials focusing on their energy filtering effects. 12 We analyzed and established the limits of 3 He spectroscopy using high density polyethylene and ideal filte r materials. 13 This work, based on the computational radiation transport methods, enabled us to design a 3 He spectroscopy system using real filtering materials.

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25 CHAPTER 2 BACKGROUND AND LITER ATURE REVIEW Our study involved neutron source generation, inv estigations of neutron detection performance, and computational methods. We first examined the neutron sources under Be capsule and SNM sources) and the methods of SNM detection. The PENTRAN S N deterministic 6 and MCNP5 Monte Car lo 14 transport codes will be also discussed, along with the ORIGEN ARP code from SCALE5.1 package, 15 which was used to generate intrinsic source energy spectra, and utilized as input for MCNP5 and PENTRAN calculations. Finally, the cross section libraries will be considered. 2.1 The Pu Be Capsule and Special Nuclear Materials The Pu Be sources can be used as didactic source materials SNM detection evaluation protocols. Based on a mixture of an emitting isotope ( 239 Pu) with a suitable target material (Be), the neutrons are produced through the reaction given in Equation 2 1. (2 1) The Pu Be source is probably the most widely used of the ( ) isotopic neutron sources 16 One of the reasons is that the maximum neutron yield is obtained when beryllium is chosen as the target for particles ; another reason that can be taken into consideration is the stability of the source which has a half life based on 239 Pu decay of ~2 4,000 years. Unfortunately, limited specific information exists for many of the Pu Be sources currently in service, regarding the Pu isotopic content and the inner geometry of the capsule. Accuracy of the results depends on the viability of the model used for the capsule. A spectrometric non destructive method for verifying the plutonium content of Pu Be neutron sources was reported spectra taken in the far field of the sample. 17 The Pu content of the sources was evaluated from the count rates of the peaks of 239 Pu relying on the assumption that the rays

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26 are coming to the detector parallel to each other. Another method of quantitative assay of Pu Be neutron sources is based on neutron coincidence technique. 18,19 Reported accuracy of the method s is about 15% For designing a viable model, w e used the data provided by manufacturer: the masses of beryllium and plutonium (weapons grade, with an expected isotopic composition: 0.005% 238 Pu, 93.54% 239 Pu, 6.00% 240 Pu, 0.44% 241 Pu, 0.015% 242 Pu ), the source strength on the shipping date in 1971 and the dose specified for the source. W e investigated also the impac t of uncertainty in Pu isotopic composition. V ariation of the 241 Pu mass will yield a different rate of Pu Be source decay, while a variation in mass of the other Pu isotopes will result in a different initial emission of neutrons. As expected, 20 the ratio between the maximum and original yield increases directly with the weight fraction of 241 Pu. Most Pu Be sources have an outer stainless steel jacket and a n inner tantalum jacket, with the Pu Be homogeneously distribut ed throughout the inner jacket. Our computational model of the Pu Be ( ) SNM neutron source is designed in the form of mixed Pu Be, an intermetallic compound with a typical density 21 of 4.35 g/cm 3 surrounded by 0.25 cm thick stainless steel (outer material) and a 0.25 cm thick tantalum (highly dense inner capsule) metal. Figure 2 1 shows the 3 D MCNP model geometry rendered by MCNP Visual Editor Computer Code 22 (VISED). Our assumptions, regarding the inner geometry of the source and the plutonium isotopic composition, were experimentally validated; our experiments compare well with computational results to within 10%. Reliable numerical sources for various isotopic components of plutonium (metal and oxide), and uranium (metal and oxide) of various enrichments in 235 U were required for our analysis. Therefore, burnups were computed with different reactor fuels for varying times using

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27 the SCALE5.1 package to yield the discharge isotopic content of plutonium metal and oxide, and also final enrichments established for uranium metal and uranium oxide. To provide assessments on detection for the parcel screening system, all source data was cataloged as reference sources for later use in criticality and source strength applications. Characterization of SNM enables us to propose a unique shield that transforms the complex neutron spectrum from a Pu Be neutron source to nearly exactly the fission neutron spectrum signature leaking from a WGPu metal mass ( US Patent Serial No. 61/027988 ) Entire design was derived completely through the use of computational transport. This Nickel co mposite alloy shield assembly enables the harder Pu Be source spectrum ( with an average neutron energy of 4.61 MeV) from a small encapsulated standard 1 Ci Pu Be source to be transformed, through interactions in the shield, so that neutron leakage spectr um is shifted in energy to become a close reproduction of the neutron leak age spectrum from a large subcritical mass of WGPu metal ( having a mean energy 2.11 MeV). U tility of this shielded Pu Be surrogate for WGPu is clear, since it directly enables detect or field testing without the expense and risk of handling large amounts of SNM as WG Pu. Also, conventional sources using 252 Cf which is difficult t o produce 23,24 and decays with a 2.65 y half life, could be replaced by this shielded Pu Be technology in o r der to simplify operational use since a sealed Pu Be source relies on 239 Pu (T=24, 110 y) and remains viable for more than hundreds of years. 2.2 Detection of Special Nuclear Materials Due to the fact that neutrons have no charge, they cannot be directly detected, and thus neutron detection techniques are typically based on nuclear reactions that create charged particles which can, in turn, be detected by radiation detectors. Slow neutron detectors, designed for neutron energies below the cadmium cutoff of about 0.5 eV, are detected via nuclear conversion

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28 reactions, such as ( ) and ( n,p ) reactions. All common techniques used to detect slow neutrons result in heavy charged particles 16 as shown in Figure 2 2. T hree conversion reactions commonly used in dete ctors are given in Equations 2 2, 2 3, and 2 4 : (2 2) (2 3 ) (2 4) A ccording to conservation of momentum and energy the energy from the reaction is shared by the two reacti on products, the particle or proton ( p ) and the recoil nucleus. The 6 Li( ) reaction (Equation 2 2) is usually used in scintillators. One possibility is LiI which is chemically similar to NaI. Due to the density of enriched 6 LiI(Eu) crystals, a 10 mm thick detector is almost 100% efficient for low energy neutrons ranging from thermal energies up to about 0.5 eV. For LiI the scintillation efficiency is nearly the same for both electrons and heavy ray rejection characteristics will therefore be in ferior to that of typical gas ray can deposit only a small fraction of its energy. Lithium is also incorporated as a component of scintillating glass matrices for detection of neutrons with intermediate energies (also called fast neutrons). Lithium glass scintillators are used in time of fl ight measurements due to their relatively fast time response of less tha n 100 ns. Silicate glasses of various compositions, generally with cerium activation, are used as the scintill ation medium. Due to its nonlinear response to the tritons and particles produced from lithium reaction, the use of this material at room temperature is vulnerable. Nonlinearities can be

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29 reduced by cooling the crystal to liquid nitrogen temperature even though the practical problems involved in cooling the crystal a re significant. Unfortunately, glass scintillators show a much reduced light output per unit energy for ray discrimination ability of these scintillators is therefore not as good as other detectors in which the response is more uniform for all particles. 25 ray backgrounds. However, optical self absorption may be present because of cerium oxidation that takes place during the process of drawing the fiber. 16 The 10 B( ) reaction (Equation 2 3) is employed in BF 3 proportional tubes where t he BF 3 gas is usually enriched in 10 B, and it has to be used at lower absolute pressures ( between 0.5 and 1.0 atm ) in order to get good perfo rmance as a proportional gas. Introducing the boron in a form of solid coating in the interior walls is an alternative approach, less satisfactory than BF 3 tubes in ray discrimination ability. Scintillators made by fusing B 2 O 3 and ZnS and boron loaded plastic scintillators are available options but they are less effective at ray backgrounds compared to BF 3 proportional tubes; the secondary ray interactions tend to deposit all their energy in the solid scintillators not a small fraction as in the BF 3 gas. Furthermore, organic scintillators produce much more light per unit energy from electrons than from the heavy charged particles produced by neutrons, while the ionization yield in g ases is very nearly the same for each. Thus the inherent separation in ray and neutron pulses from the BF 3 tube is not any longer observed from the boron loaded plastic scintillator. 26 In a similar way, 3 He employing a 3 He ( n, p ) reaction (Equation 2 4) is used as a conversion target and proportional gas in the 3 He proportional counter. This is an attractive alternative for

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30 slow neutron detection, the cross section being higher than that of the boron reaction. Compared with BF 3 tubes, 3 He counters can be operated at much higher pressure with acceptable gas multiplication behavior and are therefore preferred for those applications in which maximum detection efficiency is important. 27 The 3 He tubes are more resistant to effects of aging (prov ided gas leakage is minimized), a common degradation of the proportional counters related to the contamination of the anode wire and cathode wall by molecular disassociation products produced in the avalanches. C ross sections of the neutron capture r eactio ns described in Equations 2 2, 2 3, and 2 4 tend to decrease rapidly with increasing neutron energy. S low neutron detectors can be surrounded by a hydrogen containing material that moderates the neutrons down to energies where the detection efficiency is h igh. This moderation is done by elastic scattering, and the neutron can be slowed down most effectively by hydrogen nuclei making polyethylene and paraffin the most commonly used moderators. Retaining a large fraction of the neutrons near a certain depth is an important effect of the moderator; these neutrons have had enough collisions to lose nearly all their kinetic energy. If a thermal neutron detector is placed in this region, the chance of detecting neutrons is optimized. Therefore, t he detection effi ciency of a mode rator detector combination depend s on the neutron energy and the thickness of the moderator. Due to inelastic scattering or absorption of the neutron in moderator, an undesirable reaction is the rays which are difficult to b e detected; for example, neutron capture in hydrogen releases a 2.224 ray. Of the many types of neutron spectrometers that have been developed, the system known as the multi 28 spectrometer has been built and used by more laboratories than any other. 29,30 Detection system consists of a thermal neutron

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31 sensor placed at the centre of a number of different diameter moderating spheres. These are almost invariably made of polyethylene, and are usually mad e to exact inch, or half inch diameters. Thermal sensor plus moderating sphere combination has sensitivity to neutrons over a broad energy range. However, the sensitivity for each sphere peaks at a particular neutron energy, depending on the sphere diamete r. From the measured readings of a set of spheres, information can be derived about the spectrum of the neutron field in which the measurements were made. Derivation of this spectral information is not simple, and the validity of BS results has often been questioned 31 information about the spectra. 32 Among the design s that have evolved from the BS systems is the use of a single block of moderator containing either several extended, position sensitive thermal neutron detectors 33 or a number of small thermal neutron detectors 34 m ounted at different positions. T hen the position of neutron detectors replaces the sphere diameter as a variable in the response matrix and all measurements are made simultane ously, without interruption for geometry changes. In our approach we consider various configurations of moderating and attenuating materials placed around neutron sensitive detectors in order to isolate different parts of the neutron spectrum. To accomplis h our goal, neutron transport simulations were performed among optimum of neutron interactions to facilitate positive detection and characterization of the incid ent neutrons. We have demonstrated that the spectral sensitivity of neutron spectroscopy can be assessed using computational transport studies Based on an extended study of high density polyethylene (HDPE) moderators revealing the practical limits of the neutron spectroscopy using gas

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32 proportional detectors, we extracted the optimally detected spectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials We have also selected a number of candidate filte ring materials, finalizing with a design of a neutron detector array in an optimal methodology to resolve the spectra from SNM neutron sources using 3 He detectors by replacing the ideal filters with real materials. 2.3 Computational Transport Methods Accur ate simulation of neutral p article transport in a system is directly accomplished via solution of the linear 35,36 which describes the behavior of neutral particles in terms of spatial, angular, and energy variables as they interact in a system; the steady state form of the transport equation is given in Equation 2 5, using standard notation: (2 5 ) where : = spatial coordinate (the position of particle); = solid angle (the direction of particle); E = energy; = angular flux; = total macroscopic cross section; = macroscopic differential scattering cross section ; = source term; Left side of Equation 2 5 represents streaming and collision terms (loss), and the right side represents scattering and other sources (gain). Since it describes the flow of radiation in a three

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33 dimensional ( 3 D ) geometry with angula r and energy dependence, this can be viewed as one of the most challenging equations to solve in terms of complexity and model size Therefore, r endering a deterministic computational solution for a large problem requires a robust parallel transport solver and a high performance computing system. Although typically less demanding to initiate, large scale Monte Carlo simulations also require significant computer resources and ble, statistically based solutions. In Chapter 3 a procedure will be presented that was develop ed to investigate the effective multiplication in problems using the steady st ate multi group form of Equation 2 5. 2.3.1 The PENTRAN S N Transport Code System The S N method is a deterministic approach that discretizes the angle, energy, and physical spatial variables into a finite number of discrete angular ordinates, energy groups, and spatial grids over the entire phase space system. The PENTRAN code system can be used for 3 D multigroup forward and adjoint discrete ordinates (S N ) simulations. The PENTRAN system is actually a suite of codes that allow one to readily generate mesh geometries, solve 3 D transport models, and automatically colla t e parallel data I t has been specifically designed for distributed memory, scalable parallel comput er architectures using the Message Passing Interface (MPI) library. Hybrid domain decomposition of the phase space among the angular, energy, and spatial variables with an adaptive differencing algorithm and other numerical enhancements make PENTRAN an extremely robust s olver with a 0.975 parallel 37 ). Numerous simulations have been performed using the PEN TRAN code system, including a few in ternational benchmark computations. 38,39,40 M any advanced numerical features in PENTRAN, including adaptive differencing with a two level parallel angular memory structure in a scalable architecture, are such that it is well suited for deterministic work i n this research; at present, it is

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34 likely that PENTRAN is the only deterministic code to be directly capable of rendering a solution to extremely large scale trans port detection problems in a short time using parallel computing. PENTRAN has demonstrated ex cellent agreement with both Monte Carlo and experimental flux measurement in a variety of problems in reactor physics, detection, and medical physics applications. 4,5,41 2.3.2 The MCNP5 Monte Carlo Code and SCALE5 .1 Code Systems The Monte Carlo computatio nal method is currently the most widely used, straightforward technique applied to particle transport, and has been widely demonstrated as being capable of representing very complex geometries in a rigorous manner using robust particle physics by statistic ally tracking the outcome of individual particle histories. The MCNP5 is a globally used general purpose, continuous energy, coupled neutron photon electron Monte Carlo transport code developed at the Los Alamos National Laboratory 14 It can be used in s everal transport modes, and was developed with over 500 person years of effort. It operates in neutron only, photon only, electron only, and combined modes including neutron photon, neutron photon electron interactions, photon electron, and electron photo n interactions. C apability to calculate k eff eigenvalues for fissile systems is also a standard feature. The SCALE5 .1 package 15 contains a suite of codes that are very versatile for performing source determinations and numerous gen eral nuclear modeling applications. In particular, the ORIGEN ARP code determines the decay of any source materials used for generation of the energy spectrum of the intrinsic source. Both MCNP5 and SCALE5 .1 are distributed through the Radiation Safety Inf ormation Computational Center at Oak Ridge National Laboratory (ORNL). Depending on the type of problem to be solved, the deterministic and Monte Carlo methods can be used together in order to achieve accurate computational results in an efficient

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35 manner. There are applications presented in Chapter 6 and Chapter 7 where the accuracy of the results is improved by using the MCNP5 code for radiation transport in air (avoiding possible ray effects for large transport distances in air using deterministic S N meth ods). Projected sources obtained at the surface of the material/moderator are further used to obtain a global solution based on deterministic S N calculations in a more efficient manner. 2.4 Cross Section Library Considerations Since computational transpor t methods are necessary to determine the total leakage for specific source scenarios, adequate cross section libraries must be applied. 42 Monte Carlo users can readily access point wise cross sections in MCNP5, although care needs to be taken to select app ropriate thermal treatments [such as the S( ) cular scattering for moderators] and appropriate library temperatures. Also, deterministic cross section libraries must be evaluated carefully as to how they are applicable to a given problem. Reasonable agreement between Monte Carlo and determ inistic results should be expected, and questions should be raised to explain differences. Based on available data for transport computations, to demonstrate consistency between deterministic and Monte Carlo transport computations, we have considered the following computational approaches : 3 D Monte Carlo with MCNP5 using continuous energ y ENDF/B VI data libraries; 3 D S N with PENTRAN using the BUGLE 96 67 group broad group library, 43 derived from ENDF/B VI, partitioned as a coupled 47 group neutron/20 g roup gamma library. The MCNP5 code uses the latest point ) energy data based on ENDF/B VI. The BUGLE 96 multigroup cross section library is based also on ENDF/B VI data and it has been initially produced and tested for light water react or shielding and reactor pressure vessel dosimetry applications. The BUGLE 96 data sets have been processed without upscatter in the thermal groups. We note that for the fast assemblies modeled with Monte Carlo, no S( )

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36 light element thermal neutron molecular scattering effects were necessary; however, this may be necessary in determining response in 3 He and other detectors, since these detectors rely heavily on moderated detector responses. BUGLE 96T multigroup cros s section library which retains the upscatter reactions for groups below 5 eV can be considered for the S N calculations. N eutron group structure for the BUGLE 96 library is given in Table 2 1; note that increasing group numbers progress from high ener gy t o low energy. For photons there are 20 energy groups in BUGLE 96, numbered from 48 (high energy photons) to 67 (low energy photons). Again, note in Table 2 2 that increasing group numbers progress from high energy to low energy. Next chapter presents the computational procedures developed for characterization of the source terms and reaction rate calculations using forward S N adjoint S N and forward Monte Carlo. Efficiency of the PENTRAN code in performing 3 D parallel computations is also demonstrated.

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37 Table 2 1. Upper energies of neutron energy groups in BUGLE 96. Group MeV Group MeV Group MeV Group MeV 1 2 3 4 5 6 7 8 9 10 11 12 1 .7 3 E+01 1 .4 2 E+01 1.2 2 E+01 1 0 0E+01 8.61 E+00 7.41 E+00 6.07 E+00 4.97 E+00 3.68 E+00 3.01 E+00 2.73 E+0 0 2.47 E+00 13 14 15 16 17 18 19 20 21 22 23 24 2.37 E+00 2.35 E+00 2.23 E+00 1.92 E+00 1.65 E+00 1.35 E+00 1 .00E+00 8 21 E 01 7.43E 01 6 08 E 01 4 98 E 01 3 69 E 01 25 26 27 28 29 30 31 32 33 34 35 36 2 97 E 01 1 83 E 01 1 11 E 01 6.74 E 02 4.09 E 02 3.18 E 02 2.61 E 02 2 .42 E 02 2.19 E 02 1.50 E 02 7.10 E 03 3.35 E 03 37 38 39 40 41 42 43 44 45 46 47 1.58 E 03 4.54 E 04 2.14 E 04 1.01 E 04 3.73 E 05 1.07 E 05 5.04 E 06 1.86 E 06 8.76 E 07 4.14 E 07 1. 00 E 07 Table 2 2. Upper energies of photon energy groups in BUGLE 96. Group MeV Grou p MeV Group MeV Group MeV 48 49 50 51 52 1.40E+01 1.00E+01 8.00E+00 7.00E+00 6.00E+00 53 54 55 56 57 5.00E+00 4.00E+00 3.00E+00 2.00E+00 1. 5 0E+00 58 59 60 61 62 1.00E+00 8.00E 01 7.00E 01 6.00E 01 4.00E 01 63 64 65 66 67 2.00E 01 1.00E 01 6.00E 02 1.01 E 0 4 3.73 E 05 Figure 2 1 The MCNP model of a t ypical construction for Pu Be sources

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38 Figure 2 2. Common reactions used for slow neutrons detection.

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39 CHAPTER 3 COMPUTATIONAL PROCED URES This chapter describes the computational resources necessary for performing a comparative analysis of deterministic and Monte Carlo radiation transport computations related to the generation, transport, and detection of the leakage radiation from radiation sources. Here, we will present a compar ison between 3 He detector response in a graded 3 He detector moderator array, using forward MCNP5 calculations, and forward and adjoint PENTRAN calculations, along with the analytical approach of this procedure. Then, the efficiency of the PENTRAN code in performing 3 D parallel computations with various decomposition strategies is demonstrated, achieving a parallel (Amdahl) fraction of 0.96 with scaling up to 16 dedicated processors. Finally, we will present an important procedure developed to computationa lly determine the total source for deterministic calculations. This procedure will be used for the characterization of the Pu Be and SNM sources in Chapters 4 and 5. 3.1 Forward versus Adjoint Transport Calculation Procedures 3.1.1 Computational Approach Steady state multi group form of the transport equation (standard formulation of linear Boltzmann equation) operating on the forward group angular flux is given in Equation 3 1 : (3 1) w here : = spatial coordinate (position of particle); = solid angle (direction of particle);

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40 = angular flux for energy group g ; = total macroscopic cross section fo r energy group g ; = macroscopic scattering cross section from group to g (group transfer cross section); = intrinsic source term for group g Principally, scattering from all other groups into group g is dominated by down scattering from higher energies to lower energies. Using the adjoint function property, given in Equation 3 2, for real valued functions and the forward multi group transport operator H, t he adjoint transport operator H + can be de rived. (3 2) where represents integration over all independent variables and is the adjoint (or importance) function which is associated with the importance of particles with resp ect to an objective. Using Equation 3 1 it can be seen that the forward operator is given in Equation 3 3: (3 3) The a ngular adjoint (importance) function is Applying the vacuum boundary condition that pa rticles leaving a bounded system have an importance of zero in all groups (converse of the forward vacuum boundary condition) and requiring a well define importance function the above equations leads to the multi group adjoint transport operator (Equatio n 3 4) : (3 4)

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41 Note the minus sign on the streaming term indicates that particles travel toward high importance regions (this is opposite the forward flux which flows toward low density regions), where scattering progresses from g roup g to other groups g (i.e., its progenies). A djoint function for our application that will be presented in the next section is aliased to neutron importance with respect to an absorption in 3 He to yield an ( n,p ) reaction. If such a fixed forward neut ron source/detector problem is proposed, the neutron flux must satisfy the transport equation (Equation 3 5) : (3 5) and the inhomogeneous adjoint equation should be satisfied with an adjoint source aliased to the group detec tor response cross section (Equation 3 6): (3 6) Forming a commutation relation between Equations 3 5 and 3 6, and using Equation 3 2, we obtain the detector response R as follows (Equation 3 7): (3 7) From Equation 3 7, it is clear that detector response can be obtained by complete integration of the source distribution with the adjoint function for any arbitrary source distribution. The R can be computed directly from the results of either of several forward transport computatio ns for each neutron source, or one single adjoint transport computation. 3.1.2 Comparison of Forward, Adjoint, and Monte Carlo Results To solve for the adjoint function, a forward transport sol ver can be directly used if the group total cross sections and sources are reordered (G to 1), and the cross section scattering matrix transposed. In this case all angles are considered to be defined implicitly in opposite

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42 (negative) directions, with group G for adjoint functions reported into the forward code as group 1, group G 1 adjoint functions reported as group 2, etc. This is precisely how the adjoint is solved using the PENTRAN system, although the treatment of cross sections is performed internally by the code. W e completed 3 D t ransport models using forward and adjoint S N and Monte Carlo for a trial design of a 3 He m oderator array Figure 3 1A shows the deterministic PENTRAN discretized model visualized by using TECPLOT Software. 44 Figure 3 1B sh ows the same 3 D geometry modeled set up for the MCNP5 Monte Carlo code rendered by the MCNP Visual Editor Computer Code (VISED). In reference to a 3 He detector, in the traditional forward case, the standard Boltzmann transport equation (Equation 3 1) mus t be solved to yield a scalar flux for a specific neutron source q Detector response in the 3 He can be numerically computed in the conventional manner using group cell wise scalar fluxes and detector cross sections, as given in Equation 3 8: (3 8) where: R = detector response (counts/s); = detector volume (cm 3 ); = spatial location of 3 He; = spatial and energy dependent scalar flux (n/cm 2 /s); = spatial and energy dependent 3 He macroscopic absorption cross section (1/cm); = i th cell scalar flux for group g (n/cm 2 /s);

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43 = i th cell 3 He macroscopic absorption cross section for group g (1/cm); = i th cell volume (cm 3 ). In the adjoint case, the adjoint equation must be solved using an adjoint source that is equal in magnitude to the detector macroscopic absorption cross section placed in each location occupied by 3 He tubes. This yields the adjoint function throughout the problem phase space, and represents the importance of neutrons in each spatial locations and energy group relative to a response in 3 He tubes. Then, the 3 He tube count rate R due to any neutron source q placed in a spec ific location is computed as given in Equation 3 9: (3 9) where: R = detector response (counts/s); = source volume (cm 3 ); = spatial location of source cell s; = spa tial and energy dependent scalar adjoint flux from detector d ; = spatial and energy dependent source (n/cm 3 /s); = i th cell scalar adjoint function for group g from detector d ; = i th cell source density for group g (n/cm 3 /s); = i th cell volume (cm 3 ). Therefore, the appropriate adjoint source used for this problem is a unit source weighted by the group absorption cross section for 3 He, placed in each location of the d etector.

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44 Our model (Figure 3 1A) is based on 12 coarse meshes along the x axes, with 137,120 3 D fine mesh cells. Coarse meshes correspond to 12 cells: 6 banks of three 3 He detectors embedded in stainless steel (first two banks), copper (third and fourth banks), and dow foam (last two banks); in between them, 6 moderators (0.36 cm thick polyurethane in first cell, then 0.1 cm thick graphite, 1.3 cm thick aluminum, 4.4 cm thick aluminum, 4.4 cm thick graphite, and 4.2 cm thick paraffin). Vacuum boundary con dition is prescribed at x = 0 cm, x = 31 cm, y = 0 cm, y = 8 cm, z = 0 cm, z = 20 cm. Each 3 He tube was assumed to be 2.54 cm (1 inch) in diameter and 20 cm height. In 3 He regions, the very fine discretization of the model (0.16 cm x 0.16 cm x 1 cm) giv es a good approximation of the 3 He cylindrical tubes and permit s us to compare the responses computed using forward and adjoint deterministic solutions, and the Monte Carlo results. We are using in our calculations the total (including multiplication) leak age of an Pu metal isotropic volumetric neutron source consisting in 1.442E+05 n/s, in first cell on the front panel of the assembly ( the polyurethane cell ). Since the source volume was 0.36 cm x 8 cm x 20 cm = 57.6 cm 3 we have a source density of 2503.5 n/cm 3 /s. In Section 3.3 is presented the methodology for calculating the total leakage. Broad group neutron cross sections were derived and mixed from material mass fractions and bulk densities using BUGLE 96 library. It is assumed that these cross section s are generally applicable to this problem. To find the optimum S N order, we performed a convergence study, increasing the number of directions for the angular quadrature from 80 (S 8 ) to 288 (S 16 ) considering P 3 scattering anisotropy. Maximum relative diff erence between S 8 solution and S 10 was 7.6 % per neutron energy group. We reached a relative difference between S 14 and S 16 of less than 1.2 % per neutron energy group; hence we select to use for our simulations S 16 angular

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45 quadrature. Comparing P 1 P 3, an d P 5 order of anisotropy we observed that maximum relative difference between P 3 and P 1 is about 3 % and between P 3 and P 5 is less than 2 %. Based on our study we decided to continue our computational work for this problem by running S 16 angular quadrature P 3 scattering anisotropy. As shown in Table s 3 1 (data plotted in Figure 3 2), good agreement was achieved for computation of the reaction rate in 3 He tubes (for tube banks in cells 2, 4, 6, 8, 10 or 12, as indicated ) given that the Monte Carlo implement ed continuous energy ENDF /B VI cross sections, and the S N computations were accomplished via the multigroup BUGLE 96 library. Small differences between the forward and adjoint calculations can be attributed to numerical truncation effect in accomplishing e ach calculation, since grid spacing, adaptive differencing, and numerical treatments spanning the groups can, as a whole, affect the integral outcome. 3.2 The 3 D Parallel S N Computational Performance Parallel performance for analyzing and quantifying pa rallel speed up and efficiency was measured using an adjoint source in the 5 th 3 He tube bank for the discretized model in Figure 3 1A (36,900 3 D mesh cells). Several parallel S 16 P 3 computations of the neutron adjoint were computed using the PENTRAN Code with the BUGLE 96 multigroup library on up to 16 dedicated processors composed of 64 bit processors accessing 4 Gb of RAM each. Parallel speed up, S p (Equation 3 10), measures the overall reduction in computing time to solve a problem, and is defined as t he wall clock time on a serial (single) processor ( ) divided by the wall clock time on P processors ( ): (3 10)

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46 Parallel efficiency, Ef (Equation 3 11), measures the economic adva ntage of the parallelization by comparing the speed up factor to the allocated number of processors: 45 (3 11) It is assumed here that the parallel algorithm overhead (the extra executable code and storage required to expedi te parallel execution) is negligible during single processor execution. U pper bound on anticipated parallel speed up can be determined by applying Law which states that given the fraction of a code that is parallelizeable: 0 < < 1 the maximum observed speedup for P processors with parallel communication time ( ) is equal to (Equation 3 12): (3 12) where, in the limit of an infinite number of processors and assuming = 0 (Equation 3 13): (3 13) For parallel efficiency we have (Equation 3 14): (3 14) For our problem, the results are given in Table 3 2; the 16 processor run, using angular decomposi = 0) depicting maximum theoretical speed up based on parallel fraction and associated efficiency as a function of the number of processors is provided for illust ration in Figure 3 3.

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47 We found that for this problem, the PENTRAN code yielded an Amdahl parallel fraction of 0.96. This model assumes a zero communications cost ( estimate of parallel fraction, since attributing a non zero communications cost will allow for an increased parallel fraction; therefore, the true parallel fraction is > 0.96. Different decomposition strategies will cause the relative speedup to not follow a specific constant parallel code fraction, since different decompositions lead to different costs; this can also be influenced by specific machine parameters, processors per node, etc. These results confirm that PENTRAN is highly scalable, maintaining consistent speedup performance results with various domain decomposition strategies. Based on application of Equation 3 13, we find that for this problem and resulting parallel fraction, the maximum theoretically observed speed up for PENTRAN in this case is estimated to be = 25 (assuming a bound of 0.96 on parallel code fraction), regardless of the number of additional processors added to the problem. 3.3 Total Source as a Function of Energy To capture the spectral fidelity of SNM in radiation transport throughou t an assembly, and to computationally determine the detectable radiation leaking from SNM, systematic procedure (for comparing S N and Monte Carlo) may be applied inspired by the total (multiplied) source calculation formula (Equation 3 15) composed by the intrinsic term (based on inherent material decay properties) and the induced term (multiplication) : (3 15) where: = the intrinsic [s.f. ( ) reactions] neutron volume tric source density (n/cm 3 s 1 ) ;

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48 = the system reactivity based on fission multiplication ; = multiplication factor (eigenvalue); = the induced (multiplied) n eutron source density (n/cm 3 s 1 ) ; = the volume of the source (cm 3 ) Provided that for direct comparison energy bin tallies in Monte Carlo simulations are equivalent to the deterministic ( S N ) group structure, the procedure is describe d as follows. Perform an eigenvelue (criticality) radiation transport computation to obtain t he energy group dependent neu tron leakage ( signified by the group subscript g ) per induced fission reaction scaled then by the multipli cation of the intrinsic sou rce [the intrinsic sources include spontaneous fission (s.f.) and alpha neutron ( )]. Finally, add the leakage obtained from a steady state 3 D radiation transport computation, using the intrinsic source as shown in Equation 3 16 : ( 3 16 ) where: = the energy group g induced fission neutron source from a criticality computation, where V constitutes the volume of SNM mass in the system; = the energy group g in duced fission neutron leakage at the SNM material surface, where A constitutes the surface area of the closed surface SNM mass in the system;

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49 = the energy group g intrinsic neutron leakage at the SNM material surface, where A constit utes the outer surface area of the SNM mass in the system; Using Equation 3 14 the total multipli ed sou rce leakage is determined in Equation 3 17 from a sum of the total source from all energy groups: ( 3 17 ) I mportant fac t is that the source term of Equation 3 16 can be used to identify specific energies in the leakage spectrum that might be computationally opti mized using filters (e.g. Cd, Hf Fe, Cu, Ni, etc) and moderators. A s imilar set of equations can be used to descr ibe rays (intrinsic and induced) leaking from the SNM system. net neutron or gamma currents crossing (leaking from ) the outer SNM surface are almost equal (within 0.01 %) to the exiting (positive outward no rmal) positive partial current (see Equation 3 18), since almost no neutrons or gammas exiting from an assembly placed in air return into the multiplying system e.g. ~1 in 10 4 neutrons, and ~0.5 in 10 4 photons return for a 4 kg Pu (94% 239 metal sphe re: ( 3 18) Other objects and structures impacting the detection scenario will result in neutrons or gammas from higher energies streaming from the assembly to scatter in surrounding materials, lose energy, and subsequently appe ar in lower energies (higher energy group numbers), creating attributable re entrant currents at the SNM surface As mentioned, these must be evaluated on a case by case basis as a function of position (and time) for the model being studied, since the problem multiplication can be affected.

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50 In the following chapters, the research that will be presented, will employ the use of the computational procedures developed here for characterization of the source terms and reaction rate calcu lations using forward S N adjoint S N and forward Monte Carlo. For Pu Be (Chapter 4) and SNM (Chapter 5) neutron source assessments, a comparison will be presented between the results obtained using deterministic PENTRAN models using the multigroup BUGLE 9 6 cross section library, and the MCNP5 Monte Carlo computational method using continuous energ y ENDF/B VI data libraries.

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51 Table 3 1 Comparison of Reaction Rates in Each 3 He Tube bank using Forward S N Adjoint S N and Monte Carlo results for a 4kg Spherical Pu m etal neutron leakage s ource Cel # PENTRAN (BUGLE 96) forward PENTRAN (BUGLE 96) adjoint MCNP5 (ENDF BVI) forward Rel. error (MCNP5) Rel. diff. (%) PEN(fwd) vs MCNP Rel. diff. (%) PEN(fwd) vs PEN(adj) 2 16.470 16.220 15.82 5 0.0001 4.08 1.52 4 6.741 6.706 6.677 0.0001 0.96 0.52 6 3.203 3.178 3.130 0.0002 2.33 0.78 8 1.713 1.675 1.760 0.0010 2.67 2.22 10 13.410 1 3 270 13.396 0.0006 0.10 1.04 12 10.520 10.45 0 10.700 0.0006 1.68 0.67 Table 3 2. Co mparison of PENTRAN performance based on different decomposition strategy. Run PENTRAN Decomposition Strategy # Procs Angle # Procs Group # Procs Space # Total Procs (P) Sp= Speed up Factor Ef= Efficiency (Sp/P, %) 1 Angular 4 1 1 4 3.85 96.25 2 Sp atial 1 1 6 6 3.94 66 .00 3 Angular 8 1 1 8 6.54 82 .00 4 Angular Spatial 4 1 3 12 7.73 64 .00 5 Angular Spatial 4 1 4 16 9.47 59 .00 6 Angular 16 1 1 16 10.89 68 .00 A B Figure 3 1. Moderated 3 He Tube Bank models. A) PENTRAN model, B) MCNP5 Model.

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52 Figure 3 2 Comparison of Reaction Rates in Each 3He Tube bank using Forward S N Adjoint S N and Monte Carlo Results for a Pu Metal Neutron Source A Figure 3 3. Speedup B) Efficiency.

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53 B Figure 3 3. Continued.

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54 CHAPTER 4 METHODOLOGY FOR EXPE RIMENTAL AND 3 D COMPUTATIONAL RADI ATION TRANSPORT ASSESSMENT OF PU BE NEUTRON SOURCES To fully characterize the net leakage terms from our Pu Be neutron source, we applied the procedure described Section 3.3 for deterministic calculations, using both, steady state fixed source and criticality 3 D radiation transport computations Then, we compare the results for intrinsic and total leakage obtained using deterministic (PENTRAN) and Monte Carlo (MCNP5) methodo turns off fission neutron production. For total leakage, considering intrinsic and multiplication ased on limited s chematic and technical data documented in the original source shipment data from Mound Laboratories [Ref: Shipping Data Plutonium Neutron Source, Monsanto Research Corporation Mound Laboratory Miamisburg, Ohio, 1971], the source originator that manufacture d the source ~37 years ago, the transport model was performed Figure 2 1 shows the 3 D MCNP5 Monte Carlo model geometry rendered by VISED and Figure 4 1 shows the deterministic PENTRAN discretized model, visualized by using TECPLOT Software, for a 1/4 sym metry Pu Be capsule. To define the decay history and resulting source spectrum, exothermic [alpha neutron ( ) ] reactions are modeled using ORIGEN ARP in the SCALE5 .1 package. For transport modeling purposes, the intermetallic Pu Be compound was treated as an intimate mixture of plutonium and beryllium, based on the manufactu et caps ule leakage was derived using transport computations, and an iterative estimation of plutonium age was performed Computational results for the leakage obtained using MCNP5 code, as shown in Figure 4 2 for neutrons and in Figure 4 3 for photons, are in ag specification of neutron yield and dose rate. In these figures the red lines correspond to the intrinsic leakage, without multiplication (nonu card) and the blue lines correspond to the total

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55 leakage, with multiplication (to tnu card). Figure 4 2A reflects the major effect on the multiplication due to fission neutrons (average energy 1.93353 MeV) on the low energy peak of the neutron spectra, while the peak corresponding to neutrons (average energy 4.833 MeV) is less influen ced by the multiplication. Regarding the photons, Figures 4 3A) and B) show a very small number of induced fission photons. We also combined computational results with experimental measurement data to fully validate our computational methods. We have succe ssfully achieved agreement between computational and experimental dat a for our Pu Be source leakage. In profiling the sources, we performed an in depth investigation of Florida Pu Be source, principally to account for total source strength and, in particular, to evaluate source anisotropy/materials effects. Note that t he actual activity of the source is not exactly 1 Ci ; rather, the activity refers to the Pu conten t (a 1 Ci source contains ~ 16 g of Pu). Pu Be sources are assumed to be integer increments of 1 C i sources; sources > 1 Ci are obtained by doubling or tripling the 1 Ci plutonium mass, respectively. 46 4.1 The Pu Be Source Capsule D escription This neutron source was modeled as a homogeneous source, uniformly distributed th roughout the inner capsule region, and treated, in all calculations described here, as an intimate intermetallic mixture of plutonium and beryllium, with a typical density of 4.35 g/cm 3 Based on s, the mass of Be was 7.86 g, and of Pu, 15.02 g. In establishing source geometry, we based our model on available source schematic data. Shipping documents provided by manufacturer in June 1971 give information about the container material (tantalum and s tainless steel), and the outside dimensions of the container (2.59 cm outside diameter x 3.68 cm height). In the shipping document are also given

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56 9 cm). In our model, the 1.58 cm diameter Pu Be region is jacketed in 0.25 cm thick stainless steel (outer material) and a 0.25 cm thick tantalum (highly dense inner capsule) metal (See Figure 4 1). 4.2 Estimation of the Neutron Emission Because both the MCNP5 and PENTRAN codes begin with source neutrons, exothermic ( ) reactions and s pontaneous fission (s.f.) reactions were determined using the ORIGEN ARP code in the SCALE5 .1 package from ORNL to define the energy spectrum and the decay of the source. W e used the specified masses of beryllium and plutonium (weapons grade, with an assumed isotopic composition: 0.005% 238 Pu, 93.54% 239 Pu, 6.00% 240 Pu, 0.44% 241 Pu, 0.015% 242 Pu) in ORIGEN ARP to provide the intrinsic source term, which we then used as input in an MCNP5 calculation for net leakage. Our result for the leakage, rendered in MCNP5, is 1.7343E+06 (0.01% relative statistical error) n/s, a value smaller than 1.93E+06 n/s, the value provided by manufacturer. In order to improve the agreement between the two values, the source must be corrected for age, corresponding to activity changes, notably due to 241 Am in growth in the early years immediately after Pu sepa ration and fabrication. Figure 4 4 presents the change of isotopic composition over the year s, starting with 1959, which we estimated that is the year of Pu separation. Our iterative procedure of Pu age estimation will be presented in next section. A mercium 241 is an alpha emitter (T =432 y) that grows from 241 Pu (T =14.35 y) as a result of beta decay (99.998%). An alternative mode of 241 Pu decay is by alpha decay (0.002%) to 237 U, which is a beta gamma ray emitter useful in detecting initially pure Pu. In growth of 241 Am leads to increases in ( ) interactions with light elements for tens of years following initial separation of the Pu mass (see Figure 4 5).

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57 4.3 Plutonium Age E stimation Knowledge of the source strength on the shipping date in 1971 (1.93E+06 neutrons/s), permits a basis for iterative estimate of plutonium age using the scheme s hown in Figure 4 6 First, the ( ) reactions and s .f. reactions were determined using the ORIGEN ARP code in the SCALE5 .1 package from ORNL to define the energy spect rum and the decay of the source, based on the specified masses of beryllium and plutonium to pr ovide the intrinsic so urce term; this assumes the masses of plutonium and beryllium provided by manufacturer are up of 241 Am and average weapons grade plutonium composition in the Pu Be source as given in Secti on 4.2. T hen we used the intrinsic source as input in an MCNP5 calculation for net leakage. If the result for the l eakage, rendered in MCNP5, is not 1.93E+06 n/s, the value provided by manufacturer we will change the year of Pu production. Now we have ano ther intrinsic source given by SCALE5.1 which will be used for the new transport calculation. According to the algorithm, the refinement will continue. If a standard deviation of 0.01E+06 is considered for neutron leakage measurements the estimated plut onium age for the source is 12.3 0.9 years. Following iterative solution, the result obtained is shown in Figure 4 7. With a bound on the age of the plutonium at 12.3 0.9 years, we can accurately compute the intrinsic source output, and then use this in both MCNP5 and PENTRAN ca lculations. The ( ) and (s.f.) neutron spectral contributions are shown in Fig ure 4 8 Of course, the major contribution to the neutron intrinsic source is attributed to ( ) interactions (> 99%). Fig ures 4 9 and 4 10 show t he estimation of the to tal intrinsic neutron and gamma ray source at snapshots in time (Pu separation in 1959, source manufacture in 1971, and 2005), as a function of energy. Both, emission of neutrons and emission of photons are increasing over the

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58 time due to accumulation of 241 Am which decay by emission [E = 5.485 MeV (84.5 %) and E emission [E = 13.9 keV (42%), E = 59.5 % (35.9 %), and E = 26.3 % (2.4%)]. In addition, we investigated the impact of uncertainty in Pu isotopes Since 241 Am is longer lived than 241 Pu, it builds to an equilibrium level, and since 241 times greater than 239 241 Pu fraction. Table 4 1 shows the effect on the source (sorted by 241 Pu content ), varying the 241 Pu concentration while holding constant the Pu mass and the even numbered plutonium isotopes. V ariation of the 241 Pu mass will yield a different rate of Pu Be source decay, while a variation in mass of the other Pu isotopes will result in a different initial emission of neutrons. As expected, 20 the ratio between the maximum and original yield increases directly with the weight fraction of 241 Pu. The WGPu composition, as given in Section 4.2, is based on an extended analysis of that shown in Table 4 1. Our assumptions were validated by calculations and the experiments described in Sections 4.4 and 4.5. Alternatively, one can al spectrum of the Pu Be source to evaluate the Pu isotopic fractions. 4.4 Calculation of the Effective Dose Another metric provided by manufacturer, which may be used to further validate our model, is the dose specified for the source. Shipping Pu Be source supplied by Mound Laboratories (June 1971) contained the measurement data: product between the fluence to dose factor DE and the fluence Therefore, we performed the

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59 calculation using neutron/photon response function data for phantom related dose from combined neutron data [A merican National Standards Institute (ANSI), International Commission on Radiological Protection, and National Council on Radiation Protection] and ANSI photon response data interpolated into the BUGLE 96 library 47 (Figure 4 11). Maximum neutron fluence, at a radial distance of 88.9 cm from the Pu Be source (vertical source position) over a 40 h period of time is given in Figure 4 12A for the corresponding 47 group BUGLE 96 neutron energy group bins, computed with the MCNP5 code (with 1 statistical errors) using the 1971 source basis from the SCALE5.1, ORIGEN ARP code. Summing the product of fluence to dose factors DE and group fluences energy bins, the maximum dose obtained from neutrons was 108.25 ( over 40 h at 99.9 cm from the source (where 1cSv=1 rem). Using the same method for photons, with the fluence given in Figure 4 12B, the photon dose obtained was 0.42 ( 35 inches from the source. Note the total dose of 108.67 ( 1) mrem compares well ( 10%) to the +36 yr old experimental data sheet supplied by Mound laboratories (100 mrem) with the 1 Ci source (no uncertainty was provided). 4.5 Benchmark Problem MCNP5 S imulations vs. Experimental R esults F or the experimental stu dy a standard benchmark apparatus was established for the response of 3 He gaseous proportional counters, using the Pu Be neutron source. Two types of moderators (polyethylene and paraffin) of differ ent thicknesses were used. Different t hicknesses of polye thylene were used spanning 5.08 8.89 cm ( in quarter inch intervals ), while the paraffin thicknes ses were spanning 3.81 11.43 cm. M easurements were performed over five trials with 3 min for each position. The 3 He detector used has a 2.54 cm (1 in.) diamete r, an act ive length of 20.32 cm (8 in.) and t he filled gas pressure was ~1 atm at STP conditions.

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60 Appropriate thermal cross sections poly.60t from thermal S( ) tables were used in MCNP5 for polyethylene to represent the thermal neutron scattering b y molecules and crystalli ne solids with energy < 4 eV. Since the thermal treatment for paraffin is not available in MCNP, a previously proposed approach 48 employing the polyethylene (poly.60t) treatment for paraffin gave consistent results. The MCNP5 simul ations of the neutron detector response are quite consistent with th e laboratory results using the 1 Ci Pu Be source. Figures 4 13 and 4 14 depict identical trends when comparing the experimental detector response and the MCNP5 simulation detector response using polyethylene as moderator In Figures 4 13 and 4 14 and from 4 17 to 4 22, polynomial fits are indicated on the plots only to guide the eye, so that the polynomial coefficients do not have an impact. Even though sometimes they are too small to be seen, the error bars for both experimental data and MCNP calculations are on the graphs. Model geometry is shown in Figure 4 4 16 for the bottom and Figure 4 top position of the c apsule where A) is showing the MCNP simulation (rendered by VISED), and B) the experimental design D we investigated the response of the detector for both positions. For the vertical position, excellent model results were achieved between computation and experiment, where the difference between experimental data and MCNP5 Monte Carlo results was within 2. 7 % for polyethylene and within 5.7 % for paraffin as shown in Figures 4 18 and 4 19 B oth number of counts in measured and modeled scenarios for two other source positions

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61 ( horizontal top closer and horizontal bottom closer he horizontal top closer case, experimental and computational results agree within 2.2 % for polyethylene and within 6 % for paraffin, as can be seen in Figures 4 20 and 4 21 For the case of the horizontal bottom closer source position, experimental and c omputational results agree within 4.7 % for polyethylene, and within 7.6 % for paraf fin (see Figures 4 22 and 4 23 ). 4.6 Comparing the Leakage Spectra U sing Monte Carlo and S N Transport Methods The PENTRAN deterministic calculations, based on the BUGLE 96 cross section library, were performed and compared to MCNP5 Monte Carlo computations, using ENDF /B VI for the Pu coarse meshes, in a 2 x 2 x 10 arrangement, with boun daries along x and y axis at 0.0 cm, 1.29 cm (corresponding to the margin of the capsule), and 1.44 cm. Vacuum boundary conditions are prescribed at x = 1.44 cm, y = 1.44 cm, z = 0.0 cm and z = 4.58 cm, while reflective boundary conditions are prescribed at x = 0.0 cm and y = 0.0 cm. The 6,452 3 D fine mesh cells, with different density on different course meshes, permits a good geometrical approximation of the cylinders that form the Pu Be capsule. Fig ures 4 24 A and B [A) as a function of energy and B) a s a function of energy group] show that, overall, very good agreement was obtained for neutron leakage values computed via the two independent methods for the capsule (no multiplication) running MCNP5 (using a We obtained for t h e number of neutrons leaking out computed using MCNP5 (based on an F1 current tally) 1.8528 x 10 6 (0.01%) n/s, and 1.8527 x 10 6 n/s computed via PENTRAN using BUGLE 96 cross section library, S 24 angular quadrature, and P 3 scattering anisotropy. To find th e optimum S N order, we performed a convergence study, increasing the number of directions for the angular quadrature from 288 (S 16 ) to 624 (S 24 ) considering P 3 scattering

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62 anisotropy. Maximum relative difference between S 16 solution and S 24 per neutron ener gy group was 0.3 % and 1 % per photon energy group. We reached a relative difference between S 20 and S 24 of less than 0.04 % per energy group for neutrons and 0.2 % per energy group for photons. Using S 24 angular quadrature we compared P 1 P 3, and P 5 order of anisotropy; we observed that maximum relative difference per energy group, between P 3 and P 1 simulations is about 3 % for neutrons and about 5 % for photons. Between P 3 and P 5 the relative difference per energy group is less than 0.2 % for both, neutr ons and photons. Based on our study we decided to continue our computational work for this problem by running S 24 angular quadrature, P 3 scattering anisotropy. For the Pu Be capsule, we did note some differences in the MCNP5 and PENTRAN results using BUGLE 96 corresponding to the last 14 BUGLE 96 neutron energy groups (neutron energies <7.1 keV) as shown in Figure 4 25, A) as a function of energy or in B) as a function of energy group. Note the disagreement shown may be attributed to a combination of poor s tatistics for these energies in the MCNP5 Monte Carlo simulation (see error bars), and in part due to the broad group cross sections in selected energy groups. It is notable that these groups constitute only 0.1% of the total leakage. For the total neutro n leakage t he same trend can be seen i n Figure 4 26. T otal leakage with multiplication performed using MCNP5 (totnu card) is (1.9285 0.0001 ) x 10 06 n/s and the total leakage computed based on the procedure highlighted in Section 3.3 for the PENTRAN S N c alculation is 1.9198 x 10 06 n/s, with less than 0.5 % relative difference between the two values. Good agreement was obtained also for t he value of k eff : computed using MCNP5 is 0.03576 0.00001 and using PE NTRAN is 0.03567 Regarding th e intrinsic photo n leakage, Figure 4 27 [A) as a function of energy and B) as a function of energy group] shows the PENTRAN BUGLE 96 library results vs. MCNP5 output.

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63 U sing MCNP5 (based on an F1 current tally), t he computed number of photons leaking out is 7.7001 x 10 0 5 ( 0.01%) photons/s, and computed via PENTRAN using BUGLE 96 cross section library, S 24 angular quadrature, and P 3 scattering anisotropy is 6.2622 x 10 0 5 photons /s Relative difference between the two calculations is ~ 18.67 %, with major differences for ene rgy lower than 0.6 MeV. L eakage ratio MCNP/PENTRAN BUGLE 96 in Fig ure 4 28 [A) as a function of energy and B) as a function of energy group] shows that the PENTRAN BUGLE 96 result is lower than that computed from Monte Carlo, although the spectral trends a re quite consistent. V ery broad energy group structure of the BUGLE 96 photon cross section libr ary contributed to the observed differences. Our new methodology, developed in this chapter, is suitable for complete characterization of a Pu Be neutron sourc e based on 3 D radiation transport computations, using Monte Carlo and/or deterministic computational methods. These studies support our work toward the design of a parcel screening system capable of SNM characterization, where the source magnitude and spe ctrum must be accurately known and verified. In the following chapter, the computational procedure demonstrated here for characterization of Pu Be neutron source will be confidently applied also for the SNM assessments. Knowledge of the neutron leakage fr om the Pu Be source was essential for allowing us to determine and verify the design of a surrogate shielded source, which will be treated separately in Chapter 6.

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64 Table 4 1. Sensitivity of the Pu Be s ource with the variation of the isotopic compositio n Weight fraction (%) Years to reach (1.930.01) E+06 Years to reach max yield (max/mi n) Yield 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 0.005 0.005 0.005 0.005 93.58 93.54 93.48 93.28 6.000 6.00 0 6 000 6.000 0.4 00 0.4 40 0.5 00 0.7 00 0.015 0.015 0.015 0.015 14.11. 1 12.3 0.9 10.40.7 6.90. 5 69 68 69 70 1.20 1.22 1.2 5 1.36 Figure 4 1 The PENTRAN model of a t ypical construction for Pu Be sources

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65 A B Figure 4 2. Neutron leak age profile for 1 Ci Pu Be source, computed using MCNP5 (1 ). A) as a function of energy, B) as a function of energy group.

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66 A B Figure 4 3 P hoton leakage profile for 1 Ci Pu Be source computed using MCNP5 ( 1 ). A) as a function of energy, B) as a function of energy group.

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67 Figure 4 4 Modification of the isotopic mass composition Pu Be source over time. Figure 4 5. Increase of the ( Be source over time.

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68 Figure 4 6. The Pu age estimation algorithm. Figure 4 7. I ncrease in the int Pu Be neutron source over time due to 241 Am. MCNP5 ( totnu ) Update Iterate to yield 1.93E+06 n/s Estimate Pu age SCALE5 (intrinsic source)

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69 Figure 4 8. The ORIGEN ARP rendered intrinsic s.f. vs. ( Pu Be source as a function of energy for year 1971. Figure 4 9. Intrinsic Pu Be source, using ORIGEN ARP as a function of energy, at snapshots in time.

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70 Figure 4 10 Intr Pu Be source, using ORIGEN ARP as a function of energy, at snapshots in time. A Figure 4 11. A) Neutron response function data for phantom related dose B) photon response function data for phantom related dose.

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71 B Figure 4 11. Continued. A Figure 4 12 The MCNP5 computed over 40h, at Pu Be source(1 ) A) neutron energy fluence B) p hoton energy fluence.

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72 B Figure 4 12 Continued. Figure 4 13. Experimental 3 He neutr using polyethylene as moderator.

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73 Figure 4 14. The MCNP5 simulated 3 He neutr ) using polyethylene as moderator. A B Figure 4 15 View of the capsule in the vertical position A) MCNP5 benchmark simulation, B) experimental design

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74 A B Figure 4 16 View of the capsule in the horizontal bottom closer position A) MCNP5 benchmark sim ulation B) experimental design. A B Figure 4 17 View of the capsule in the horizontal top closer position A) MCNP5 benchmark simulation, B) experimental design.

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75 Figure 4 18 Experiment vs. MCNP5 (1 ): t he capsule in the vertical position; polyethylene moderator. Figure 4 19 Experiment vs. MCNP5 (1 ): t he capsule in the vertical position; paraffin moderator.

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76 Figure 4 20 Experiment vs. MCNP5 (1 ): t he capsule in horizontal top closer posit ion; polyethylene moderator. Figure 4 21 Experiment vs. MCNP5 (1 ): t he capsule in horizontal top closer position; paraffin moderator.

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77 Figure 4 22 Experiment vs. MCNP5 (1 ): t he capsule in horizontal bottom closer position; polyethylene moderator Figure 4 23 Experiment vs. MCNP5 (1 ): t he capsule in horizontal bottom closer position; paraffin moderator.

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78 A B Figure 4 24 PENTRAN BUGLE 96 vs. MCNP5 (1 ): Neutron leakage profile (shielding calcula tion, no multiplication), 1 Ci Pu Be neutron s ource capsule A) as a function of energy B) as a function of energy group.

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79 A B Figure 4 25 The MCNP5 / PENTRAN BUGLE 96 (1 ): Neutron leakage (shielding calculation, no multiplication), 1 Ci Pu Be neutron source capsule. A) as a function of neutron en ergy, B) as a function of energy group.

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80 A B Figure 4 26 PENTRAN BUGLE 96 v ersus MCNP5 (1 ): Neutron leakage profile (w ith multiplication), 1 Ci Pu Be neutron source capsule A) as a function of neutron energy B) as a function of energy group

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81 A B Fi gure 4 27 PENTRAN BUGLE 96 v ersus MCNP5 (1 ): Photo n leakage 1 Ci Pu Be neutron source capsule A) as a function of photon energy, B) as a function of energy group.

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82 A B Figure 4 28 The MCNP5 / PENTRAN BUGLE 96 (1 ) Photon leakage ratio (shielding c a lculation, no multiplication), 1 Ci Pu Be capsule A) as a function of energy, B) as a function of energy group.

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83 CHAPTER 5 THE SNM NEUTRON SOUR CE ASSESSMENTS In this chapter, the research leveraging 3 D radiation transport models to ultimately yield a c omplete mosaic of the radiation spectrum from a fissile source are presented In the previous chapters we demonstrated that the BUGLE 96 multigroup library is indeed applicable to our general deterministic transport neutron detection scenarios. Here, we ef fectively characterize and construct SNM neutron source terms based on the procedure presented in Section 3.3 and successfully applied to Pu Be neutron source assessment. To provide assessments on detection, reliable numerical sources for various isotopic components of plutonium (metal and oxide) and uranium (metal and oxide) of various enrichments in 235 U are required. Therefore, isotopic compositions were computed for different reactor fuels and varying times using the SCALE5.1 package to yield the disc harge isotopic content of plutonium metal and oxide, and final enrichments with minor isotopes were established for uranium metal and uranium oxide. Plutonium is assumed to have been discharged from a power reactor following burnup with chemical separatio n and purification into spherical 4 kg metal or oxide masses, and uranium is assumed to be formed as metal or oxide spheres of varying mass (considering 10 kg, 30 kg, and 50 kg). We p erform ed criticality computations on materials providing an assessme nt of leakage multiplication and total neutron count rate in candidate geometries This task was completed line multiplication sources. For this work, it is unilaterally assumed that all source materia ls are subcritical (and verified by transport computation) and are of homogeneous composition and density. It is readily observed that due to changing source spatial configurations, with subsequent multiplication of the intrinsic source

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84 and leakage effect s, correct absolute source signatures can only be yielded from unique radiation transport computations accomplished for each relative change in the source configuration. 5.1 Plutonium Sources In order to c haracterize and quantify radiation source terms fo r plutonium metal and oxide materials, varying in isotopic quantities from Weapons Grade Pu (~6% 240 Pu ) to Reactor Grade Pu (~25% 240 Pu) we used a set of nuclear data modules that contained the necessary isotope and decay data to correctly quantify the is otopic constituents for various burnups of plutonium discharged at various intervals from Pressurized Water Reactors (PWRs) and Canadian Deuterium Uranium (CANDU) reactors. The SCALE5.1 code was used to define decay sources for plutonium at various points of discharge for both PWRs (17x17 standard UO 2 fuel assemblies) with irradiation at 35 MW/MTU between 5,500 Mega Watt Days/Metric Ton heavy metal (MWD/MT) and 33,000 MWD/MT burnup, and for CANDU (CANDU 37 fuel) also with irradiation at 35 MW/MTU between 8 88 MWD/MT and 7,928 MWD/MT burnup. Based on the fuel burnups, we assumed that Pu (with the various 240 Pu qualities at discharge) was extracted at various burnups following a 10 year cooling period (an assumed average cooling period for a complete closed fuel cycle), and was formed as PuO 2 (10.59 g/cm 3 density) and Pu metal (19.86 g/cm 3 density). Further consideration could be made for Pu alloyed in a phase metal (15.92 g/cm 3 density ) assumed in an unspecified alloy to achieve room temperature phase stability. Spectral source (n, ) terms were computed using SCALE5. 1 to enable fixed Pu sources to be evaluated for multiplication as 4 kg spherical assemblies. Using the specified mass and density we determined the radii of the spheres; plutonium metal spheres had a radius of 3.636 cm, while the plutonium oxide spheres h ad a radius of 4.484 cm. One part per million of oxygen

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85 was incorporated into the plutonium metal to account for impurities, which yields a minor effect on light element neutron production (higher levels of oxygen will impact this). In the course of these investigations, Pu quality (by assessment of 240 Pu content) varied from 9.98% to 24.23% 240 Pu from the burned down PWR fuel, and 4.98% to 27.7% for the burned down CANDU fuel (considering minimum to maximum fuel burnup in a nominal power fuel channel). Al l source radiation data has been adapted to the BUGLE 96 cross section library group structure since this is an effective shielding transport library. 5.1.1 The PWR Generated Plutonium Burnup was assessed using the SCALE5.1 package for a PWR fuel (with 17 x 17 bundles, 235 U enrichment 2.8 w% and 0.013 w% 236 U) for the burnups of: 5498.5, 11000.5, 16499, 22001, 27499.5, and 33001.5 MWD/MT, spanning a typical operational cycle; the irradiation times were 157.1, 314.3, 471.4, 628.6, 785.7, and 942.9 days for t he PWR. Details of the variation in plutonium discharge isotopics are presented Figure 5 1, depicting weight percent of each isotope versus burnup in MWD/MTU, based on data collected in Table 5 1. Isotopic weight percent and concentrations of the differe nt isotopes of plutonium considering fabrication into metal and oxide ( 238 Pu, 239 Pu, 240 Pu, 241 Pu, and 242 Pu) were determined based on SCALE5.1/ORIGEN ARP burnup calculations. With a density of the phase of plutonium equal to 19.86 g/cm 3 and mass and ge ometry set to a standard Pu source defined as a 4 kg spherical ball, the mass of each isotope in the sphere was calculated based on separated discharge Pu isotopic concentrations (data presented in Table 5 2). Similar procedures and calculations were car ried out for plutonium oxide spheres with the same standard configuration, except that a nominal density of 10.59 g/ cm 3 was used (92.5% of PuO 2 theoretical density of 11.46 g/cm 3 ), and the appropriate oxygen mass was accounted for (see data in Table 5 3).

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86 Isotopic information was entered into ORIGEN ARP (SCALE5.1 package) to determine the intrinsic neutron and gamma energy spectrum both initially and after a realistic aging period (up to 10 years) for each 4 kg mass. A 67 group BUGLE 96 energy bin struct ure (see Chapter 2, Section 2.4 for details) was used by SCALE5.1 to collect these spectra information. Figures 5 2 (metal) and 5 3 (oxide) show the intrinsic source spectra for neutrons and photons emitted per second after 10 years. For metals, most of the intrinsic neutron source (over 99.99%) comes from spontaneous fission (s.f.) in even numbered isotopes, and 240 Pu can be attributed the majority of the s.f. reactions, with the remainder dominated by 242 Pu, and 238 Pu. Intrinsic neutron source increases with burnup irradiation of the fuel that produced the plutonium; this trend is also true for the intrinsic gamma source spectrum. As with metal, the intrinsic neutron source of PuO 2 increases with burnup irradiation of the fuel that produced the plutoniu m. This trend is also true for the intrinsic gamma source spectrum; the gamma spectrum is close to that of the metal, although it tends to be slightly softer. In growth of 241 Am can lead to increases in ( ) interactions with light elements for tens of y ears following initial separation of the Pu mass, as we observed in Chapter 4, in the discussions Be neutron source. The Pu metal intrinsic spectrum as a function of energy group is shown in Figure 5 4. Figu re 5 5 shows the two components of the intrinsic source for a PuO 2 corresponding to s.f. and ( ) reactions. For oxides, the intrinsic neutron source term is often about twice that of Pu metal (a rough rule of thumb; it can be more or less depending upon specific SNM parameters), since the presence of oxygen results in a significant light element ( ) component (about twice the s.f. neutrons), dominated by these reactions attributed to 239 Pu, 238 Pu, 240 Pu, and 241 Am in aged

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87 samples. Comparison between metal and oxide spectra from the same quantity of material (4 kg) is presented in Figure 5 6. Var ious total source strengths for the 4 kg metal and oxide spheres as a function of PWR burnup (at discharge with purification) are shown in Figure 5 7. Was determined the neutron multiplication eigenvalue, k eff by using the isotopic compositions of each c ase. Criticality simulations were performed using the MCNP5 Monte Carlo code to determine the multiplication factor. Several of the cases were also run using PENTRAN with BUGLE 96 library. The k eff data and trends versus burnup for PWR fuel are provided in Figure 5 8. Note that shorter irradiation times lead to higher relative 239 Pu concentrations in the spheres, and larger k eff values (which implicitly require significantly more reprocessing operations to recover the Pu from a larger number of fuel rods, etc). Also, note that oxide sphere eigenvalues were ~35% lower than for the metal assemblies, due to less fissile content. Tables 5 4 and 5 5 contain the values for the intrinsic source strength and the k eff for Pu metal, and PuO 2, respectively. 5.1.2 T he CANDU Generated Plutonium Fuel burnup was simulated with the SCALE5.1 package for CANDU 37 reactor fuel (with 37 pins, natural UO 2 ) for the burnups of 888, 2643, 4404 and 7928 MWD/MT spanning a typical operational cycle; CANDU power reactor irradiation times were 25.3, 75.5, 125.8, and 226.5 days. We considered the weight percents of different isotopes of plutonium metal: 238 Pu, 239 Pu, 240 Pu, 241 Pu, and 242 Pu (note 243 Pu existed in very trace amounts, and was neglected). Again, a density of the alpha phase of plutonium equal to 19.86 g/cm 3 was used for standard Pu source defined as a 4 kg spherical ball, and the mass of each isotope was calculated from the Pu isotopic concentrations. As in the PWR cases, one part per million of oxygen was incorporate d into the plutonium metal to account for impurities. Similar procedures and calculations were carried out for plutonium oxide spheres as with the PWR case, 10.59 g/cm 3

PAGE 88

88 was used (92.5% of PuO 2 theoretical density 11.46 g/cm 3 ), and the appropriate oxygen m ass was incorporated into the concentration of the total mass (Data collected in Tables 5 6, 5 7, and 5 8). Figure 5 9 is presenting a plot of CANDU plutonium isotopics as a function of burnup. Compared to the isotopic values for the PWR, higher overall values of 239 Pu content in the lower burnup CANDU fuel resulted, as expected. In addition, isotopic information was entered as for the PWR cases into ORIGEN ARP to determine the intrinsic neutron and gamma energy spectrum both initially and after the 10 y ear aging period. A 47 group BUGLE 96 energy bin structure was used in SCALE5.1 to collect these spectra information. In Figure 5 10 (metal) and Figure 5 11 (oxide) the intrinsic source spectra for neutrons and photons after 10 years are recorded as a fun ction of energy; the characteristics are similar to PWR generated Plutonium. Using isotopic composition, the neutron multiplication eigenvalue ( k eff ) was determined and a criticality simulation was performed using the MCNP5 Monte Carlo code. Several cases were also investigated using PENTRAN with BUGLE 96 library. Due to the higher overall content of fissile isotopes, principally 239 Pu, the resulting k eff values for the CANDU fuel were higher compared to the PWR rendered plutonium, also as expected. This is shown in Figure 5 12. As with the PWR fuel, note that oxide sphere eigenvalues were ~35% lower than for the metal assemblies, consistent with the Pu concentration. Similar to the trends in PWR fuel data for the plutonium metal and oxide, the longer the irradiation time, the higher the 240 Pu content, leading to higher relative source strengths with more intrinsic neutrons emitted due to spontaneous fission reactions. As expected, the spheres with plutonium derived from the longest irradiation times have higher neutron and gamma

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89 emission rates. This is evident from inspection of Figure 5 13. Tables 5 9 and 5 10 contain the value for the intrinsic source strength and the neutron multiplication eigenvalue, k eff for Pu metal and PuO 2 5.2 Enriched Uranium F uel For uranium, enrichments by weight percent in 235 U considered included: 20%, 35%, 50%, 75%, 90%, and 94%. Isotopes that were tracked and considered were 234 U, 235 U, 236 U, and 238 U. As the concentration of 235 U varied, the concentration of 234 U and 23 6 U were scaled with an assumed linear ratio based on representative samples of reactor fuel mass spectrometry assays (Equation 5 1): ; (5 1) Note that inclusion of 236 U assumes that reprocessed uranium hexaf luoride was used as feed material in the enrichment plant flowsheet generating the HEU, which is a reasonable assumption for most enrichment cascades in operation. The 238 U concentration is taken in all cases to be the remainder of the percentages (tare v alue). For uranium metal, one part per million of oxygen was included. Same procedures were performed for the uranium oxide, except with the addition of oxygen. For the uranium studies, in addition to varying the fixed enrichments, three different sets of masses were also considered for the uranium metal and oxide spheres: 10, 30, and 50 kg, spanning the criticality space. For the uranium metal and oxide, the densities used were 19.1 and 10.07 (95% of the theoretical density of 10.6 g/cm 3 ), respectively. The 10, 30, and 50 kg uranium metal spheres have the radii of 5.00, 7.21, and 8.55 cm, while for the uranium oxide spheres the radii were 6.20, 8.93, and 10.58 cm, respectively. Isotopic concentrations for the uranium metal and oxides with differing enri chments and masses (data collected in Tables 5

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90 11 to 5 17) were used in ORIGEN ARP (from SCALE5.1) to assess the initial and 10 year aged neutron and gamma energy spectra. Figures 5 14 to 5 19 show the intrinsic sources trend for the three masses of Uran ium (both metal and oxide materials) plotted as a function of energy. Most of the intrinsic neutron source of U metal comes from spontaneous fission (s.f.) in even numbered isotopes, well dominated by 238 U for most of the reactions. Therefore, the source drops significantly as a function of increasing enrichment, and is lowest for 94 w% 235 U, yielding only 7.2 n/s for a 10 kg mass. However, the intrinsic gamma source increases substantially with increasing enrichment. Intrinsic neutron source term of U O 2 is typically an order of magnitude larger than that of U metal, since the presence of oxygen results in a significant light element ( ) component, dominated by these reactions attributed to primarily 234 U (some to 235 U). Unlike uranium metal, the intrinsic neutron source increases with enrichment; consider that 94 w% 235 U oxide yields 289 n/s for a 10 kg mass. This trend is also true for the intrinsic gamma source spectrum; the intrinsic gamma spectrum is close to that of the metal, although it tends to be slightly softer. As indicated in Figure 5 20A, as metal enrichments increase, the total neutron intrinsic source yield drops signif icantly; this is expected since 90% of the intrinsic spontaneous fission source is attributable to the 238 U isotope. We observed that the photon source strengths increase with enrichment, with the largest contributions of photons with energies below 0.4 Me V; this trend is depicted in Figure 5 20B for U metal masses. Total neutron and gamma sources vs. enrichment for UO 2 are given in Figures 5 21. Figures 5 22 and 5 23 depict uranium metal and oxide criticality eigenvalues for comparison. Using MNCP5, the i nitial uranium metal and oxide concentrations were modeled to 239 Pu or 235 U

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91 concentrations in the initial spheres yielded larger k eff values. Since the mass/size is also being v aried, the k eff value will increase with increasing mass. For the highest enrichment (~94%) and largest sphere (50 kg) uranium metal, the k eff value is 0.99561, which is the largest value obtained among these calculations. With added reflection from surr ounding materials in a shipping scenario, the 50 kg case is likely not credible for a parcel screening system scenario 18 through 5 23 highlight the intrinsi c source strength and the neutron multiplication eigenvalue, k eff of Uranium SNM sources. 5.3 Monte Carlo (MCNP5) Versus S N (PENTRAN/BUGLE 96) L eakage In Section 3 3, the methodology used for complete characterization of SNM sources was highlighted. Here we show an example; the leakage from a 4 kg WGPu metal ball (CANDU fuel) computed using Monte Carlo methods ( MCNP5 code ) with ENDF/B VI cross sections, and using 3 D S N methods ( PENTRAN code) with the B UGLE 96 (see Section 2.4 for details) The PENTRAN mo del of the ball, for a 1/8 symmetry sphere contains 8 coarse meshes, in a 2 x 2 x 2 arrangement, with boundaries along x y and z axis at 0.0 cm, 1.9 cm, and 3.8 cm. Vacuum boundary conditions are prescribed at x = 3.8 cm, y = 3.8 cm, and z = 3.8 cm, w hile reflective boundary conditions are prescribed at x = 0.0 cm, y = 0.0 cm, z = 0.0 cm. For a good geometrical approximation of the sphere, 16,000 3 D fine meshes (1 mm x 1mm x 1mm grid) were used to build the model shown in Figure 5 24, along with the f lux solution for the 19 th energy group, which is illustrative of the solution obtained. Comparison between the leakage without multiplication, computed via Monte Carlo (using continuous energy, equivalent group energy bin tallies nonu card ) and d etermini stic S N (BUGLE 96 library) is given in Fig ure 5 25; the values comp are very well U sing MCNP5 (based on an F1 current tally), t he number of neutrons leaking out was computed and the value

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92 obtained, 1.6106 x 10 0 5 (0.01%) n/s, is in a good agreement with 1. 6083 x 10 0 5 n/s parallel computed via PENTRAN using BUGLE 96 cross section library. We used for our deterministic simulations S 24 angular quadrature and P 3 scattering anisotropy, following the convergence study performed for Pu Be in Section 4.6. W e did n ote some differences in the MCNP5 and PENTRAN results using BUGLE 96 corresponding to the last 14 BUGLE 96 neutron energy groups (neutron energies <7.1 keV) as shown in Figure 5 26A as a function of energy or in Figure 5 26B as a function of energy group. Note the disagreement shown may be attributed to a combination of poor statistics for these energies in the MCNP5 Monte Carlo simulation (see error bars), and in part due to the broad group cross sections in selected energy groups. It is notable that these groups constitute only 0.1% of the total leakage. Regarding the intrinsic photon leakage Figures 5 27A) as a function of energy and 5 27B) as a function of energy group, show the PENTRAN BUGLE 96 library results vs. MCNP5 output. Based on MCNP5 (using an F1 current tally), the number of photons leaking out was computed and the value obtained was 4.6635 x 10 8 (0.01%) photons/s. Via PENTRAN, using BUGLE 96 library, S 24 angular quadrature, and P 3 scattering anisotropy, the computed leakage was 4.8351 x 10 8 p hotons/s; the relative difference between the two calculations is ~ 3.55 %, mainly due to the very broad energy group structure of the BUGLE 96 photon cross section libr ary. L eakage ratio MCNP / PENTRAN BUGLE 96 from Figure 5 28A, as a function of energy and 5 28B as a function of energy group, show that the PENTRAN BUGLE 96 result is lower than that computed from Monte Carlo, although the spectral trends are quite consistent. The very broad group structure of the BUGLE 96 photon cross section library for some energy

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93 groups likely contributed to the differences, along with a potential for ray effects in the discrete ordinates gamma calculation. In combination, these effects can impact the accuracy of the calculations. In Figures 5 29 (neutron) and 5 30 (photon) are depicted the results showing the leakage profile, intrinsic (without multiplication) and total (with multiplication), based on MCNP5 calculation. In MCNP5 we used the nonu card for the intrinsic leakage calculation; this card turns off fission neutron production. For total leakage, considering intrinsic and multiplication terms, we used the totnu card option. For deterministic computation of the induced radiation leakage source component (see Equation 3 16), we need the value of k eff For mult iplication factor, the result obtained using PENTRAN BUGLE 96 library was 0.75316, in a very good agreement with Monte Carlo result 0.75344 0.00064. Total leakage with multiplication performed using MCNP5 (totnu card) is (5.9583 0.0001) x 10 5 n/s, and the total leakage computed based on the procedure highlighted in Section 3.3 for the PENTRAN S N calculation is 6.4181 x 10 5 n/s, with ~7.16 % relative difference between the two values, due mainly to the approximation of the procedure. Cmparison between th e results obtained using the two independent computational methods is depicted in Figure 5 31A), as a function of energy and B) as a function of energy group. Spectral characterization of the SNM neutron sources described in this chapter provides extremel y useful information for other computational application implying detection of SNM materials. Now, the differences in the signature/detection potential between SNM oxides and metals can be evaluated, and a reverse process can be developed to enable the spe ctroscopy evaluation.

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94 As a practical example, in Chapter 7, the analysis of the spectral detection using ideal filter materials is based on the input (total leakage spectrum) information obtained here, and presents the optimally detected spectral differen ces between SNM materials (Plutonium and Uranium), metal and oxide, via detection in 3 He detector. We have also used the SNM sources, characterized in this chapter, for evaluation of a number of candidate filtering materials, finalizing our design of a neu tron detector array to resolve the input spectra sources using 3 He detectors by replacing the ideal filters with real materials.

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95 Table 5 1. Isotopic Values of PWR 3 ) MWD/MT Pu wt ( % ) 238 P u 239 P u 240 P u 241 P u 242 P u 5499 0.069 87.075 9.980 2.736 0.140 11001 0.214 77.299 15.218 6.539 0.730 16499 0.432 69.640 18.743 9.466 1.719 22001 0.721 63.396 21.234 11.657 2.991 27500 1.073 58.328 23.000 13.149 4.448 33002 1.478 54.413 24.224 13. 896 5.988 Table 5 2. Mass Values of PWR 3 ) MWD/MT Pu mass (g) O (Nat) mass (g) 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 5499 2.754 3483.009 399.215 109.437 5.583 0.004 11001 8.558 3091.962 608.720 261.571 29.182 0.004 16499 17.286 2785.601 749.711 378.644 68.739 0.004 22001 28.845 2535.856 849.340 466.275 119.647 0.004 27500 42.935 2333.115 920.008 525.973 177.916 0.004 33002 59.129 2176.524 968.956 555.820 239.498 0.004 A mass 238.050 239.052 240.05 4 241. 057 242.059 16.00 2 Table 5 3. Mass Values of PWR Generated PuO 2 3 ) MWD/MT Pu mass (g) O (Nat) mass (g) 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 5499 2.429 3072.013 352.108 96.523 4.924 472.003 11001 7.549 2727.304 536.929 230.722 25.740 471.757 16499 15.248 2457.220 661.331 334.007 60.636 471.558 22001 25.446 2237.031 749.253 411.329 105.548 471.392 27500 37.877 2058.268 811.629 464.012 156.957 471.258 33002 52.165 1920.188 854.839 490.359 211.292 471.157 A mass 238.050 239.052 240.054 241.057 242.059 16.00 2 Table 5 4. Molec ular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of PWR 3 ) MWD/MT Pu metal Mol Wt Source (10 yr aged) k eff 1 n/s 5499 239.210 4.33E+05 5.16E+12 0.74148 0.00062 11001 239.355 7.06E+05 1.16E+13 0.72865 0.00065 16499 239.476 9.43E+05 1.68E+13 0.71708 0.00056 22001 239.579 1.16E+06 2.11E+13 0.70690 0.00060 27500 239.666 1.37E+06 2.44E+13 0.69979 0.00066 33002 239.734 1.57E+06 2.68E+13 0.69223 0.00058

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96 Table 5 5. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenv alue (k eff ) of PWR Generated PuO 2 3 ) MWD/MT PuO 2 Mol Wt Source (10 yr aged) k eff 1 n/s 5499 271.214 6.92E+05 4.55E+12 0.48601 0.00043 11001 271.358 1.16E+06 1.02E+13 0.47640 0.00046 16499 271.479 1.59E+06 1.48E+13 0.46780 0.00042 22001 271.582 2. 00E+06 1.86E+13 0.46161 0.00040 27500 271.669 2.41E+06 2.15E+13 0.45641 0.00042 33002 271.737 2.80E+06 2.36E+13 0.45069 0.00043 Table 5 6. Isotopic Values of CANDU 3 ) MWD/MT Pu wt ( %) 238 Pu 239 Pu 240 Pu 241 Pu 2 42 Pu 888 0.003 94.745 4.983 0.263 0.006 2643 0.020 85.313 12.846 1.688 0.133 4404 0.043 77.285 18.906 3.295 0.471 7928 0.104 64.566 27.689 5.891 1.749 Table 5 7. Mass Values of CANDU 3 ) MWD/MT Pu m ass (g) O (Nat) mass (g) 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 888 0.128 3789.788 199.306 10.525 0.254 0.004 2643 0.787 3412.511 513.838 67.531 5.332 0.004 4404 1.718 3091.406 756.221 131.793 18.857 0.004 7928 4.167 2582.654 1107.577 235.627 69.957 0.004 A mas 238.050 239.052 240.05 4 241.05 7 242.05 9 16.00 2 Table 5 8. Mass Values of CANDU Generated PuO 2 3 ) MWD/MT Pu mass (g) O (Nat) mass (g) 238 Pu 239 Pu 240 Pu 241 Pu 242 Pu 888 0.113 3342.422 175.779 9.282 0.224 472.180 2643 0.694 3009.845 453.207 59.563 4.703 471.988 4404 1.515 2726.768 667.023 116.248 16.633 47 1.813 7928 3.676 2278.223 977.021 207.852 61.711 471.517 A mas 238.050 239.052 240.05 4 241.05 7 242.05 9 16.00 2 Table 5 9. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of CANDU metal 4 kg sphere 3 ) MWD/MT Pu metal Mol Wt Source (10 yr aged) k eff 1 n/s 888 239.107 2.085E+05 1.0138E+12 0.75344 0.00064 2643 239.218 5.467E+05 3.4965E+12 0.73733 0.00062 4404 239.321 8.252E+05 6.2214E+12 0.72400 0.00061 7928 239.498 1.28 6E+06 1.0657E+13 0.70196 0.00054

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97 Table 5 10. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of CANDU Generated PuO 2 3 ) MWD/MT PuO 2 Mol Wt Source (10 yr aged) k eff 1 n/s 8 88 271.111 3.45E+05 8.94E+11 0.49398 0.00049 2643 271.222 7.43E+05 3.08E+12 0.48232 0.00044 4404 271.324 1.08E+06 5.49E+12 0.47293 0.00044 7928 271.501 1.64E+06 9.40E+12 0.45801 0.00041 Table 5 11. Isotopic Values of Enriched Uranium spheres U wt (%) 234 U 235 U 236 U 238 U 0.217 20.0000 0.083 79.700 0.379 35.0000 0.145 64.475 0.542 50.0000 0.208 49.25 1 0.813 75.0000 0.311 23.876 0.975 90.0000 0.374 8.651 1.019 94.0000 0.390 4.591 Table 5 12. Mass Values of Enriched Uranium metal 10 kg spher 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 21.672 2000.000 8.304 7970.024 0.010 35.0000 37.926 3500.000 14.532 6447.542 0.010 50.0000 54.180 5000.000 20.761 4925.059 0.010 75.0000 81.270 7500.000 31.141 2387.589 0.010 90.0000 97.524 9000.000 37.369 865.107 0.010 94.0000 101.858 9400.000 39.030 459.112 0.010 A mass 234.041 235.044 236.046 238.051 16.00 2 Table 5 13. Mass Values of Enriched UO 2 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 19.098 1762.448 7.318 7023.376 1187.761 35.0000 33.414 3083.575 12.803 5680.422 1189.786 50.0000 47.723 4404.090 18.286 4338.081 1191.819 75.0000 71.556 6603.583 27.419 2102.219 1195.223 90.0 000 85.848 7922.453 32.895 761.530 1197.274 94.0000 89.658 8274.047 34.355 404.118 1197.823 A mass 234.041 235.044 236.046 238.051 16.00 2

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98 Table 5 14. Mass Values of Enriched Uranium metal 30 kg 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 65.016 6000.000 24.913 23910.071 0.030 35.0000 113.778 10500.000 43.597 19342.625 0.030 50.0000 162.540 15000.000 62.282 14775.178 0.030 75.0000 2 43.810 22500.000 93.422 7162.768 0.030 90.0000 292.572 27000.000 112.107 2595.321 0.030 94.0000 305.575 28200.000 117.089 1377.336 0.030 A mass 234.041 235.044 236.046 238.051 16.00 2 Table 5 15. Mass Values of Enriched UO 2 0.07 g/cm 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 57.294 5287.344 21.954 21070.127 3563.282 35.0000 100.241 9250.724 38.410 17041.266 3569.359 50.0000 143.168 13212.271 54.859 13014.244 3575.458 75.0000 214. 669 19810.749 82.256 6306.657 3585.669 90.0000 257.543 23767.359 98.685 2284.590 3591.823 94.0000 268.973 24822.140 103.064 1212.355 3593.468 A mass 234.041 235.044 236.046 238.051 16.00 2 Table 5 16. Mass Values of Enriched Uranium metal 50 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 108.360 10000.000 41.521 39850.119 0.050 35.0000 189.630 17500.000 72.662 32237.708 0.050 50.0000 270.900 25000.000 103.803 24625.297 0.050 75.0000 4 06.350 37500.000 155.704 11937.946 0.050 90.0000 487.620 45000.000 186.845 4325.535 0.050 94.0000 509.292 47000.000 195.149 2295.559 0.050 A mass 234.041 235.044 236.046 238.051 16.00 2 Table 5 17. Mass Values of Enriched UO 2 07 g/cm 3 ) 235 U wt (%) U mass (g) O (Nat) mass (g) 234 U 235 U 236 U 238 U 20.0000 95.489 8812.239 36.589 35116.879 5938.803 35.0000 167.068 15417.874 64.017 28402.109 5948.932 50.0000 238.613 22020.452 91.431 21690.407 5959.097 75.0000 357.782 33017.914 137.094 10511.096 5976.114 90.0000 429.238 39612.265 164.474 3807.650 5986.372 94.0000 448.288 41370.234 171.774 2020.592 5989.113 A mass 234.041 235.044 236.046 238.051 16.00 2

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99 Table 5 18. Molecular Weight, Intrinsic Source Strength an d Neutron Multiplication eigenvalue (k eff 3 ) 235 U wt (%) U metal Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 237.439 1.09E+02 9.84E+08 0.25687 0.00030 35.0000 236.980 8.82E+01 1.69E+09 0. 34069 0.00033 50.0000 236.521 6.76E+01 2.40E+09 0.41872 0.00044 75.0000 235.75 7 3.33E+01 3.58E+09 0.53376 0.00051 90.0000 235.298 1.27E+01 4.29E+09 0.59651 0.00058 94.0000 235.17 6 7.22E+00 4.48E+09 0.62943 0.00057 Table 5 19. Molecular Weight, Intri nsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Enriched UO 2 3 ) 235 U wt (%) UO 2 Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 269.442 1.57E+02 8.68E+08 0.16185 0.00019 35.0000 268.98 4 1.83E+02 1.49E+09 0.21681 0.00022 50.0000 268.525 2.10E+02 2.12E+09 0.26819 0.00030 75.00 00 267.760 2.55E+02 3.15E+09 0.34765 0.00038 90.0000 267.301 2.81E+02 3.78E+09 0.39194 0.00038 94.0000 267.179 2.89E+02 3.94E+09 0.40458 0.00042 Table 5 20. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of En 3 ) 235 U wt (%) U Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 237.439 3.27E+02 2.95E+09 0.37189 0.00042 35.0000 236.980 2.65E+02 5.08E+09 0.49722 0.00045 50.0000 236.521 2.03E+02 7.20E+09 0.607 00 0.00054 75.0000 235.75 7 9.99E+01 1.07E+10 0.76133 0.00073 90.0000 235.298 3.81E+01 1.29E+10 0.83982 0.00071 94.0000 235.17 6 2.17E+01 1.34E+10 0.86032 0.00081 Table 5 21. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenv alue (k eff ) of Enriched Enriched UO 2 3 ) 235 U wt (%) UO 2 Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 269.442 4.70E+02 2.60E+09 0.24359 0.00029 35.0000 268.98 4 5.50E+02 4.47E+09 0.33093 0.00036 50.0000 268.525 6.30E+02 6.35E+09 0.40917 0.00045 75.00 00 267.760 7.64E+02 9.46E+09 0.52398 0.00050 90.0000 267.301 8.44E+02 1.13E+10 0.58717 0.00057 94.0000 267.179 8.65E+02 1.18E+10 0.60133 0.00060

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100 Table 5 22. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of En 3 ) 235 U wt (%) U metal Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 237.439 5.44E+02 4.92E+09 0.44194 0.00043 35.0000 236.980 4.41E+02 8.46E+09 0.59148 0.00057 50.0000 236.521 3.38E+02 1.20E+10 0.71792 0.00067 75.0000 235.75 7 1.67E+02 1.79E+10 0.88965 0.00075 90.0000 235.298 6.36E+01 2.15E+10 0.97414 0.00071 94.0000 235.17 6 3.61E+01 2.24E+10 0.99561 0.00094 Table 5 23. Molecular Weight, Intrinsic Source Strength and Neutron Multiplication eigenvalue (k eff ) of Enriched Enriched UO 2 3 ) 235 U wt (%) UO 2 Mol Wt Source (10 yr aged) k eff 1 n/s 20.0000 269.442 7.83E+02 4.34E+09 0.29692 0.00029 35.0000 268.98 4 9.17E+02 7.46E+09 0.40403 0.00042 50.0000 268.525 1.05E+03 1.06E+10 0.49671 0.00047 75.00 00 267.760 1.27E+03 1.58E+10 0.63121 0.00066 90.0000 267.301 1.41E+03 1.89E+10 0.70284 0.00070 94.0000 267.179 1.44E+03 1.97E+10 0.72078 0.00072 Figure 5 1. Variation in isotopic Pu content versus burnup in PWR fuel.

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1 01 A B Figure 5 2. The PWR generat ed 4 metal intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source.

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102 A B Figure 5 3. The PWR generated 4 kg PuO 2 intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic sourc e.

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103 Figure 5 4. Typical neutron intrinsic source components for Pu metal (s.f. neutrons). B Figure 5 5. Typical neutron intrinsic source components for PuO 2 [s.f. and ( ) neutrons].

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104 Figure 5 6. The 4 kg spherical Pu Metal neutron intrinsic source ver sus 4 kg spherical PuO 2 neutron intrinsic source. A Figure 5 7. Comparison of source strengths from PWR fuel derived plutonium, 4 kg sphere A) neutrons, B) photons.

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105 B Figure 5 7. Continued. Figure 5 8. Variation of k eff in PWR fuel, 4kg sphere, determi

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106 Figure 5 9. Variation in isotopic Pu content vs. burnup in CANDU fuel A Figure 5 10. The CANDU generated 4 kg Pu metal intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source.

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107 B Figure 5 1 0. Continued. A Figure 5 11. The CANDU generated 4 kg PuO 2 intrinsic source as a function of energy. A) Neutron intrinsic source. B) Photon intrinsic source

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108 B Figure 5 11. Continued. Figure 5 12. Variation of k eff in CANDU fuel, 4kg sphere, determined

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109 A B Figure 5 13. Comparison of source strengths from CANDU fuel derived plutonium, 4 kg sphere. A) neutrons, B) photons.

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110 A B Figure 5 14. The 10 kg U metal intrinsic source as a function of energy. A) Neutron intrinsic source, B) Pho ton intrinsic source.

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111 A B Figure 5 15. The 10 kg UO 2 intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source.

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112 A B Figure 5 16. The 30 kg U metal intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source.

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113 A B Figure 5 17. The 30 kg UO 2 intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source.

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114 A B Figure 5 18. The 50 kg U metal intrinsic source as a function of energy. A) Neutro n intrinsic source, B) Photon intrinsic source.

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115 A B Figure 5 19. The 50 kg UO 2 intrinsic source as a function of energy. A) Neutron intrinsic source, B) Photon intrinsic source.

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116 A B Figure 5 20. Variations in U Metal source strength. A) neutrons, B) ph otons.

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117 A B Figure 5 21. Variations in UO 2 source strength. A) neutrons, B) photons.

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118 Figure 5 22. The U metal k eff Figure 5 23. The UO 2 k eff

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119 A B C D Figure 5 24. The 4 kg Pu metal ball in air projected on S N 1/8 symmetry mesh A) PENTRAN th th view).

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120 A B Figure 5 25. PENTRAN BUGLE 96 vs. MCNP5 (1 ): Neutron leakage profile (shielding calcula tion, no multiplication), 4 kg Pu metal. A) as a function of energy B) as a function of energy group.

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121 A B Figure 5 26 The MCNP5 / PENTRAN BUGLE 96 (1 ): Neutron leakage (shielding calculation, no multiplication), 4 kg WGPu metal. A) as a function of energy, B) as a function of energ y group.

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122 A B Figure 5 27. PENTRAN BUGLE 96 vs. MCNP5 (1 ): Photon leakage profile (shielding calcula tion, no multiplication), 4 kg WGPu metal. A) as a function of energy B) as a function of energy group.

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123 A B Figure 5 28 The MCNP5 / PENTRAN BUGLE 96 ( 1 ) Photon leakage ratio (shielding ca lculation, no multiplication), 4 kg WGPu metal. A) as a function of energy, B) as a function of energy group.

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124 A B Figure 5 29. Neutron leak age profile for 4 kg WGPu metal source, computed using MCNP5 (1 ). A) as a function of energy, B) as a function of energy group.

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125 A B Figure 5 30 P hoton leakage profile for 4 kg WGPu metal source computed using MCNP5 ( 1 ). A) as a function of energy, B) as a function of energy group.

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126 A B Figure 5 31 PENTRAN BUGLE 96 v ersus MCNP5 (1 ): Neutron leakage profile (with multiplication) for 4 kg WGPu metal neutron source. A) as a function of energy, B) as a function of energy group.

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127 CHAPTER 6 COMPUTATIONAL AND EX PERIMENTAL VALIDATIO N OF A WGPU NEUTRON LEAKAGE SOURCE USING A SHIE LDED PU BE NEUTRON SOURCE In previous chapters we performed a number of evaluations of SNM sources, several validated with laboratory experiments. Expertise gained in previous work, as well as recognizing the need to leverage computational transport method s to evaluate SNM sources led to the work described here. Therefore, we present in this chapter the development process for a unique shield design that transforms the complex neutron spectrum from a Pu Be neutron source (average energy of 4.61 MeV) to ne arly exactly the neutron signature leaking from a significant spherical mass (6.670 kg) o f WGPu metal (mean energy 2.11 MeV) Now covered by a patent 9 established through the University of Florida Research Foundation (UFRF), t his Nickel composite alloy shi eld assembly, fashioned in a specific geometry was derived completely through the use of computational transport methods. Utility of this device is clear, since it directly enables detector field testing without the expense and risk of handling large amou nts of SNM as WGPu. Figure 6 1A shows the 3 D MCNP model geometry rendered by VISED, and Figure 6 1B presents the 6.1 Computational Simulations Major differences between the normalized leakage spectra of WGPu metal and Pu Be neutron sources are displayed on Figure 6 2, where spectral features can be noted both as a function of energy (Figure 6 2A), and as a function of energy group (Figure 6 2B). Main reason for the differences is the intrinsic source of the two neutron sourc es, the Pu metal being over 99.99% based on spontaneous fission reactions, since in Pu Be over 99% of all neutrons come from ( ) reactions. Our research goal was to find the proper shield that shifts the Pu Be spectrum (red in Figure 6 2) into a spectru m as close as feasible to the Pu metal spectrum (blue in Figure 6 2). In

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128 doing so, we tried to preserve the characteristics of the Pu metal spectrum, including the peak probabilities, etc, (shown in Figure 6 2B) and the relative amplitude inherent between these peaks. First of all, observing the Pu Be spectrum in Figure 6 2, we note the large relative amplitude between the peak with a maximum at energy group 8 and the other peaks with lower energies. Therefore, the candidate material should absorb the neutr ons with energies higher than ~2.5 MeV, or scatter them by the requisite amount to lower energies. Also, the shield material should be transparent for the peaks corresponding to energy groups 8, 18, 21, 23, and 25. Note that low energy neutrons leaking fro m SNM sources have a very small contribution to the spectrum so, we are not interested in energies lower than ~30 keV (groups higher than energy group 30). There are a few materials with as high of an absorption cross section at energies higher than ~2.5 MeV as Nickel, Lead, Silicon, Aluminum, Iron, Magnesium, Manganese, and Graphite. Total absorption cross sections of these materials, from the ENDF/B VI.1Library, 49 are shown in Figure 6 3 as a function of energy, with energies spanning from 30 keV to 17.3 MeV. Note that for clarity, the same logarithmic scale was used for all the graphs and higher energies correspond to lower energy groups, and lower energies correspond to higher energy groups (see Section 2.4 for details). For comparison, Figure 6 4 show s the total absorption cross section of Indium, Cadmium, Hafnium and Silver, materials with lower propensity for absorption of high energy neutrons. Next step toward our goal of finding the proper shielding material to shift the spectrum of Be neutron source was to compare the materials with the total absorption cross section presented in Figure 6 3, considering pure materials, or combinations of each other, or

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129 with other materials, in order to minimize the shielding and to obtain the desired Pu metal Be leakage spectrum in front of a block of material, we can compute the leakage at different distances (via an F1 directional tally in MCNP5) and compare those using different materials. The MCNP model, as rendered by VISED code, is presented in Figure 6 5. Using this model we cannot find the exact dimensions of the shield, however, the set up will help us to compare the effect of passing certain thicknesses of different materials from an inc ident Pu Be neutron spectrum. We computed the leakage to observe the change in the profile of the spectrum, and the effectiveness of the materials in absorbing high energy neutrons, while 2B. For example, the results are shown for a 12 cm thickness of one of the candidate materials, Iron, in Figure 6 6. Iron is one of the most effective materials when considering absorption of high energy neutrons; a smaller thickness of Iron shielding is needed to obtain the s ame relative amplitude between the first two peaks of interest, corresponding to energy groups 8 and 18 as in P metal spectrum. Using Iron, the high energy neutrons are absorbed; however, not all of the 6 2) at low energies are aliased to mimic the neutron spectrum of Pu metal. In addition, the peaks with maxima corresponding to energy groups 23 and 25 are missing. Compared to Iron, the same thickness of Graphite as used in the previous example, 12 cm, is used here, and the Pu Be neutron spectrum passing through this material yields no appreciable shift, as indicated in Figure 6 7. Figure 6 8 shows the leakage obtained using 12 cm Copper, which is another relevant example for the methodology we used to ana lyze the materials. In this case, we have all the peaks corresponding to energy groups 8, 18, 21, 23, and 25. Relative

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130 amplitudes of first two peaks are indeed similar to the Pu metal spectrum, but the peaks corresponding to lower energy groups have differ ent relative amplitudes. Extended material study, with simulations rendered using the materials mentioned in this chapter or also presented in Chapter 7 (Section 7.3 Filtration effect study), with different dimensions (where most of the analyses have bee basis), guided us to the final Nickel composite alloy a material that has the properties we are seeking. Figure 6 9 depicts the steps of the transformation of the harder Pu Be neutron spectrum (with an average n eutron energy of ~4.61 MeV), due to interactions in the shield so that leakage neutron s are shifted in energy and beca me a close reproduction (within 10% of the relative difference between the amplitude of the peaks) of the neutron spectrum leaking from a significant spherical ( subcritical ) mass of WGPu metal ( average energy ~ 2 .11 MeV). Figure 6 10 shows the leakage obtained by using Nickel composite alloy, with the peaks marked and the features quite similar to the Pu metal spectrum (within 10% of the rel ative difference between the amplitude of the peaks). Now, having the material established, we are able to perform refinement transport simulations to determine the exact dimensions of the shield using the Pu Be capsule model. We investigated different sha pes for the shield, and concluded that a cylinder is most suitable for our needs, since the Pu Be capsule is cylindrical. In our computational trials, we also tried to produce the same leakage in all the directions (both axially and radially) relative to t he initial number of neutrons, as well as the neutron spectrum. We modified the dimensions of the Nickel composite alloy shielding centimeter by centimeter, and eventually millimeter by millimeter in order to optimize the shield design for leakage and spe ctrum matching purposes. Figure 6 11 depicts the leakage profiles obtained with a cylindrical geometry of the shield with a hole placed inside the

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131 shielding material where the Pu Be neutron source is placed. Details of the final geometry are presented in F igure 6 12. The Pu Be neutron spectrum shift via the Nickel composite alloy shield is depicted in Figure 6 13A, and the normalized to maximum value of the leakage spectrum is shown in Figure 6 u Be source, the shielded surrogate source yields 1.8404 x 10 6 (0.01%) n/s over the entire volume, equivalent to 6.670 kg WGPu metal mass yield. Comparison between WGPu metal leakage and the simulated obtained WGPu metal leakage using an encapsulated Pu B e source is presented in Figure 6 14, both of the spectra corresponding to the two spectra (WGPu and Surrogate). Relative differences between the amplitude of the peaks ar e within 10%, with very fine convergence for all Monte Carlo results. 6.2 Experimental Validation To test the validity of the shielded SNM source performance, we conducted an experiment utilizing a He 3 proportional counter with a high density polyethylene (HDPE) moderator for the detection of neutrons from the unshielded (bare) and shielded (filtered) Pu Be source. Our purpose was two fold: to validate a computational model of neutron detection using the two Pu source types and to conduct a study of Cd shi elding to reduce backscatter from concrete near the detector. 6.2.1 Materials and Procedures Be source was used in the experiments in the bare, as shown in Figure 6 15A, and filtered, as in Figure 6 15B, configurations; the assembly enabled s imulation of the neutron spectrum of WGPu metal via filtration. Inside the Nickel composite alloy cylinder a central cavity was created by tapping the interior pieces according to the design specified in

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132 Figure 6 12. The Pu Be source was placed inside the cavity once the lower and middle regions of the shield were assembled, and then the top pieces were installed; clamps were installed to ensure a close contact between shield disks to minimize the number of unfiltered neutrons reaching the detector. We use d a 3 He proportional tube detector with 2.54 cm diameter and a length of 30.48 cm, operating at 900 V. Varying thicknesses of high density polyethylene (HDPE) were used both in front of and behind the detector to allow for a verification of the computation al model and to aid in determining the optimal moderator thickness for future experiments. Entire experimental assembly was positioned on an aluminum cart and suspended approximately 102 cm off of the concrete floor of the detection laboratory to minimize floor scattered neutrons into the detector. Cardboard spacers were used to maintain the source in a single position relative to the center of the 3 He detector (see Figure 6 15) for all appropriate measurements. Since the source sat elevated inside the filt er assembly, a separate cardboard spacer was added to ensure the bare Pu Be source was maintained at the same vertical position as in the filtered case. For the entire experiment, the front face of the HDPE was maintained at a constant 45 cm from the sourc e centerline to match the computational model. We finally included, for the final portion of the experimental setup, the installation of various arrangements of cadmium (Cd) shielding to further minimize neutron scatter into the detector. Since at higher neutrons energies, Cd is an excellent scattering material, we experimented with three separate configurations (Figures 6 16A, 6 16B and 6 16C) to help us determine an arrangement that minimized the return of neutrons from both the floor and the concrete an d soil that existed to the right hand side of Figures 6 15 and 6 16.

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133 Three separate measurements were conducted during the experiment for each source configuration (bare and filtered). Separate 3 minute counts were performed with varying amounts of HDPE bo th in front of and behind the 3 He detector. Using three separate counts provided both an average count rate and standard deviation for each data point. We began each of the grouped measurements with 15 cm of HDPE in front of the detector and 0 cm behind it ; this configuration is shown for the case of the bare source (Figure 6 15A). After each count was completed, we relocated 0.5 cm of HDPE from the front of the detector to the rear region. Figure 6 15B shows a filtered source exposure with 7.5 cm of HDPE in front of the detector, and 7.5 cm to the rear. We continued this progression until we finally reached 0 cm of HDPE in front of the detector and 15 cm to the rear. We also conducted this procedure for each of the three Cd arrangements shown in Figures 6 16A, 6 16B, and 6 16C. 6.2.2 Results and Analysis Results for the six groups of experiments are shown in Figures 6 17A and 6 17B for the bare and shielded sources. Figure 6 17A illustrates the higher count rates that resulted from source exposures done wit h the larger versus smaller Cd shielding on the floor, and using the bare Pu Be source. Increased count rate was resulted from fast neutrons being preferentially scattered by the Cd rather than being absorbed, since Cd is an excellent fast neutron reflecto r. in Figure 6 17B is showing the converse situation for the shielded Pu Be source, where the filtration yielded a more thermal neutron spectrum that was then preferentially absorbed by the large Cd sheet, rather than being scattered into the detector. Fig ures 6 18A, 6 18B, and 6 18C show the count rate data grouped according to the Cd shielding configuration. Results obtained with the smaller Cd floor shielding (see Figure 6 18A) demonstrate intersections for the two source spectra at approximately 8.5 cm and 15.0 cm respectively of HDPE moderation. Similar result was achieved for the two additional Cd

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134 configurations shown in Figures 6 18B and 6 18C; however, the data intersections were far less dramatic. Using the smaller Cd shielding on the floor, the low est count rates for the bare source exposures were achieved, while the lowest count rates for the filtered source were from the small Cd shielding on the floor and the large Cd sheet standing beside the array. These curves dictate that two different confi gurations are best suited for the different source exposures: the bare source should be used solely with the smaller Cd floor shield, while the shielded source should also be used with the floor shield and the additional larger Cd sheet. Possible explanati on for the greater impact of the walls on the shielded source is the volume of the two neutron sources: the more localized bare Pu Be neutron source compared to a larger The MCNP5 predicted Be sources simulated using the MCNP Monte Carlo code are presented in Figure 6 19. Figure 6 20 displays the corresponding experimental results. Similar profiles are obtained using the two methods, computationally and by experiment, with difference s attributable to floor and surrounding albedo effects. In this chapter we described the procedure that was followed for designing, building, and laboratory Surrogate Shielded Source D esign for Pu which enable s the harder Pu Be source neutron spectrum [average energy of 4.6 1 MeV primarily due to ( ) interactions ] from a standard 1 Ci Pu Be source to be transformed, through interactions in the shield, so that leakage neutrons appro ximate the neutron spectrum leaking from a large, subcritical mass of WGPu metal (average neutron energy of 2.1 MeV, of multiplied spontaneous fission neutrons).

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135 Besides the possibility of using the WGPu energy spectrum wi thout the expens e and risk of sign ificant quantity materials, this shielded Pu Be source can be also used in the calibration of neutron detection devices, since n early all current calibrations of neutron detectors use 252 Cf for generation of a fission neutron spectrum The 252 Cf decays wi th a half life of ~2.65 years and therefore it must be continually produced, and it is very expensive to procure. By converting to the surrogate WGPu design, Pu Be sources relying on 239 Pu (T =24,110 y) and lasting hundred s of years may be used to precise ly calibrate and te st detectors for simulated WGPu metal neutrons Up to now, we presented a comprehensive characterization of different SNM neutron sources. In the next chapter we are using the neutron leakage of these sources in our investigation of diff erent materials in order to isolate regions of the neutron spectrum relative to neutron detection in 3 He.

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136 Table 6 1. Relative difference between the amplitude of the peaks, comparing WGPu leakage to final Surrogate Shield design leakage. Peaks Group Rel. dif.(%) 1 1 8 6 192 0 00002 2 18 4 309 0 00001 3 21 0. 568 0 00001 4 23 0. 165 0 00001 5 25 9 7 00 0 00004 A B Figure 6 1. The Pu Be Shielded Source Assembly. A) MCNP simulation, B) Experimental Design.

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137 A B Figure 6 2. The MCNP5 computed normalized leakage spectra of Pu metal and Pu Be neutron

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138 Figure 6 3. Total neutron absorption cross sections of Nickel, Lead, Silicon, Aluminum, Iron, Magnesium, Manganese, and Carbon. F igure 6 4. Total neutron absorption cross section of Indium, Silver, Cadmium, and Hafnium.

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139 Figure 6 5. Source Material MCNP5 model set up. Figure 6 12 cm Iron for filter ing the Pu Be spectrum compared to initial Pu Be spectru (red).

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140 Figure 6 12 cm Graphite for filtering the Pu Be spectrum compared to initial Pu Be spectru (red). Figure 6 cm Copper for filtering the Pu Be spectrum compared to initial Pu Be spectrum (red).

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141 Figure 6 9. Transformation of the Pu Be neutron spectrum in Pu metal spectrum [MCNP5 com Figure 6 cm Nickel composite alloy material for filtering the Pu Be spectrum compared to in itial Pu Be spectrum (red).

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142 Figure 6 11. The MCNP5 computed neutron spectrum profiles obtained with a cylindrical A Figure 6 12. Detailed geometry of the Nickel composite alloy shielded source A) computed dimensions of the shield. B) The VISED simulated design.

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143 B Figure 6 12. Continued. A Figure 6 13. The MCNP5 computed Pu Be versus Surrogate Shielded neutron sources as a neutron spectra.

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144 B Figure 6 13. Continued. Figure 6 14. Normalized neutron leakage comparison between Surrogate Shielded Source and WGPu source.

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145 A B Figure 6 15. Source Detector experimental set up. A) Bare Source. B) Filtered Source.

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146 A B Figure 6 16. Source Detector experimental set up. A) Bare Source and small Cd shielding below. B) No Source and large Cd shielding below. C) Bare Source, small Cd below, and large Cd shielding beside.

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147 C Figure 6 16. Continued. A Figure 6 17. Experimental Reactio n Rate versus Moderator Thicknesses with Varying Cd Shielding for A) the Bare Source, B) Shielded Source.

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148 B Figure 6 17. Continued. A Figure 6 18. Reaction Rate versus Moderator Thicknesses for Bare and Shielded Sources. A) Small Cd Floor Shielding B) Large Cd Floor Shielding C) Small Cd Floor Shielding and Large Cd Standing Shielding

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149 B C Figure 6 18. Continued.

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150 Figure 6 obtained using MCNP models. Figure 6 20. B experimentally obtained.

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151 CHAPTER 7 DETECTI ON OF SPECIAL NUCLEA R MATERIALS Using the computational tools and methods discussed in previous chapters, and the total leakage deter mined for SNM neutron sources, we now present our efforts related to designing a neutron detection array system for SNM neutron sources using gas proportional detectors. This challenging task is presented in several sections, including the summary of the s tudy done over thirty moderator materials which were investigated focusing on their energy filtering effects. We analyzed and established the limits of 3 He spectroscopy using high density polyethylene and ideal filter materials. All this work, based on the computational radiation transport methods, enabled us to present the design proposed for 3 He spectroscopy system using real filtering materials capable of resolving the spectra from SNM neutron sources of interest (metal and oxide) 7.1 Moderator Study 7. 1.1 Moderator Properties Overall, in support of our SNM detection efforts for parcel screening, we seek to determine if different regions of the source neutron energy spectrum can be selectively thermalized to augment absorption and subsequent detection in gas proportional counters (focusing here on 3 He detectors). As fast neutrons thermalize via collisions in a moderator their potential for subsequent detection in a nearby 3 He detector [undergoing a ( n,p ) reaction with Q=0.764 MeV] increases with thermal ization The 3 He cross section for a typical 4 atm pressure tube at room temperature, using macroscopic multigroup (BUGLE 96) cross sections, is shown in Figure 7 1. Toward this goal, a number of neutron moderators were selected and analyzed to evaluate t hem for ( n,p ) response in 3 He and ( ) response in BF 3 (Equations 2 3 and 2 4). Figure 7 2A, shows the simple standard geometry (7,612 fine meshes), with 24 course meshes (cells) along 12

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152 cm moderator, established to perform 3 D S N computations using the parallel PENTRAN code with the SN M leakage spectra as an isotropic volumetric source in the front cell of the 12 cm moderator block material. We used for our deterministic simulations S 24 angular quadrature and P 3 scattering anisotropy, following the convergence study performed for the de tection simulation in Section 3.1.2. Transport models for moderator materials were executed using the BUGLE 96 library (see Section 2.4). Still, what is truly detected is based on the reaction rate in 3 He, which is not explicitly modeled in the problem. To investigate the expected 3 He reaction rate resulting from the best possible moderation effects in each material, we computed the reaction rate in 3 He, assuming that 4 atm 3 He is uniformly diluted throughout the block material. With this approach, neutr on moderation effects are solely the result of the best achievable moderator properties of the material. Note that the 3 He ( n,p ) reaction rates ( R ) in the block are computed as a function of BUGLE 96 energy group using Equation 3 8 Regarding the complete assessment of the many moderators we considered, we sought to identify the relative effectiveness of each in isolating the fast, epithermal, and thermal portions of the neutron spectrum relative to neutron detection in 3 He. Spectral energy bands bound by B UGLE 96 were defined: Groups 1 20 (to 0.7 MeV), 21 41 (0.7 MeV to 10 eV), and 42 47 (thermal), corresponding to our working definition of fast, epithermal, and thermal energies, respectively. Examples of fast (9 th energy group), epithermal (30 th energy gr oup) and thermal (47 th energy group) neutron fluxes in polyethylene are visualized in Figures 7 2B, 7 2C and 7 2D. To obtain these results, we post processed our 3 D forward S N transport data for each moderator according to ( n,p ) reaction rate in 3 He to id entify the important energies in each neutron energy range.

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153 Data presented in Table 7 1 shows the optimum moderator needed relative to the type of R fast, epit hermal and thermal neutrons that can be detected via ( n,p ) reaction in 3 He (see Equation 7 1) and the average R weighted energies within each spectral interval and over all the energy groups (see Equation 7 2). ; ; (7 1) ; ; (7 2) There are also the locations of maximum neutron and gamma fluxes ( in Equation 7 3) in moderator material (the same wi th the maximum of R ), averaged over neutron, respective gamma flux spectrum as well as the ratio of the two maxima (for neutrons and photons). In order to optimize the thickness of moderator the following reaction locations can be useful to analyze: (7 3) From the data in Table 7 1, we note that for a large number of the light element nuclides, the relative fraction of thermal neutrons in the moderator block was above 95%, with the best thermalization properties for reactions in 3 He being for the material Kynar TM a high molecular weight thermoplastic polymer that is chemically inert. Other observations include that low density polyurethane, graphite foam, aluminum, Dow Etha Steel 304, Copper, Gra phite, and Teflon distribute neutrons across a range of energies, resulting in a number of 3 He R weighted neutron energies between 0.134 MeV, up to 3.373 MeV.

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154 Later on, in this chapter, we will present another detailed study related to the effect (on spe will be presented to reveal insight into how specific materials might be combined to target specific neutron energies of interest for detection, which is the topi c of the following sections. 7.1.2 Energy Band Separation in Polyethylene Since we are using 3 He and BF 3 detectors, polyethylene or paraffin moderators will be used to increase the detection efficiency. High density polyethylene (HDPE) moderator (1.07 g/cm 3 the same model shown in Figure 7 2A, with 3 He gas diluted throughout the HDPE moderator. The 3 He ( n,p ) reaction rate matrix, shown in Figures 7 3, was computed as a function of BUGLE 96 energy group and the distance into the HDPE moderator block. All simulations were performed independently fo r every energy group to identify exactly w h ere the neutrons with certain energies will have a maximum ( n,p ) reaction rate ef fect in 3 He The MCNP5 Monte Carlo calculations were performed with less than 1% statistical relative error, 1 confidence interval. In Figure 7 indicating the maximum response in 3 He for a given distance (cell number) in the moderator, important relative to the reaction rate in 3 He gas at a certain distance in HDPE moderator. Since eac h cell of the polyethylene moderator is 0.5 cm thick, the 24 cells directly correspond to the first 12 cm polyethylene moderator. Similarly, in Figure 7 3B, the 11 cells correspond to the first 5.5 cm of polyethylene. Figure 7 3B presents the position in t he moderator, along an energy group, looking 3 He gas. In this

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155 maximum response in 3 He for every energy group. Therefore, t he spectral sensitivity of this approach will be lim ited to eight energy bands: Band I: from energy group 1 to 8 (3.68 17.3 MeV), maximum R at 3.75 cm in cell 8; Band II: from energy group 9 to 18 (1. 3.68 MeV), maximum R at 3.25 cm in cell 7; Band III: from energy group 19 to 23 (0.369 1 MeV), maximum R at 2.75 cm in cell 6; Band IV: from energy group 24 to 29 (31.8 369 keV), maximum R at 2.25 cm in cell 5; Band V: from energy group 30 to 38 (0.214 31.8 keV), maximum R at 1. 75 cm in cell 4; Band VI: from energy group 39 to 42 (5.04 214 eV), maximum R at 1.25 cm in cell 3; Band VII: from energy group 43 to 45 (0.414 5.04 eV), maximum R at 0.75 cm in cell 2; Band VIII: from energy group 46 to 47 (0 0.414 eV), maximum R at 0.25 cm in cell 1. Of course, a different spectrum of neutrons will modify the amplitude of the reaction rate, but the maximum reaction rate for each and every group of energy will be reached after the same distance, regardless of the spectrum. Spectral effects can be observed in Figure 7 4, where the SNM spectra are used as planar sources in front of the moderator block. We separated the energy band on the figure with horizontal lines and the maxima reached by the neutrons from an energy band with vertic al lines; the vertical lines have the same position regardless of neutron spectra used. Figure 7 5 shows the small contribution of the low energy neutrons leaking from the SNM neutron sources (> group 30). We will neglect this part of the spectra, focusi ng our work on Bands I to IV, corresponding to energy groups 1 to 29 (31.8 keV to 17.3 MeV). Maximum reaction rate for each spectral band is reached in cells 5 to cell 8, from 2.25 cm to 3.75 cm. Figure 7 6 shows the normalized to the maximum reaction rat e curves in 3 He using HDPE moderator and SNM neutron sources (rel. errors < 0.5 %); enclosed in the rectangular shape are the four most important cells for our study. There is practically no distinction between Pu metal and oxide or U metal and oxide.

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156 7.2 Spectral Detection Analysis Using Ideal Filters Radiation transport analysis yielded a spectrum unfolding strategy, reported here, based on the energy structure of the BUGLE 96 cross section library, with 47 neutron energy groups. Therefore, the practical limits in designing a neutron detector array to resolve the spectra from SNM neutron sources, to the greatest extent permissible, can be assessed based on computational transport studies. 7.2.1 Diluted 3 He A pproximation throughout the Moderator In orde r to observe the effect of using the diluted 3 He gas, we modeled blocks of 12 cm polyethylene with rows containing three 3 He detectors, similar to what is shown in Figure 7 8. Practically, the rows of 3 He detectors correspond to the cells used in our dilut ed approximation. First block has three 3 He detectors in a row after 0.25 cm polyethylene; second block is located after 0.75 cm polyethylene, and so on. The MCNP5 results [less than 1% statistical relative error (1 )] are shown in Figure 7 7 with blue co lor. In the same figure (red color) are the results for the reaction rate curve when the first row of 3 He detectors follow after 0.5 cm thick polyethylene, and the second block with a row of 3 He after 1 cm of polyethylene, and so on. On the figure, the gre en color shows the reaction rate curve with no polyethylene in front of the first row of Be neutron source. Since our concern is related with the upper region of the reaction rate curve (rows 5, 6, 7 and 8), the best fit of the diluted 3 He gas reaction rate is obtained for the reaction rate curve when the position of the first row of 3 He detectors follows 0.5 cm in polyethylene. Our results show that when we relate the distance from infinitely diluted 3 He to the distance for a row of detectors, we have to add 0.25 cm; the adjustment is due mainly to extra moderation in 3 He gas detectors and the modification in backscattering.

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157 7.2.2 Reference (without Filtering) SNM Detection Four positions that are interesting to us are shown in Figure 7 8 with the 3 He rows of detectors embedded at 2.5 cm, 3 cm, 3.5 cm and 4 cm in polyethylene moderator; the reference is a plane source placed on the left side of the block. Using our previous detailed work regard ing the spectral characterization of the SNM neutron sources, the MCNP5 computed normalized leakage spectra of Pu metal and PuO 2 in Figure 7 9 while the spectra of U metal and UO 2 are shown in Figure 7 10. Our research work is focusing now on differentiation of the SNM spectra, metal and oxide. Figures 7 11 and 7 12 shows d etected spectra for Pu (metal vs. oxide) and U (metal and oxide), respectively, using a detection assembly based on HDPE moderator and 3 He detectors at staggered positions presented in Figure 7 8, without filtering energy [MCNP5 calculations, less than 1% statistical relative error (1 )]. The R provided by Band IV reflects the lack (oxide) or the presence (metal) of the peak corresponding to group 23 (~ 0.5 MeV). Due to the relatively larger peaks in the bands corresponding to higher energies as a result of neutrons generated from ( ) reactions, the oxide induces higher reaction rates in this part of the spectrum. However, there is no isolation of the R which prohibits distinction of the source type. Figure 7 13 reveals the difference between detected spectra of the Pu Be neutron so urce Be source, corresponding to ~4.2 MeV energy peak. 7.2.3 Strategy for Improvi ng the Spectral Detection Using Filter Materials With the wide use of gas proportional detectors, it is an important research goal, and would be a significant technical milestone, to identify the neutron spectrum using these types of detectors. We used th e theoretical model with 3 He diluted throughout 4 blocks of polyethylene,

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158 12 cm thick, to predict the maximum possible resolution that can be obtained using ideal filter materials. Further research involving real filter materials to selectively remove neut rons from the different energy bands of the spectrum will be presented later in this chapter. In the following section we summarize the strategy followed for each detector block: In the First block it is proposed that a filter material be used to remove the neutrons from energy gro ups higher than 24 (31.8 keV); then a row of 3 He detectors is placed following 2.5 cm of polyethylene. The HDPE will enable neutrons from Band IV to reach maximum t hermalization, and they will subsequently be counted (Figure 7 1 4 A). For the Second detector block the target will be neutrons in energy Band III, and the filter material will remove the neutrons from the other regions. The 3 He detectors row will be placed after 3 cm in polyethylene, and the neutrons from Band III reach a maximum thermalization (Figure 7 14 B). For the t hird and fourth blocks the embedded 3 He detectors will be at 3.5 cm, respectively at 4 cm, targeting the measurements of neutrons from Band I and Band II, as shown in Figures 7 14 C) and D). Practic ally, we extract the four energy bands from the energy group matrix shown in Figure 7 3B. The computational results obtained using ideal filters with 3 He gas diluted throughout polyethylene moderator is highlighted with red in Figures 7 15 to 7 20. The hig h energy peak from Pu Be neutron source is represented by the higher relative response in this region (energy groups 1 8), comparing with the detection of the other SNM neutron sources. A great effect in differentiation between metal and oxide neutron sou rces is the presence of a much higher peak for the oxides in the upper energy region of the spectrum, with a

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159 detected profile (Figure 7 20) yields the characteristi cs for metal sources, with a maximum detection in Band III, and characteristically lower in Band II. The differences between SNM neutron spectra with respect to partitioning in the energy bands we identified are represented in the detection device (theoret ical solution) as shown in Figures 7 21 to 7 23. For comparison between metal and oxide, Figure 7 21 shows the response of Pu, and Figure 7 22 the response of U, as a function of energy band. Figure 7 23 shows the difference in detection between Pu Be neu tron source and the Be and computational results obtained. 7.3 Filtration Effec t Study In the previous section, an idealized strategy was presented leveraging that an optimal spectral fidelity is achievable for SNM detection using four energy bands spanning among groups 1 to 29 (31.8 keV to 17.3 MeV ). Using ideal filter materials t o remove the neutrons from different energy bands we predicted the maximum neutron spectral resolution obtainable using this approach. This section contains a study of a number of materials that can be used for filtering different parts of the SNM spectr a We used the computational model presented in Figure 7 2A different thicknesses of the materials. Our methodology can be seen better in Figure 7 29 where Tant alum is the moderator used, and we present the effect of passing 6 cm (red color) and 12 cm (green color) thickness of Tantalum with a flat neutron spectrum (blue color), reflecting the cross sections of the material under observation. The 6 cm and 12 cm t hicknesses were chosen arbitrarily; more data is

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160 available for all the range from 0 to 12 cm moderator. The 0 cm corresponds to the incident the moderator 28. For a better through different thickness of material, the leakage is normalized to th e maximum. On the graph are highlighted the four energy regions that we are trying to filter. Projected in the background is a PuO 2 total neutron leakage spectrum to guide the eye through the special features of an SNM neutron spectrum. All the other figur es follow the methodology described in this paragraph. In Figure 7 24, the flat profile of the spectrum is not affected by the air. As a result, we can continue to use the air need an e xact absolute number of the reaction rate and/or leakage. Next two moderators, polyurethane (Figure 7 25) and Dow foam (Figure 7 26), induce a small change in the leakage profile. With some approximation, the change is small and can be neglected. In the s ame category can be included Helium gas (Figure 7 27) which absorbs the lower energy neutrons and unaltered the profile for the rest of the spectrum. Cadmium will not only absorb thermal neutrons, but also it will affect the high energy profile (bands I II ). Together with Tantalum (Figure 7 29) and Gold (Figure 7 30), it can be used to target the energy bands III IV. Indium (Figure 7 31) and Hafnium (Figure 7 32) are very good absorbers for thermal and epithermal neutrons, with energies lower than 30 keV. They have also important effects on energy in band I and partial on energy in band II. They can be used for filtering the energy bands II III. Copper (Figure 7 33), Iron (Figure 7 34), Cesium (Figure 7 35), and Iodine (Figure 7 36) can be targeted by usi ng the same energy bands.

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161 for energy Band II, Silver (Figure 7 37) is a candidate material, which is a very good absorber for thermal and epithermal neutrons. Similar properties are shared by Stainless Steel (Figure 7 38), Nickel (Figure 7 39), Lead (Figur e 7 40), Vanadium (Figure 7 41), Cobalt (Figure 7 42), and Manganese (Figure 7 43); they absorb very well the high energy neutrons from Region I and partial form Region II. Better transparency for energy Band II can be observed for Graphite (Figure 7 44), BeO (Figure 7 45), Teflon (Figure 7 46), and Aluminum (Figure 7 47). However, they are not as good absorbers for high energy neutrons and also for thermal and epithermal neutrons. In fact, Aluminum is very transparent to the small energy neutrons (less tha n 30 keV). Celotex (Figure 7 48), ABS fm160 (Figure 7 49), Concrete (Figure 7 50), and PVC (Figure 7 51) are candidate materials that are transparent for the energy Bands I II. Finally, the moderators that can be used for targeting Energy Band I (using a proper are presented. Several candidate materials are shown here: Polyethylene (Figure 7 52), Paraffin (Figure 7 53), Kynar (Figure 7 54), Nylon (Figure 7 55), PVT (Figure 7 56), Lexan (Fig ure 7 57), Plexiglas (Figure 7 58), Asphalt (Figure 7 59), and ABS Plastic (Figure 7 60). The B figures show the profile of the leakage with the thermal neutrons removed. 7.4 Detection Device Proposal Previous studies presented in this thesis, namely the s pectral characterization of the SNM materials, the moderator study, the separation in four energy bands in HDPE, the ideal and the real filtering materials led us to recommend the following detection assembly to isolate the four energy bands and resolve th e spectra from SNM neutron source s of interest (metal and oxide). For targeting energy B and IV Cadmium is one of the best suitable material. Figure 7 61 shows the effect on the transmitted flat neutron spectrum through 3 cm of Cadmium (red line) together with an improved combination of 3 cm Cadmium and 1 cm Hafnium (blue line).

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162 For targeting energy B and III 1 cm Indium can be used as shown in Figure 7 62 (red line). The blue curve in Figure 7 62 illustrates that the filtering effect is improved by addin g 5 mm Ta. For targeting energy B and I I, we propose for filtering 16 cm Concrete and 1 cm Hf, as shown in Figure 7 63. For targeting energy B and I, the best solution consists in a combination of 13 cm Asphalt and 1 mm Cadmium to remove the thermal neutron s (see Figure 7 64). Corresponding to the targeted energy band, four detection assemblies (blocks) are modeled and presented in Figures 7 65 to 7 68 by placing the above combination of filtering materials in front of the HDPE with the rows of 3 He de tectors at 2.5 cm, 3.0 cm, 3.5 cm, and 4.0 cm (see Figure 7 8). For comparison, we performed independent simulation for every detection block using the SNM neutron sources in front of the filter materials, in the same way in which we analyzed the ideal f iltering case. Table 7 2 for Plutonium and in Table 7 3 for Uranium are presenting the simulated results for the detection of the neutrons corresponding to the four energy bands, together with the relative difference between metal and oxide. Our relevant c riteria utilized to analyze the materials chosen for filtering the energy bands includes the comparison between the relative reaction rate differences between metal and oxide obtained using ideal filters (red lines) and real materials (blue lines), as show n in Figure 7 69 for Plutonium and in Figure 7 70 for Uranium. Due to the impracticality in removing all of the neutrons from the energy bands other than the desired/measured targeted band, the features of the real material filters case are smoothed compar ed to the ideal case results.

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163 cross arrangement, as shown in Figure 7 71, which also enables orthogonal independent measurements of the reaction rate corresponding t o the four energy bands. In Table 7 4 for Plutonium, Table 7 5 for Uranium, and Table 7 6 for Pu Be and Surrogate WGPu neutron sources are presented the results obtained using this model of detection assembly with the SNM neutron sources in the central pos ition, at 30 cm from the front faces of every detection block. In Figures 7 69 for Plutonium and 7 70 for Uranium, the relative reaction rate differences between metal and oxide are depicted with green line. These figures show that the differences between the results obtained by independent simulated measurements, using the SNM neutron sources in front of every detection block (blue line) and the results obtained by modeling the SNM sources in the center of the detection assembly (green line) are not signif icant. We can exploit the relative Ratios of the Reaction Rates from the four detection blocks, corresponding to the four energy bands, to directly differentiate the SNM material; the Ratios presented in the Table 7 7 would be set up to electronically yie sources assuming that the results were not affected by background radiation (the background counts are subtracted or the system is scree ned against background radiation); the fingerprint signature of Pu Be and WGPu Surrogate neutron sources can be used for a future laboratory experimental validation of the simulated model. Two major challenges that the proposed detection device should ove rcome are reflected in Table 7 7. First, the difficulty to differentiate between Pu metal and oxide; there are very small differences between the reaction rate ratios obtained using the two different neutron sources. However, this impediment can be suppres sed by increasing the amount of time for detection,

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164 improving the statistics of the measurements. Table 7 6 shows the detection time t necessary for obtaining equivalent statistics (standard deviation) in the Monte Carlo simulations and experimental measu rements (Equation 7 4). (7 4) where: = standard deviation associated to the experimentally measured count rates; = standard deviation associated to Monte Carlos simulated count rates; = standard deviation associated to experimental counts measurements in the time t; = Monte Carlo simulated count rates. 7, a much better differentiation between U metal and oxide is possible comparing to the Pu metal and oxide case. However, the small count rate obtainable when using U metal neutron source raises the second challenge for our proposed detection device: beside the long time needed for measurements, the background radiation can easily affect the results. Further thorough analysis is necessary to overcome these issues and to extend the practicality of the system over all the neutron sources of interest. This cha pter was conclude with the recommended design for a neutron detector array assembly using 3 He detectors intended to resolve the spectra from SNM neutron sources. We have successfully accomplished the overall research objective by correlating our efforts de scribed in the previous chapters regarding the complete characterization of SNM neutron sources with our ample study, the most comprehensive one up to date, of over thirty moderators

PAGE 165

165 analyzed to identify the relative effectiveness in isolating regions of t he neutron spectrum relative to neutron detection. Based on our extended study of high density polyethylene moderator which reveal the practical limits of the neutron spectroscopy using gas proportional detectors, we present ed here the optimally detected s pectral differences between SNM materials (Plutonium and Uranium), metal and oxide, using ideal filter materials We have also analyzed a number With this research work w e have conv incingly demonstrated that the spectral sensitivity of neutron spectroscopy can be assessed using computational transport studies

PAGE 166

166 Table 7 1. Modera tor performance study, using Pu Be, Pu O 2 and Pu m etal n source spectrum transmitted through 12 cm of mode rator, 67 Group n BUGLE 96 cross section library. Mat l Name SNM Source Det Type ( g/c m 3 ) R Wgtd Fast Fraction R Wgtd Epitherm. Fraction R Wgtd Thermal Fraction G1 20 Fast n Energy ( MeV ) G21 41 Epitherm. n Energy ( MeV ) G42 47 Thermal n En ergy ( MeV ) All R Rwgtd n Energy ( MeV ) Mat l a n R ( #/s ) Matl b n xmax ( cm ) Mat l c R ( #/s ) Matl d xmax ( cm ) Matl e n / xmax Air humid PuBe 3 He 1.203E 03 81.06% 18.94% 0.00% 3.8669 0.3754 Thermal 3.20561 1.02E 03 5.91605 9.32E 09 10.55610 0.560439 BF 3 84 .54% 15.46% 0.00% 5.5136 0.3331 Thermal 4.71249 2.66E 04 4.69428 1.27E 05 10.35140 0.453492 PuO 2 3 He 65.66% 34.34% 0.00% 2.2415 0.3525 Thermal 1.59286 1.48E 03 5.66068 2.16E 02 1.23588 4.580260 BF 3 54.44% 45.56% 0.00% 2.9646 0.3110 Thermal 1.75559 2.42E 04 5.89806 2.35E+01 1.38013 4.273550 PuM 3 He 61.57% 38.43% 0.00% 2.2183 0.3627 Thermal 1.50512 1.48E 03 5.37246 1.34E 02 1.23366 4.354900 BF 3 50.79% 49.20% 0.00% 3.1867 0.3225 Thermal 1.77738 2.51E 04 5.36654 1.45E+01 1.37761 3.895550 ABSf m160 PuBe 3 He 1.600E 01 3.77% 10.73% 85.50% 3.7798 0.0435 Thermal 0.14724 1.74E 02 5.57748 1.29E 08 5.10677 1.092170 BF 3 5.63% 11.10% 83.28% 5.4869 0.0463 Thermal 0.31399 3.10E 03 5.45699 1.80E 05 5.38060 1.014200 PuO 2 3 He 1.96% 10.94% 87.10% 2.25 79 0.0428 Thermal 0.04903 3.41E 02 5.67754 8.37E 03 0.84974 6.681530 BF 3 1.55% 11.59% 86.86% 3.0308 0.0458 Thermal 0.05234 5.93E 03 5.67781 9.19E+00 0.91244 6.222650 PuM 3 He 1.70% 10.99% 87.30% 2.2767 0.0440 Thermal 0.04361 3.63E 02 5.68449 5.17E 03 0.84822 6.701670 BF 3 1.41% 11.64% 86.95% 3.3054 0.0471 Thermal 0.05194 6.34E 03 5.67841 5.68E+00 0.91083 6.234350 ABSPlastic PuBe 3 He 1.024E+00 0.03% 0.92% 99.05% 3.5049 0.0077 Thermal 0.00124 9.78E 01 4.71873 4.88E 08 5.15800 0.914837 BF 3 0. 05% 0.94% 99.01% 5.3081 0.0088 Thermal 0.00259 1.70E 01 4.71756 6.76E 05 5.12283 0.920889 PuO 2 3 He 0.02% 0.93% 99.05% 2.2280 0.0080 Thermal 0.00055 1.19E+00 4.21859 1.84E 03 0.25000 16.874400 BF 3 0.02% 0.95% 99.03% 3.0769 0.0091 Thermal 0.00061 2. 07E 01 4.21818 2.12E+00 0.25000 16.872700 PuM 3 He 0.02% 0.93% 99.05% 2.2941 0.0081 Thermal 0.00053 1.20E+00 4.19168 1.14E 03 0.25000 16.766700 BF 3 0.02% 0.95% 99.03% 3.3988 0.0092 Thermal 0.00065 2.08E 01 4.19119 1.31E+00 0.25000 16.764800 Alumin um PuBe 3 He 2.700E+00 57.13% 42.86% 0.00% 3.0400 0.3412 Thermal 1.88309 9.43E 04 1.32403 2.87E 08 3.33924 0.396508 BF 3 55.46% 44.54% 0.00% 4.8215 0.3025 Thermal 2.80874 2.00E 04 1.50954 4.11E 05 3.31044 0.455995 PuO 2 3 He 45.66% 54.33% 0.01% 2.0485 0.3186 Thermal 1.10843 1.16E 03 0.68895 9.76E 05 0.25 000 2.755810 BF 3 31.78% 68.21% 0.00% 2.7206 0.2832 Thermal 1.05783 2.07E 04 0.85194 1.24E 01 0.25000 3.407740 PuM 3 He 42.31% 57.68% 0.01% 2.0444 0.3221 Thermal 1.05075 1.17E 03 0.70581 6.02E 05 0.25000 2.823240 BF 3 29.45% 70.54% 0.01% 2.9296 0.2871 Thermal 1.06519 2.13E 04 0.85941 7.63E 02 0.25000 3.437650 Asphalt PuBe 3 He 2.200E+01 0.02% 0.67% 99.31% 3.5173 0.0067 Thermal 0.00073 7.81E 01 1.74836 6.10E 08 4.24133 0.412219 BF 3 0.03% 0 .69% 99.29% 5.3487 0.0076 Thermal 0.00154 1.36E 01 1.74813 8.49E 05 4.20886 0.415344 PuO 2 3 He 0.01% 0.69% 99.29% 2.2651 0.0071 Thermal 0.00037 7.65E 01 1.74418 4.16E 04 0.25000 6.976720 BF 3 0.01% 0.71% 99.28% 3.1539 0.0081 Thermal 0.00042 1.33E 01 1.74406 5.12E 01 0.25000 6.976240 PuM 3 He 0.01% 0.70% 99.29% 2.3436 0.0072 Thermal 0.00036 7.58E 01 1.74090 2.57E 04 0.25000 6.963590 BF 3 0.01% 0.71% 99.28% 3.4901 0.0083 Thermal 0.00046 1.32E 01 1.74076 3.16E 01 0.25000 6.963030 Celotex PuBe 3 H e 3.100E 01 0.78% 4.71% 94.50% 3.7375 0.0236 Thermal 0.03038 7.47E 02 5.68779 1.40E 08 6.03970 0.941735 BF 3 1.18% 4.89% 93.94% 5.4639 0.0259 Thermal 0.06568 1.31E 02 5.66139 1.99E 05 6.09329 0.929120 PuO 2 3 He 0.42% 4.73% 94.85% 2.2626 0.0235 Therm al 0.01067 1.35E 01 5.70087 2.92E 03 0.25000 22.803500 BF 3 0.34% 4.93% 94.73% 3.0478 0.0258 Thermal 0.01151 2.35E 02 5.69957 3.29E+00 0.25000 22.798300 PuM 3 He 0.37% 4.74% 94.89% 2.2924 0.0240 Thermal 0.00958 1.43E 01 5.70336 1.81E 03 0.25000 22.8 13400 BF 3 0.31% 4.94% 94.75% 3.3351 0.0264 Thermal 0.01156 2.49E 02 5.70052 2.03E+00 0.25000 22.802100 Concrete PuBe He 3 2.300E+00 0.18% 2.89% 96.92% 3.3468 0.0139 Thermal 0.00656 2.36E 01 5.72792 2.25E 08 2.96765 1.930120 3 He 0. 24 % 2 98 % 96.77 % 5.0521 0.0155 Thermal 0.01277 4.11E 02 5.72303 3.20E 05 2.94840 1.941070 PuO 2 BF 3 0.11% 2.90% 96.99% 2.1833 0.0140 Thermal 0.00289 3.53E 01 5.71770 1.24E 04 0.25000 22.870800 3 He 0.09% 2.99% 96.92% 2.8990 0.0156 Thermal 0.00299 6.14E 02 5.71650 1.55E 01 0.25000 22.866000 PuM BF 3 0.10% 2.90% 97.00% 2.2160 0.0142 Thermal 0.00265 3.62E 01 5.71827 7.62E 05 0.25000 22.873000 3 He 0.08% 2.99% 96.93% 3.1669 0.0158 Thermal 0.00304 6.29E 02 5.71665 9.59E 02 0.25000 22.866600

PAGE 167

167 Table 7 1. Continued Mat l n ame SNM s ource Det t ype ( g/c m 3 ) R Wgtd f ast f raction R Wgtd e pitherm. f raction R Wgtd t hermal f raction G1 20 f ast n e nergy ( MeV ) G21 41 e pitherm. n e nergy ( MeV ) G42 47 t hermal n e nergy ( MeV ) All R wgtd n e nergy ( MeV ) Mat l a n R ( #/s ) Matl b n xmax ( cm ) Mat l c R ( #/s ) Matl d xmax ( cm ) Matl e n / xmax Copper PuBe BF 3 8.960E+00 30.55% 69.36% 0.09% 2.5234 0.2681 Thermal 0.95681 1.26E 03 2.87189 2.24E 09 0.64768 4.434130 3 He 25.34% 74.59% 0.07% 4.3873 0.2450 Thermal 1.29438 2.59E 04 3.13249 3.40E 06 0.64281 4.873150 PuO 2 B F 3 27.16% 72.78% 0.06% 1.8338 0.2677 Thermal 0.69285 1.37E 03 2.27070 2.84E 06 0.25000 9.082780 3 He 15.96% 83.99% 0.06% 2.4554 0.2443 Thermal 0.59701 2.63E 04 2.68598 3.60E 03 0.25000 10.743900 PuM BF 3 25.86% 74.08% 0.06% 1.8158 0.2691 Thermal 0. 66891 1.37E 03 2.09236 1.75E 06 0.25000 8.369420 3 He 15.26% 84.69% 0.05% 2.6099 0.2460 Thermal 0.60656 2.65E 04 2.46496 2.22E 03 0.25000 9.859840 DeutPoly PuBe 3 He 1.000E+00 0.08% 4.27% 95.65% 3.5393 0.0075 Thermal 0.00311 3.70E 01 5.72776 4.30E 08 5 .11114 1.120640 BF 3 0.11% 4.40% 95.49% 5.3276 0.0090 Thermal 0.00641 6.43E 02 5.72329 5.96E 05 5.07587 1.127550 PuO 2 3 He 0.05% 4.28% 95.66% 2.2594 0.0076 Thermal 0.00151 4.17E 01 5.71662 2.20E 03 0.25000 22.866500 BF 3 0.04% 4.41% 95.54% 3.122 2 0.0091 Thermal 0.00172 7.25E 02 5.71356 2.51E+00 0.25000 22.854200 PuM 3 He 0.05% 4.28% 95.67% 2.3236 0.0077 Thermal 0.00146 4.19E 01 5.71651 1.36E 03 0.25000 22.866000 BF 3 0.04% 4.41% 95.54% 3.4423 0.0092 Thermal 0.00184 7.29E 02 5.71316 1.55E+0 0 0.25000 22.852700 DowEFm221 PuBe 3 He 3.500E 02 43.77% 31.40% 24.84% 3.8455 0.1419 Thermal 1.72758 1.73E 03 3.42684 1.04E 08 9.08622 0.377147 BF 3 53.02% 27.63% 19.36% 5.5157 0.1389 Thermal 2.96264 3.86E 04 2.71348 1.43E 05 9.23312 0.232959 PuO 2 3 He 27.02% 40.72% 32.27% 2.2574 0.1366 Thermal 0.66547 3.09E 03 3.83786 1.71E 02 1.30219 2.947230 BF 3 21.34% 46.32% 32.34% 3.0031 0.1344 Thermal 0.70305 5.35E 04 3.86438 1.86E+01 1.45513 2.655700 PuM 3 He 24.11% 42.60% 33.29% 2.2547 0.1415 Thermal 0.60392 3.23E 03 4.02316 1.06E 02 1.29965 3.095580 BF 3 19.43% 47.73% 32.84% 3.2512 0.1396 Thermal 0.69830 5.69E 04 4.00929 1.15E+01 1.45225 2.760730 D2O PuBe 3 He 1.100E+00 0.16% 6.29% 93.55% 3.5846 0.0096 Thermal 0.00616 2.03E 01 5.71736 3.62E 08 4.7 0693 1.214670 BF 3 0.22% 6.50% 93.27% 5.3581 0.0114 Thermal 0.01279 3.53E 02 5.70915 5.08E 05 4.66637 1.223470 PuO 2 3 He 0.10% 6.30% 93.59% 2.2827 0.0097 Thermal 0.00293 2.41E 01 5.70695 9.28E 04 0.25000 22.827800 BF 3 0.08% 6.52% 93.40% 3.1273 0.0115 Thermal 0.00332 4.20E 02 5.70205 1.11E+00 0.25000 22.808200 PuM 3 He 0.09% 6.31% 93.60% 2.3442 0.0097 Thermal 0.00281 2.42E 01 5.70711 5.73E 04 0.25000 22.828500 BF 3 0.08% 6.52% 93.39% 3.4457 0.0116 Thermal 0.00355 4.21E 02 5.70172 6.83E 01 0.25000 22.806900 P Grafm60 PuBe 3 He 6.000E 01 77.17% 22.70% 0.12% 3.6860 0.3436 Thermal 2.92262 8.25E 04 0.33492 2.14E 08 4.66300 4.886000 BF 3 80.63% 19.28% 0.09% 5.3791 0.3058 Thermal 4.39602 2.04E 04 0.31196 3.03E 05 4.82844 0.064608 PuO 2 3 He 60.23% 39.52% 0.25% 2.1910 0.3188 Thermal 1.44572 1.19E 03 0.40757 1.66E 03 0.25000 1.630280 BF 3 48.61% 51.14% 0.26% 2.9106 0.2836 Thermal 1.55971 1.96E 04 0.42184 1.92E+00 0.25000 1.687360 PuM 3 He 55.61% 44.14% 0.25% 2.1863 0.3277 Thermal 1.36057 1.19E 03 0.44731 1.03E 03 0.25000 1.789230 BF 3 44.69% 55.05% 0.25% 3.1541 0.2928 Thermal 1.57080 2.05E 04 0.46043 1.19E+00 0.25000 1.841710 Graphite PuBe 3 He 1.600E+00 17.99% 38.35% 43.66% 3.1828 0.0820 Thermal 0.60394 3.14E 03 4.43816 7.00E 08 4.83 680 0.917582 BF 3 20.86% 39.13% 40.02% 4.9014 0.0849 Thermal 1.05546 5.96E 04 4.24761 9.67E 05 4.80740 0.883556 PuO 2 3 He 9.22% 42.09% 48.69% 2.0646 0.0749 Thermal 0.22191 5.64E 03 4.79695 1.25E 03 0.25000 19.187800 BF 3 6.58% 45.82% 47.60% 2.77 61 0.0787 Thermal 0.21871 1.00E 03 4.82149 1.47E+00 0.25000 19.285900 PuM 3 He 7.85% 42.74% 49.41% 2.1052 0.0747 Thermal 0.19716 6.05E 03 4.86441 7.70E 04 0.25000 19.457600 BF 3 5.83% 46.22% 47.95% 3.0472 0.0788 Thermal 0.21398 1.08E 03 4.85529 9.05 E 01 0.25000 19.421200 Kynar PuBe 3 He 1.760E+00 0.04% 1.14% 98.82% 3.3701 0.0077 Thermal 0.00139 8.74E 01 5.18475 1.34E 07 4.71912 1.098670 BF 3 0.05% 1.17% 98.78% 5.1528 0.0087 Thermal 0.00280 1.52E 01 5.18337 1.87E 04 4.68615 1.106110 PuO 2 3 He 0 .03% 1.14% 98.83% 2.1846 0.0080 Thermal 0.00065 1.07E+00 4.72034 5.67E 04 0.25 000 18.881300 BF 3 0.02% 1.17% 98.81% 2.9938 0.0091 Thermal 0.00070 1.85E 01 4.71982 6.92E 01 0.25000 18.879300 PuM 3 He 0.02% 1.15% 98.83% 2.2430 0.0081 Thermal 0.00062 1 .07E+00 4.71177 3.50E 04 0.25000 18.847100 BF 3 0.02% 1.17% 98.81% 3.2977 0.0092 Thermal 0.00074 1.86E 01 4.71116 4.27E 01 0.25000 18.844600 Lexan PuBe 3 He 1.200E+00 0.04% 1.01% 98.95% 3.4776 0.0080 Thermal 0.00141 9.05E 01 5.18708 5.22E 08 4.72149 1. 098610 BF 3 0.05% 1.04% 98.91% 5.2658 0.0091 Thermal 0.00292 1.57E 01 5.18566 7.26E 05 4.68396 1.107110 PuO 2 3 He 0.02% 1.02% 98.96% 2.2179 0.0083 Thermal 0.00063 1.13E+00 4.68603 1.29E 03 0.25 000 18.744100

PAGE 168

168 Table 7 1. Continued. Mat l Name SNM S ource Det Type ( g/c m 3 ) R Wgtd Fast Fraction R Wgtd Epitherm. Fraction R Wgtd Thermal Fraction G1 20 Fast n Energy ( MeV ) G21 41 Epitherm. n Energy ( MeV ) G42 47 Thermal n Energy ( MeV ) All R wgtd n Energy ( MeV ) Mat l a n R ( #/s ) Matl b n xmax ( cm ) Mat l c R ( #/s ) Matl d xmax ( cm ) Matl e n / xmax BF 3 0.02% 1.04% 98.94% 3.0469 0.0094 Thermal 0.00069 1.97E 01 4.68552 1.51E+00 0.25000 18.742100 PuM 3 He 0.02% 1.02% 98.96% 2.2809 0.0084 Thermal 0.00060 1.14E+00 4.68118 7.97E 04 0.25000 18.724700 BF 3 0.02% 1.05% 98.94% 3.3635 0.0096 Thermal 0.00073 1.99E 01 4.68057 9.34E 01 0.25000 18.722300 Nylon PuBe 3 He 1.140E+00 0.03% 0.84% 99.13% 3.5306 0.0072 Thermal 0.00104 9.64E 01 3.731 00 5.35E 08 5.1664 0 0.722166 BF 3 0.04% 0.86% 99.10% 5.3492 0 .0082 Thermal 0.00219 1.68E 01 3.73021 7.43E 05 5.12775 0.727456 PuO 2 3 He 0.02% 0.86% 99.13% 2.2459 0.0075 Thermal 0.00048 1.10E+00 3.23121 1.37E 03 0.25 000 12.924800 BF 3 0.01% 0.88% 99.11% 3.1136 0.0086 Thermal 0.00054 1.90E 01 3.23094 1.60E+00 0 .25000 12.923800 PuM 3 He 0.02% 0.86% 99.12% 2.3170 0.0076 Thermal 0.00046 1.09E+00 3.19813 8.44E 04 0.25000 12.792500 BF 3 0.01% 0.88% 99.11% 3.4426 0.0087 Thermal 0.00058 1.90E 01 3.19778 9.85E 01 0.25000 12.791100 OBrienDirt PuBe 3 He 1.700E+00 0 .55% 4.95% 94.50% 3.4342 0.0214 Thermal 0.01995 8.93E 02 5.69914 2.66E 08 3.54218 1.608930 BF 3 0.75% 5.14% 94.11% 5.1442 0.0235 Thermal 0.03971 1.56E 02 5.6843 0 3.77E 05 3.52004 1.614840 PuO 2 3 He 0.32% 4.97% 94.71% 2.1997 0.0213 Thermal 0.00816 1. 45E 01 5.70205 2.17E 04 0.25 000 22.808200 BF 3 0.25% 5.17% 94.58% 2.9227 0.0234 Thermal 0.00847 2.53E 02 5.70045 2.72E 01 0.25000 22.801800 PuM 3 He 0.28% 4.97% 94.74% 2.2257 0.0216 Thermal 0.00738 1.51E 01 5.70364 1.34E 04 0.25000 22.814500 BF 3 0.23% 5.18% 94.60% 3.1883 0.0238 Thermal 0.00850 2.63E 02 5.70076 1.68E 01 0.25000 22.803000 Paraffin PuBe 3 He 9.300E 01 0.02% 0.74% 99.24% 3.5587 0.0070 Thermal 0.00089 1.03E+00 3.23872 4.97E 08 5.14537 0.629443 BF 3 0.03% 0.76% 99.21% 5.3897 0.008 0 Thermal 0.00189 1.79E 01 3.23813 6.86E 05 5.11218 0.633415 PuO 2 3 He 0.02% 0.75% 99.23% 2.2615 0.0073 Thermal 0.00042 1.12E+00 2.73884 2.11E 03 0.25 000 10.955400 BF 3 0.01% 0.77% 99.22% 3.1511 0.0084 Thermal 0.00047 1.94E 01 2.73863 2.41E+00 0.250 00 10.954500 PuM 3 He 0.01% 0.76% 99.23% 2.3375 0.0074 Thermal 0.00040 1.12E+00 2.73805 1.30E 03 0.25000 10.952200 BF 3 0.01% 0.77% 99.21% 3.4866 0.0085 Thermal 0.00051 1.94E 01 2.73780 1.49E+00 0.25000 10.951200 Plexiglas PuBe 3 He 1.180E+00 0.03% 0.85% 99.12% 3.5194 0.0074 Thermal 0.00108 1.02E+00 4.23034 5.16E 08 4.70837 0.898473 BF 3 0.04% 0.87% 99.09% 5.3237 0.0084 Thermal 0.00226 1.77E 01 4.22943 7.17E 05 4.66999 0.905661 PuO 2 3 He 0.02% 0.86% 99.12% 2.2437 0.0077 Thermal 0.00049 1.19E+0 0 3.72154 1.17E 03 0.25 000 14.886200 BF 3 0.02% 0.88% 99.11% 3.0974 0.0088 Thermal 0.00055 2.07E 01 3.72120 1.38E+00 0.25000 14.884800 PuM 3 He 0.02% 0.86% 99.12% 2.3130 0.0078 Thermal 0.00047 1.19E+00 3.69752 7.25E 04 0.25000 14.790100 BF 3 0.0 2% 0.88% 99.11% 3.4231 0.0089 Thermal 0.00059 2.07E 01 3.69711 8.54E 01 0.25000 14.788500 Polyeth PuBe 3 He 9.400E 01 0.02% 0.74% 99.23% 3.5557 0.0070 Thermal 0.00090 1.03E+00 3.23864 4.98E 08 5.14848 0.629047 BF 3 0.03% 0.76% 99.20% 5.3854 0.0080 Ther mal 0.00191 1.79E 01 3.23805 6.89E 05 5.11527 0.633017 PuO 2 3 He 0.02% 0.76% 99.23% 2.2600 0.0073 Thermal 0.00042 1.13E+00 2.73887 2.08E 03 0.25 000 10.955500 BF 3 0.01% 0.78% 99.21% 3.1478 0.0084 Thermal 0.00047 1.96E 01 2.73866 2.38E+00 0.25000 10. 954700 PuM 3 He 0.01% 0.76% 99.23% 2.3356 0.0074 Thermal 0.00041 1.12E+00 2.73877 1.29E 03 0.25000 10.955100 BF 3 0.01% 0.78% 99.21% 3.4828 0.0085 Thermal 0.00052 1.95E 01 2.73853 1.47E+00 0.25000 10.954100 PVT PuBe 3 He 1.020E+00 0.03% 0.88% 99.09% 3.5115 0.0075 Thermal 0.00116 1.01E+00 4.69349 4.93E 08 5.15993 0.909605 BF 3 0.04% 0.90% 99.05% 5.3187 0.0086 Thermal 0.00243 1.75E 01 4.69238 6.83E 05 5.12509 0.915569 PuO 2 3 He 0.02% 0.89% 99.09% 2.2328 0.0078 Thermal 0.00052 1.20E+00 4.18845 1. 86E 03 0.25 000 16.753800 BF 3 0.02% 0.91% 99.07% 3.0877 0.0089 Thermal 0.00058 2.09E 01 4.18802 2.14E+00 0.25000 16.752100 PuM 3 He 0.02% 0.89% 99.09% 2.3004 0.0079 Thermal 0.00050 1.21E+00 4.18845 1.15E 03 0.25000 16.753800 BF 3 0.02% 0.91% 99. 07% 3.4116 0.0091 Thermal 0.00062 2.10E 01 4.18796 1.32E+00 0.25000 16.751900 Polyureth. PuBe 3 He 2.100E 02 78.21% 21.54% 0.25% 3.8604 0.3273 Thermal 3.08982 1.03E 03 5.44539 9.48E 09 9.00980 0.604385 BF 3 82.25% 17.59% 0.17% 5.5110 0.2940 Thermal 4.5 8430 2.66E 04 4.35278 1.31E 05 9.14228 0.476115 PuO 2 3 He 61.82% 37.73% 0.45% 2.2457 0.3084 Thermal 1.50467 1.51E 03 3.71034 1.69E 02 1.35503 2.738210 BF 3 50.77% 48.76% 0.47% 2.9725 0.2764 Thermal 1.64388 2.50E 04 3.76017 1.84E+01 1.51639 2.479690 PuM 3 He 57.65% 41.88% 0.47% 2.2276 0.3182 Thermal 1.41746 1.52E 03 4.02918 1.05E 02 1.35239 2.979310 BF 3 47.21% 52.31% 0.48% 3.2012 0.2869 Thermal 1.66145 2.61E 04 4.10109 1.14E+01 1.51341 2.709840

PAGE 169

169 Table 7 1. Continued. Mat l n ame SNM s ource Det t ype ( g/c m 3 ) R Wgtd f ast f raction R Wgtd e pitherm. f raction R Wgtd t hermal f raction G1 20 f ast n e nergy ( MeV ) G21 41 e pitherm. n e nergy ( MeV ) G42 47 t hermal n e nergy ( MeV ) All R wgtd n e nergy ( MeV ) Mat l a n R ( #/s ) Matl b n xmax ( cm ) Mat l c R ( #/s ) Matl d xmax ( cm ) Matl e n / xmax PVC PuBe 3 He 1.650E+00 0.20% 5.70% 94.09% 3.4441 0.0080 Thermal 0.00748 1.54E 01 4.19999 2.43E 08 3.88503 1.081070 BF 3 0.28% 5.83% 93.89% 5.2662 0.0091 Thermal 0.01537 2.67E 02 4.19438 3.50E 05 3.84539 1.0907 50 PuO 2 3 He 0.13% 5.74% 94.13% 2.2057 0.0083 Thermal 0.00343 1.87E 01 3.68833 1.15E 04 0.25 000 14.753300 BF 3 0.10% 5.87% 94.02% 3.0391 0.0094 Thermal 0.00374 3.26E 02 3.68661 1.45E 01 0.25000 14.746400 PuM 3 He 0.12% 5.75% 94.13% 2.2618 0.0084 Thermal 0.00326 1.89E 01 3.68788 7.10E 05 0.25000 14.751500 BF 3 0.10% 5.88% 94.02% 3.3476 0.0096 Thermal 0.00398 3.29E 02 3.68578 8.97E 02 0.25000 14.743100 RTVGel PuBe 3 He 9.000E 01 0.04% 0.99% 98.97% 3.5472 0.0080 Thermal 0.00145 9.09E 01 5.19022 3 .83E 08 5.06220 1.025290 BF 3 0.06% 1.01% 98.93% 5.3446 0.0092 Thermal 0.00306 1.58E 01 5.18875 5.34E 05 5.0178 0 1.034070 PuO 2 3 He 0.02% 1.00% 98.98% 2.2406 0.0083 Thermal 0.00063 1.16E+00 4.68821 1.54E 03 0.25 000 18.752900 BF 3 0.02% 1.02% 98. 96% 3.0844 0.0094 Thermal 0.00070 2.01E 01 4.68771 1.78E+00 0.25000 18.750800 PuM 3 He 0.02% 1.00% 98.98% 2.3042 0.0084 Thermal 0.00060 1.17E+00 4.68709 9.48E 04 0.25000 18.748400 BF 3 0.02% 1.02% 98.96% 3.4052 0.0096 Thermal 0.00074 2.03E 01 4.6865 0 1.10E+00 0.25000 18.746000 Teflon PuBe 3 He 2.200E+00 16.17% 66.08% 17.75% 3.1461 0.0579 Thermal 0.54692 3.03E 03 4.44650 2.25E 07 4.74946 0.936211 BF 3 17.91% 66.25% 15.85% 4.8766 0.0601 Thermal 0.91301 5.91E 04 4.3095 0 3.14E 04 4.72056 0.912922 PuO 2 3 He 9.84% 71.03% 19.13% 2.0739 0.0563 Thermal 0.24394 4.49E 03 4.57226 4.15E 04 0.25 000 18.289000 BF 3 6.77% 75.21% 18.03% 2.7951 0.0588 Thermal 0.23337 8.28E 04 4.60053 5.12E 01 0.25000 18.402100 PuM 3 He 8.71% 71.93% 19.36% 2.1134 0.0562 The rmal 0.22444 4.64E 03 4.60899 2.56E 04 0.25000 18.435900 BF 3 6.23% 75.65% 18.12% 3.0604 0.0589 Thermal 0.23528 8.62E 04 4.60395 3.16E 01 0.25000 18.415800 Tissue PuBe 3 He 1.070E+00 0.03% 0.82% 99.16% 3.5826 0.0073 Thermal 0.00106 1.01E+00 4.19676 4.2 1E 08 4.75574 0.882462 BF 3 0.04% 0.84% 99.12% 5.393 0 0.0083 Thermal 2.24E 03 1.76E 01 4.19581 5.89E 05 4.71657 0.889589 PuO 2 3 He 0.02% 0.83% 99.16% 2.2722 0.0076 Thermal 0.00048 1.18E+00 3.69693 9.31E 04 0.25 000 14.787700 BF 3 0.01% 0.85% 99.1 4% 3.1361 0.0086 Thermal 0.00054 2.05E 01 3.69657 1.11E+00 0.25000 14.786300 PuM 3 He 0.02% 0.83% 99.15% 2.3437 0.0077 Thermal 0.00046 1.17E+00 3.69195 5.75E 04 0.25000 14.767800 BF 3 0.01% 0.85% 99.14% 3.4668 0.0088 Thermal 0.00059 2.04E 01 3.69153 6.85E 01 0.25000 14.766100 Water PuBe 3 He 1.000E+00 0.03% 0.80% 99.18% 3.6003 0.0072 Thermal 0.00103 1.03E+00 4.19787 3.88E 08 4.76444 0.881083 BF 3 0.04% 0.81% 99.15% 5.4132 0.0083 Thermal 0.00220 1.79E 01 4.19693 5.44E 05 4.72693 0.887876 PuO 2 3 He 0.02% 0.81% 99.18% 2.2802 0.0075 Thermal 0.00047 1.20E+00 3.69804 9.21E 04 0.25 000 14.792200 BF 3 0.01% 0.82% 99.16% 3.1487 0.0086 Thermal 0.00053 2.08E 01 3.69769 1.10E+00 0.25000 14.790800 PuM 3 He 0.02% 0.81% 99.18% 2.3526 0.0077 Thermal 0.00 045 1.19E+00 3.69316 5.69E 04 0.25000 14.772600 BF 3 0.01% 0.83% 99.16% 3.4811 0.0087 Thermal 0.00057 2.07E 01 3.69274 6.78E 01 0.25000 14.771000 SS304 PuBe 3 He 7.920E+00 32.87% 63.75% 3.37% 2.5602 0.2356 Thermal 0.99184 1.34E 03 2.94343 3.46E 09 0.64 763 4.544900 BF 3 28.91% 68.06% 3.03% 4.3280 0.2202 Thermal 1.40099 2.59E 04 3.12347 5.14E 06 0.650412 4.802300 PuO 2 3 He 27.84% 68.68% 3.48% 1.8649 0.2347 Thermal 0.68047 1.53E 03 2.26783 4.38E 06 0.25 000 9.071330 BF 3 17.47% 79.18% 3.35% 2.461 2 0.2189 Thermal 0.60326 2.76E 04 2.52872 5.57E 03 0.25000 10.114900 PuM 3 He 25.80% 70.67% 3.53% 1.8482 0.2365 Thermal 0.64394 1.55E 03 2.27393 2.70E 06 0.25000 9.095710 BF 3 16.19% 80.45% 3.36% 2.6183 0.2213 Thermal 0.60190 2.83E 04 2.49671 3.44E 03 0.25000 9.986800 PuM 3 He 61.54% 38.46% 0.00% 2.2186 0.3634 Thermal 1.50513 1.48E 03 5.33811 1.37E 02 1.22228 4.367330 BF 3 50.77% 49.23% 0.00% 3.1880 0.3231 Thermal 1.77763 2.50E 04 5.31541 1.48E+01 1.36464 3.895110 C a d mium PuBe 3 He 8.650E+00 3 0.45% 69.51% 0.04% 2.9661 0.2984 Thermal 1.11051 1.11E 03 2.19943 9.37E 11 0.25000 8.797710 BF 3 28.44% 71.53% 0.03% 4.9749 0.2720 Thermal 1.60923 2.45E 04 2.37057 1.47E 07 0.25000 9.482230 PuO 2 3 He 26.21% 73.74% 0.05% 2.0470 0.2864 Thermal 0.74761 1.21E 03 1.38249 2.66E 06 0.25000 5.529980 BF 3 16.41% 83.55% 0.04% 2.8002 0.2617 Thermal 0.67806 2.44E 04 1.65450 2.99E 03 0.25000 6.618000 PuM 3 He 25.50% 74.45% 0.05% 2.0183 0.2914 Thermal 0.73160 1.20E 03 1.30432 1.64E 06 0.25000 5.217260 B F 3 16.20% 83.76% 0.05% 2.9902 0.2662 Thermal 0.70737 2.43E 04 1.54700 1.85E 03 0.25000 6.188010 He 3 PuBe 3 He 4.930E 04 81.05% 18.95% 0.00% 3.8667 0.3762 Thermal 3.20545 1.02E 03 5.87459 9.37E 09 10.56170 0.556215

PAGE 170

170 Table 7 1. Continued. Mat l n ame SNM s ource Det t ype ( g/c m 3 ) R Wgtd f ast f raction R Wgtd e pitherm. f raction R Wgtd t hermal f raction G1 20 f ast n e nergy ( MeV ) G21 41 e pitherm. n e nergy ( MeV ) G42 47 t hermal n e nergy ( MeV ) All R wgtd n e nergy ( MeV ) Mat l a n R ( #/s ) Matl b n xmax ( cm ) Mat l c R ( #/s ) Matl d xmax ( cm ) Matl e n / xmax BF 3 84.53% 15.47% 0.00% 5.5144 0.3338 Thermal 4.71302 2.65E 04 4.66789 1.28E 05 10.35600 0.450742 PuO 2 3 He 65.64% 34.36% 0.00% 2.2415 0.3533 Thermal 1.59267 1.47E 03 5.63637 2.21E 02 1.22448 4.603 080 BF 3 54.42% 45.58% 0.00% 2.9654 0.3117 Thermal 1.75574 2.41E 04 5.87844 2.40E+01 1.36713 4.299840 H afnium PuBe 3 He 1.331E+00 29.24% 70.76% 0.00% 2.6949 0.2814 Thermal 0.98705 1.17E 03 2.31382 1.75E 11 0.25000 9.255280 BF 3 25.15% 74.85% 0.00% 4.7674 0.2544 Thermal 1.38952 2.53E 04 2.53272 2.79E 08 0.25000 10.130900 PuO 2 3 He 29.35% 70.65% 0.00% 1.8879 0.2819 Thermal 0.75323 1.15E 03 1.50859 7.43E 07 0.25000 6.034370 BF 3 17.45% 82.55% 0.00% 2.6120 0.2541 Thermal 0.66561 2.24E 04 1.80417 8.72E 04 0.25000 7.216690 PuM 3 He 28.17% 71.83% 0.00% 1.8696 0.2845 Thermal 0.73101 1.14E 03 1.51379 4.59E 07 0.25000 6.055170 BF 3 16.92% 83.08% 0.00% 2.7940 0.2566 Thermal 0.68599 2.26E 04 1.79691 5.38E 04 0.25000 7.187620 Ni ckel PuBe 3 He 8.908E +00 23.80% 61.50% 14.70% 2.4595 0.1525 Thermal 0.67924 1.71E 03 3.62488 2.07E 09 0.62827 5.769640 BF 3 20.81% 65.47% 13.72% 4.2697 0.1517 Thermal 0.98801 3.19E 04 3.71366 3.11E 06 0.62761 5.917120 PuO 2 3 He 20.12% 64.73% 15.14% 1.7951 0.1539 Thermal 0.46082 2.14E 03 3.12151 3.01E 06 0.25000 12.486000 BF 3 12.34% 72.79% 14.87% 2.3658 0.1528 Thermal 0.40324 3.79E 04 3.19132 3.82E 03 0.25000 12.765200 PuM 3 He 19.13% 65.68% 15.19% 1.7699 0.1565 Thermal 0.44138 2.14E 03 3.13165 1.86E 06 0.25000 12 .526600 BF 3 11.73% 73.46% 14.81% 2.4937 0.1558 Thermal 0.40702 3.82E 04 3.18129 2.36E 03 0.25000 12.725100 In dium PuBe 3 He 7.310E+00 47.12% 52.88% 0.00% 2.8510 0.3438 Thermal 1.52514 8.95E 04 1.06503 6.39E 10 0.25743 4.137240 BF 3 44.96% 55.04% 0.00% 4.8714 0.3107 Thermal 2.36102 1.85E 04 1.17026 9.99E 07 0.25801 4.535640 PuO 2 3 He 40.90% 59.10% 0.00% 1.9553 0.3203 Thermal 0.98908 1.00E 03 0.28228 2.98E 06 0.25000 1.129120 BF 3 27.67% 72.33% 0.00% 2.6871 0.2901 Thermal 0.95322 1.79E 04 0.2 8184 3.35E 03 0.25000 1.127340 PuM 3 He 39.83% 60.17% 0.00% 1.9303 0.3324 Thermal 0.96893 9.90E 04 0.30801 1.84E 06 0.25000 1.232020 BF 3 27.23% 72.77% 0.00% 2.8682 0.3013 Thermal 1.00031 1.78E 04 0.30683 2.07E 03 0.25000 1.227310 a N eutron reactio n rate using group dependent neutron cross section ; b Location of maximum neutron flux in moderator material averaged over flux spe ctrum, measured from the entrance ; c G amma reaction rate using group dependent gamma cross section ; d Location of maximum ga mma flux in moderator material averaged over flux spectrum, measured from the entrance ; e Ratio of the maxima for neutrons and photons

PAGE 171

171 Table 7 2. The R obtained using real filter materials and Pu (frontal placed) neutron sources. Band Pu metal (#/s) 1 PuO 2 (#/s) 1 Rel. dif. (%) I 14.265 0.120 12.955 0 101 1 0.11 2 II 103.320 0.506 103.730 0 498 0.395 III 3932.000 4.325 3562.300 4.275 10.378 IV 2152.300 2.798 1973.400 2.565 9.066 Table 7 3. The R obtained using real filter ma terials for U (frontal placed) neutron sources. Band U metal (#/s) 1 UO 2 (#/s) 1 Rel. dif. (%) I 0.000251 0.000002 0.00816 0 00008 3147.7 II 0.002150 0.000011 0.07583 0 00038 3426.9 III 0.091790 0.000110 2.52420 0.00303 2649.9 IV 0.049320 0.000064 1.40150 0.00182 2741.5 Table 7 4. The R obtained using real filter materials for Pu (central placed) neutron sources. Band Pu metal (#/s) 1 t (h) PuO 2 (#/s) 1 t (h) Rel. dif. (%) I 4.00 2 0.01 8 3.43 3.67 6 0.01 7 3.53 8 861 II 13.294 0.03 2 3.61 13.331 0.03 2 3.62 0 278 III 200.4 00 0.120 3.87 181.02 0 0.10 9 4.23 10 706 IV 130.1 00 0.104 3.34 118.81 0 0.095 3.66 9 503 Table 7 5. The R obtained using real filter materials for U (central placed) neutron sources. Band U metal (#/s) 1 UO 2 (#/s) 1 Rel. dif. (%) I 0.0000840 0.0000004 0.00264 0.0000 1 30.43 8 II 0.0002 777 0.000000 7 0.01008 0.0000 2 35.300 III 0.00471 00 0.000002 8 0.12839 0.0000 7 26.256 IV 0.003 0000 0.0000024 0.08466 0.00007 27.242 Table 7 6. The R obtained using real fi lter materials for Pu Be and Surrogate WGPu (central placed) neutron sources. Band Pu Be (#/s) 1 Surrogate (#/s) 1 I 23.404 0.161 17.852 0.15 4 II 53.969 0.243 45.143 0.249 III 497.54 0 0.746 636.62 0 0.955 IV 358.75 0 0.646 415.62 0 0.748 Tab le 7 7. Relative Ratios of the R produced using SNM neutron sources*. SNM b3/b1 1 b3/b2 1 b4/b2 1 b4/b1 1 Pu m etal 50.081 0.250 15.074 0.045 9.786 0.031 32.51 3 0.169 PuO 2 49.246 0.251 13.57 9 0.04 1 8.912 0.029 32.322 0.171 U m etal 56.085 0.2 97 16.960 0.054 10.80 3 0.03 7 35.723 0.196 UO 2 48.63 3 0.248 12.737 0.03 7 8.39 9 0.026 32.068 0.1 70 Pu Be 21.25 9 0.17 9 9.21 9 0.055 6.647 0.04 2 15.32 9 0.133 Surrogate 35.66 1 0.360 14.102 0.09 9 9.20 7 0.067 23.281 0.242 *b = energy band

PAGE 172

172 Figure 7 1.Th e 3 He cross section, BUGLE 96, groups 1 47. A B Figure 7 2. Source moderator (polyethylene) block problem. A) Set up. B) Flux from fast neutron (9 th energy group). C) Flux from epithermal neutrons (30 th energy group). D) Flux from thermal neutrons (47 th energy group).

PAGE 173

173 C D Figure 7 2. Continued A Figure 7 3. The MCNP5 results for R in 3 He [less than 1% statistical relative error (1 ) for every value], as a function of energy group and the distance in polyethylene moderator spectrum. A) Vertical approach. B) horizontal approach.

PAGE 174

174 B Figure 7 3. Continued Figure 7 4. The MCNP5 results for R in 3 He as a function of energy group and the thickness of polyethylene moderator using SNM neutron sources [less than 1% statistical rela tive error (1 ) for every value].

PAGE 175

175 Figure 7 5. The SNM neutron spectra as a function of energy group [MCNP5 (1 ) calculations]. Figure 7 6. Normalized to maximum R curves in 3 He using SNM sources and HDPE moderator [MCNP5 calculations, less than 0.5% statistical re lative error (1 )].

PAGE 176

176 Figure 7 7. The normalized to maximum R curves for different distances of the first row of 3 He detectors compared with infinitely diluted 3 He gas in polyethylene moderator [MCNP5 calculations, less than 0.5% statistical relative erro r (1 )]. A B Figure 7 8. The 3 He (green) detector positions in moderator (blue) corresponding to upper region of the reaction rate curve. A) 2.5 cm HDPE/ 3 He detector/9.5 cm HDPE, B) 3 cm HDPE / 3 He detector/9 cm HDPE, C) 3.5 cm HDPE / 3 He detector/8.5 c m HDPE, D) 4 cm HDPE / 3 He detector/8 cm p HDPE.

PAGE 177

177 C D Figure 7 8. Continued Figure 7 9. The MCNP5 computed normalized leakage spectra of Pu metal and PuO 2 neutron

PAGE 178

178 Figure 7 10. The MCNP5 computed normalized l eakage spectra of U metal and UO 2 neutron Figure 7 11. Difference in detection of Pu metal and PuO 2 [MCNP5 calculations, less than 1% statistical relative error (1 )]

PAGE 179

179 Figure 7 12. Difference in detection of U metal and UO 2 [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 13. Difference in detection of Pu Be neutron source and [MCNP5 calculations, less than 1% statistical relative error (1 )]

PAGE 180

180 Figure 7 14. Capture of the four bands of spectra using ideal filters [MCNP5 calculations, less than 1% statistical relative error (1 )]

PAGE 181

181 Figure 7 15. Normalized to maximum Pu Be neutron source leakage spectrum (blue) and the detected spectrum using an ideal f ilter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 16. Normalized to maximum Pu metal neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% sta tistical relative error (1 )]

PAGE 182

182 Figure 7 17. Normalized to maximum PuO 2 neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 18. Normali zed to maximum U metal neutron source leakage spectrum (blue) and the ideal case detection processed results (red) [MCNP5 calculations, less than 1% statistical relative error (1 )]

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183 Figure 7 19. Normalized to maximum UO 2 neutron source leakage spectrum (blue) and the detected spectrum using an ideal filter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 an ideal filter (red) [MCNP5 calculations, less than 1% statistical relative error (1 )]

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184 Figure 7 21. Difference in detection of Pu metal and PuO 2 using ideal filter [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 22. Dif ference in detection of U metal and UO 2 using ideal filter [MCNP5 calculations, less than 1% statistical relative error (1 )]

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185 Figure 7 23. Difference in detection of PuBe and surrogate source using ideal filter [MCNP5 calculations, less than 1% statisti cal relative error (1 )] Figure 7 24. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) air [MCNP5 calculations, less than 1% statistical relative error (1 )].

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18 6 Figure 7 25. Modification of a flat spectrum profil e (blue) moderated by 6 cm (red) and 12 cm (green) polyurethane. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 26. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Dow foam. [MCNP5 ca lculations, less than 1% statistical relative error (1 )]

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187 Figure 7 27. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) helium gas. [MCNP5 calculations, less than 1% statistical relative error (1 )] A Figure 7 2 8. Modification of a flat spectrum profile (blue) moderated by Cadmium [MCNP5 calculations, less than 1% statistical relative error (1 )] A) 1 mm (red) and 2 mm (green) Cadmium. B) 6 cm (red) and 12 cm (green) Cadmium.

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188 B Figure 7 28. Continued. Figu re 7 29. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Tantalum. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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189 Figure 7 30. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Gold. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 31. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Indium. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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190 Figure 7 32. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Hafnium. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 33. Modification of a flat spectrum profil e (blue) moderated by 6 cm (red) and 12 cm (green) Copper. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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191 Figure 7 34. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Iron. [MCNP5 calculations less than 1% statistical relative error (1 )] Figure 7 35. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Cesium. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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192 Figure 7 36. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Iodine. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 37. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Silver. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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193 Figure 7 38. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Stainless Steel. [MCNP5 calculations, less than 1% statistical relative err or (1 )] Figure 7 39. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Nickel. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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194 Figure 7 40. Modification of a flat spectrum profile (blue) mode rated by 6 cm (red) and 12 cm (green) Lead. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 41. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Vanadium. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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195 Figure 7 42. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Cobalt. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 43. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Manganese. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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196 Figure 7 44. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Graphit e. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 45. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) BeO. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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197 Figure 7 46. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Teflon. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 47. Modification of a flat spectrum profile (blue) moderated by 6 cm (red ) and 12 cm (green) Aluminum. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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198 Figure 7 48. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) Celotex. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 49. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) ABS fm160. [MCNP5 calculations, less than 1% statistical relative error (1 )]

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199 Figure 7 50. Modification of a flat spectrum pro file (blue) moderated by 6 cm (red) and 12 cm (green) Concrete. [MCNP5 calculations, less than 1% statistical relative error (1 )] Figure 7 51. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) PVC. [MCNP5 calculat ions, less than 1% statistical relative error (1 )]

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200 A B Figure 7 52. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green). [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Polyethylene. B) Polyet hylene with thermal neutrons removed

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201 A B Figure 7 53. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Paraffin. B) Paraffin with thermal neutr ons removed.

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202 A B Figure 7 54. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Kynar. B) Kynar with thermal neutrons removed.

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203 A B Figure 7 55 Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Nylon. B) Nylon with thermal neutrons removed.

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204 A B Figure 7 56. Modification of a flat spect rum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) PVT. B) PVT with thermal neutrons removed.

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205 A B Figure 7 57. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Lexan. B) Lexan with thermal neutrons removed.

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206 A B Figure 7 58. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MC NP5 calculations, less than 1% statistical relative error (1 )] A) ABS Plastic. B) ABS Plastic with thermal neutrons removed.

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207 A B Figure 7 59. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistical relative error (1 )] A) Plexiglas. B) Plexiglas with thermal neutrons removed.

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208 A B Figure 7 60. Modification of a flat spectrum profile (blue) moderated by 6 cm (red) and 12 cm (green) [MCNP5 calculations, less than 1% statistic al relative error (1 )] A) Asphalt. B) Asphalt with thermal neutrons removed.

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209 Figure 7 61. Targeting Energy Band IV by using 3 cm Cd and 1 cm Hf filter materials. Figure 7 62. Targeting Energy Band III by using 1 cm In and 0.5 cm Ta filter materials.

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210 Figure 7 63. Targeting Energy Band II by using 16 cm Concrete and 1 cm Hf filter materials. Figure 7 64. Targeting Energy Band I by using 13 cm Asphalt and 1 mm Cd filter materials.

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211 Figure 7 65. Block I: 13 cm Asphalt, 1 mm Cd filter materials, 12 cm HDPE moderator. Figure 7 66. Block II: 16 cm Concrete, 1 cm Hf filter materials, 12 cm HDPE. Figure 7 67. Block III: 1 cm In and 0.5 cm Ta filter materials, 12 cm HDPE. Figure 7 68. Block IV: 3 cm Cd, 1 cm Hf filter materials, 12 cm HDPE.

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212 Figure 7 69. Relative difference between Pu metal and PuO 2 generated reaction rates using ideal filtering (red line) and real materials (blue line) frontal source, and real materials (green line) central source. Figure 7 70. Relative difference between U met al and UO 2 generated reaction rates using ideal filtering (red line) and real materials (blue line) frontal source, and real materials (green line) central source.

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213 Figure 7 71. Detection device Assembly.

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214 CHAPTER 8 CONCLUSIONS AND FUTURE WORK This thesis describes the research efforts t oward design ing a parcel screening system for SNM where the source magnitude and spectrum must b e accurately known and verified. Our research goals are reviewed here to highlight the accomplished tasks and the possi bilities for future work. Developing a procedure for total source construction for SNM computational modeling This premier task necessary for deterministic calculation of the total leakage, was accomplished and was successfully applied for the Pu Be neu tron source characterization and SNM assessments. Adjoint coupling approach validation with application for reaction rate calculations using forward and adjoint S N and forward Monte Carlo. C omparative results of the three computational procedures were pre sented for an isotropic volumetric source folded with a scalar adjoint function. Design of a viable model for Pu Be neutron source capsule for complete characterization of Pu Be leakage spectrum using deterministic and Monte Carlo computational techniqu es and experimental validation of the model. We successfully profiled the intrinsic and induced radiation from a Pu Be source using deterministic discrete ordinates transport (PENTRAN code), Monte Carlo transport (MCNP5 code), and experimental measurement s. We profiled both in the laboratory and com putationally 1 Ci Pu Be source issued to the University of Florida by the U S Atomic Energy Commission in 1971. Reasonable agreement was achieved be tween all methods to profile the neutron and gamma leakage radiation. We also determined that in this application, the use of the BUGLE 96 multigroup library in 3 D deterministic computations compared reasonably well with MCNP5 Monte Carlo results for shie lding calculations, and also for determination of criticality eigenvalues to evaluate total leakage from the Pu Be capsule.

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215 Our innovative methodology proposed for Pu Be source assessment consists in the following steps: estimation of the neutron emission on the shipping date; evaluation of the Pu age; estimation of the effective dose at the shipping date; laboratory validation of the models; evaluation of the leakage. This procedure is suitable for complete characterization of a Pu Be neutron source based on 3 D radiation transport computations, using Monte Carlo and/or de terministic methods. by using ORIGEN ARP from the SCALE5 .1 package t he intrinsic (input) source spectrum may be obtained. Generation, design and complete characterization of SNM neutron sources using deterministic and Monte Carlo computational techniques. This task was accomplished using PENTRAN S N deterministic and MCNP5 Monte Carlo collected, is a n intended initiative related to this part of the research. Design of a shield for Pu Be neutron source capsule to emulate WGPu neutron spectrum. We generated a SNM WGPu metal neutron source by a unique shield design that transforms the complex neutron sp ectrum (4.6 MeV average energy) from Pu Be neutron s ource to nearly exactly the neutron signature leaking from a sphere of WGPu metal (2.11 MeV average energy). This patented invention was experimentally validated and will enable testing for detection of a significant quantity of weapons plutonium without the expense or risk of testing detector components with real full size mass materials. Detection of SNM.

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216 Last part of this research work employed an ample moderator study in support of detection assembly design; we extended our study of the shielding materials developed for designing the Surrogate Shielded Source to over thirty moderator materials. Our analysis of the energy filtering effect in high density polyethylene, with the new approach proposed her e of four energy bands, enabled us to establish the practical limits of 3 He spectroscopy by using ideal filters We have demonstrated that the spectral sensitivity of neutron spectroscopy can be assessed using computational transport studies and we finaliz ed the moderator study with the analysis of candidate materials capable of replacing the ideal filters. Corroborating the entire research work presented on this thesis we recommend a design for a neutron detector array able to resolve the spectra from SNM neutron sources of interest (metal and oxide), to the greatest extent permissible, based on four energy bands separation in HDPE, using 3 He detectors and specific filtering materials. Building the propose d neutron detector assembly is a possibility for a future work. However, a carefully analysis of the background effect on the correctitude of the fingerprints of the SNM neutron sources, particularly for Uranium neutron sources, is strongly recommended. Study of the environment effect on the SNM detection be another extremely useful study that can continue our presented work. Different geometry perturbation, depending on the application of the detection device it might be also necessary. Many other applications can get us e of part of the study presented in this thesis in different ways; the leakage of SNM, the moderator study, the filter materials can find a future work application just by themselves.

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217 LIST OF REFERENCES and Photon Multiplicities for Nuclear Transactions of the American Nuclear Society, 90 865 866, (2007). Sources Using the Liquid Scintillator BC Transactions of the American Nuclear Society, 90 457 458, (2007). Transactions of t he American Nuclear Society, 90 874 875, (2007). 4. G. GHITA G. SJODEN, and J. B ACIAK M ethodology for E xperimental and 3 D C omputational R adiation T ransport A ssessment of Pu Be N eutron S ources Nuclear Technology 159 321 322, (2007). 5. G. SJODEN Deterministic Adjoint Transport Application for He 3 Neutron Detector Design Annals of Nuclear Energy 29 1055 1071, ( 2002 ) 6. G. SJODEN and A. HAGHIGHAT PENTRAN A 3 D Cartesian Parallel S N Code with Angular, Energy, and Spatial Decomposition Proceedings of the Joint International Conference on Mathematical Methods and Supercomputing for Nuclear Applications p 553, Saratoga Springs, NY, October 5 10, 1997. 7. G. GHITA G. SJODEN and J. B ACIAK M ethodology for E xperimental and 3 D C omput ational R adiation T ransport A ssessment of Pu Be N eutron S ources Nuclear Technology 159 319 331, (2007). 8. G. GHITA G. SJODEN and J. B ACIAK Comparison of 3 D Deterministic Parallel and Monte Carlo Transport Computations for Special Nuclear Materia ls Assessments Proceedings of PHYSOR 2006, Advances in Nuclear Analysis and Simulation Vancouver, BC, Canada, September 10 14, 2006. 9. G. GHITA G. SJODEN, J. B ACIAK and S. WALKER, Method and Apparatus for Emulating a Neutron Signature, UF Invention Disclosure #12609 July 16, 2007, US Patent Serial No. 61/027988 US Provisional Patent Application Docket No. UF 606P February 12, 2008. 10 G. GHITA G. SJODEN, and J. B ACIAK WGPu Neutron Leakage Source Nuclear Technology, 2008. 11 G. GHITA G. SJODEN, J. B ACIAK S. WALKER and S. CORNELISON, n Source for WGPu Derived from a Spectrum Proceedings of SPIE 2008 D ef en s e and Security Symposium 6945 O rlando, Fl, March 16 21, 2008

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218 12 G. GHITA, G.E. SJODEN, J. BACIAK, and N. HUANG 3D Computational and Experimental Radiation Transport Assessments of Pu Be Sources and Graded Moderators for Parcel Screening Proceedi ngs of SPIE, International Society for Optical Engineering, Defence and Security Symposium 6213 I01 I015 Orlando, Florida, April 17 21 (2006). 13 G. GHITA G. SJODEN, and J. Proportional Detectors Optimized b Nuclear Technology Journal, 2008. A General Monte Carlo N Particle Transport Code, Version 5X 5 TEAM MCNP5 LA UR 03 1987, Los Alamos Natio nal Laboratory, Los Alamos, N M, ( 2003 ) Standardized Com puter Analyses for Licensing Evaluation Version 5 (SCALE5) B OWMAN Oak Ridge National Laboratory, Lockheed Martin Energy Research Corp, ( 2004 ) 16. G. F. KNOLL Radiation Detection and Measurement, 3 rd Edition John Wiley & Sons New York, NY (2000). 17. C. T. NGUYEN, 239 content, isotopic composition and age of plutonium in Pu Be neutron sources by gamma spectrometry Nuclear Instruments and Methods in Physics Research B, 251 227 236, (2006). 18. C. T. NGUYEN, J. BAGI, and L. LAKOSI Nuclear Instruments and Methods in Physics Research B, 246 409 416, (2007). 19. C. T. NGUYEN, J. BAGI, and L. LAKOSI position and Pu content of PuBe sources by neutron coincidence technique Nuclear Instruments and Methods in Physics Research B, 262 75 80, (2007). 20. M. E. A NDERSON Increases in Neutron Yield of 239Pu Be( ) Sources II Nuclear Technology 52 ( 19 81 ) 21. A. C. BEARD et al A radiation barrier alloy for long term storage of Special Nuclear Materials: definition and preliminary assessment Nuclear Technology 120 19 34, ( 1997 ) splay MCNP Input Transactions of the American Nuclear Society 77 223, (1997) Californium 252 neutron sources Applied Radiation and Isotopes 48 1563 1566, (1997). 24 Prod uction, di stribution and applications of C alifornium 252 neutron sources Applied Radiation and Isotopes 53 785 792, (2000).

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219 25. M. KATAGIRI, K. SAKASAI, M. MATSUBAYASHI, and T. KOJIMA ray discrimination characteristics of novel neutron scintillators Nuclear Instruments and Methods in Physics Research A 529 317 320, (2004). 26. S. NORMAND, B. MOUANDA, S. HAAN, and M. Nuclear Instrum ents and Methods in Physics Research A 484 342 350, (2002). 27. V. S. CORNELISON, G. SJODEN, and G. GHITA, 3 Neutron Detectors Under Varying Gas Pressures Using MCNP5 Transactions of the American Nuclear Society 96 Boston, MA, June 24 28, ( 2007 ). 28. R. L. BRAMBLETT, R. I. EWING, and T. W. B Nuclear Instruments and Methods, 9 1, (1960). Nuclear Instruments and Methods in Physics Research A, 476 21 25, (2002). Nuclear Instruments and Methods in Physics Research A, 476 26 30, (2002). Nuclear Instruments and Methods in Physics Research A, 476 (2002). sp Nuclear Instruments and Methods in Physics Research A, 476 270 272 (2002). Radiation Protection Dosimetry, 70 (1997). 34. S. Spherical neutron detector for space neutron measurement Nuclear Instruments and Methods in Physics Research A, 422 (1999). 35. E. E. LEWIS and W. F. M ILLER Computational Methods of Neutron Transport pp. 42 47, American Nuclear So ciety Publish ing Co., LaGrange Park, IL ( 1993 ) 36. J. DUDERSTADT and L. HAMILTON Nuclear Reactor Analysis pp. 111 114, John Wiley, New York, ( 1976 ). 37. G. M. A MDAHL "Validity of the single processor approach to achieving large scale computing capabil ities," Proceedings of AFIPS Conference Atlantic City, N.J., April 18 20, 1967

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220 38. A. HAGHIGHAT G. E. SJODEN and V. K UCUBOYACI Unique Numerics for Simulation of the Kobayashi Benchmarks Special Issue, Progress in Nuclea r Energy Journal, 3D Radiation Transport Benchmarks for Simple Geometries with Void Region 39 2, ( 2001 ) 39. G. LONGONI, A. HAGHIGHAT, CE YI and G. E. SJODEN Benchmarking of PENTRAN SS N parallel transport code and FAST preconditioning algorithm using the VENUS 2 MOX Fueled Benchmark Problem Journal of Testing and Evaluation (ASTM International) 3 7, ( 2006 ) 40. M. GHITA, G. SJODEN, and G. GHITA Steady State Neutron Transport Benchmark Problems Joint Inte rnational Topical Meeting on Mathematics & Computation and Supercomputing in Nuclear Applications ), Monterey, CA, April 15 19 2007. 41. G. E. SJODEN Performance of PENTRAN Using a Heterogeneous Cluster for Selected Medical Physics Problems Transaction s of the American Nuclear Society 90 ( 2004 ) A Nuclear Cross Section Databook H. M. FISHER, LA 11711 M, Los Alamos National Laboratory, Los Alamos NM ( 1989 ) BUGLE 96: A Revised Multi group Cross Section Library for LWR Applications Based o n ENDF/B VI Release 3 J. WHITE D. I NGER S OLL C. S LATER and R. R OUSSIN DLC 185, Oak Ridge National Laboratory, Oak Ridge, T N ( 1996 ) 44. Tecplot, 2007, http://www.tecplot.com June 2008. 45. T. FREEMAN and C. P HILLIPS, Parallel Numerical Algorithm Prentice Hall, New York, (1992). Dose Modeling of Plutonium Beryllium Source unpacking Operations D.E. K ORNREICH LA UR 99 1429, Los Alamos National Laboratory, Los Alamos NM ( 1999 ) 47. G. E. SJODEN Compil ation of NCRP ICRP, and ANSI Flux to Dose conversions for Neutron and Photon dosimetry for the BUGLE 96 Library Private Communication, ( 2005 ) MCNP: Criticality Safety Benchmark Problems LA 12415, Los Alamos National Laboratory J.C.WAGNER, J.E. SISOLAK and G.W. McKINNEY, Los Alamos, N M, ( 1992 ) 49. Nuclear Data Evaluation Lab Korea Atomic Energy Research Institute 2000 http://atom.kaeri.re.kr/ June 2008.

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221 BIOGRAPHICAL SKETCH Gabriel Mihail Ghita wa Physics profile, in Braila. After serving for nine months in Romanian Army, a mandatory service at that time, he enrolled in Physics Department at University of Bucharest i n 1987. Upon graduation with an Engineering Physics Diploma, in 1992, he enjoyed a short experience as high school teacher. Then he started an industrial career as Physicist, Head of Nondestructive Testing Laboratory, and Quality Director in two important Romanian companies specialized in oil industry refineries. During 2002 2004, he completed the Master Degree in Physics at Cen tral Michigan University, as a member of the x ray diffraction group, gaining essential skills in crystallography physics In Augu st 2004, Nuclear and Radiological Engineering Department at University of Florida offered him admission to the Ph.D. Program in Nuclear Engineering and appointed him as a University of Florida Alumni Fellow for four years Here Gabriel was a m ember of UF T ransport Theory Group joining also Conversion Project Team which performed the transition from High Enriched Uranium (HEU) to Low Enriched Uranium (LEU) for the UF Training Reactor (UFTR) Gabriel was selected by a special NRE comm ittee to attend the Fred erick Jo liot Otto Hahn (FJOH) Summer School of Nuclear Engineering held in Germany in September 2007. In recognition of his outstanding scholastic and professional achievements, the NRE Department awarded him James E. Swander Memorial Sc h olarship in Decem ber, 2007. He is married to Monica and has a daughter, Gabriela Livia.