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Measurement of Flexible Wing Deformations in Flight


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1 MEASUREMENT OF FLEXIBLE WING DEFORMATIONS IN FLIGHT By JAMES D. DAVIS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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2 This thesis is dedicated to my family w ho has supported me as much as possible through the years. To my Father for teaching me how to work. To my mother for teaching me patients and persistence. To my sister for teaching me survival and compassion. And to the rest of my family for all the life lessons offered through the years. I also dedicate this thesis to all the teach ers, instructors, prof essors, classmates, and coworkers I have had the honor to know and work with. For all of the lessons, challenges, and clarifications. I would not be where I am without any of you. Thank you.

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3 ACKNOWLEDGMENTS This work was made possible by the US Ai r force civil service internship program PALACE Acquire thru which I attended the Univers ity of Florida. Also, I thank the professors at the University of Florida specifically Dr. Pe ter Ifju for advising me through the one calendar year I was allotted to complete the required course work. I woul d also like to acknowledge the USAF AFRL/MN for supporting the completion of this thesis in a timely manor. In addition, I thank every one on the UF MAV team for all the help and support. I would also like to recognize my family for he lping me anyway possible. Finally I thank my dog, Adian, who I rescued from the Alachua County Humane Society, for the badly needed distractions and unconditional love Hang in there little buddy, I pr omise things will get better.

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4 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................3 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 ABSTRACT....................................................................................................................... ............10 CHAPTER 1 INTRODUCTION..................................................................................................................12 1.1 Challenges and Developments.....................................................................................12 1.2 Motivation and Overview............................................................................................15 2 LITERATURE SURVEY.......................................................................................................17 2.1 Research.......................................................................................................................17 2.2 Deformation Measurement Methods...........................................................................18 2.2.1 Visual Image Correlation...................................................................................18 2.2.2 Video Model Deformation.................................................................................18 2.2.3 Projection Moir Interferometry........................................................................19 2.3 Flight Test Instrumentation..........................................................................................20 3 SYSTEM LAYOUT...............................................................................................................22 3.1 Platform....................................................................................................................... .22 3.2 Camera.........................................................................................................................22 3.3 Tracking Points............................................................................................................24 3.4 Angle of Attack Indicator............................................................................................25 3.5 Deformation Measurement Calibration.......................................................................25 3.6 AOA Indicator calibration...........................................................................................29 4 FLIGHT TEST.................................................................................................................... ....37 4.1 Flight Test Setup..........................................................................................................37 4.2 Processing Results.......................................................................................................38 4.3 Observations................................................................................................................39 4.4 Discussion of Deformations and Plots.........................................................................40 5 CONCLUSIONS AND RE COMENDATIONS.....................................................................58 5.1 Discussion of Error and Sensitivity Analysis..............................................................58 5.2 Recommendations........................................................................................................59

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5 APPENDIX: CALIBRATION OF CCD CAMERA.....................................................................66 LIST OF REFERENCES............................................................................................................. ..68 BIOGRAPHICAL SKETCH.........................................................................................................71

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6 LIST OF TABLES Table page 4-1. Calculated airspeed and AOA of le vel passes with error estimations....................................42

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7 LIST OF FIGURES Figure page 3-1. 16 Wingspan second generation MMALV..........................................................................30 3-2. Various Planform Designs in use by UF MA V team: Rigid (A), Batten Reinforced (B), Perimeter Reinforced (C), and Floating Angled (D).........................................................30 3-3. Directional convention utilized........................................................................................... ...31 3-4. Color CCD snake type camera...............................................................................................31 3-5. Camera location and mounting.............................................................................................. .31 3-6. The two tracking point patterns investigat ed, suspected maximum deflection (A), and ease of processing (B)........................................................................................................32 3-7. The AOA indicator and its mounting.....................................................................................32 3-8. VIC system installation and setup........................................................................................ .33 3-9. The numbered order of the tracking points and the location of each centroid......................33 3-10. Example of image of MMALV through VIC camera with VIC data field overlaid, this is the standard output from the VIC software....................................................................34 3-11. Image of MMALV through VIC camer a with tracking points installed.............................34 3-13. A VIC data set before and after alignment...........................................................................36 3-14. Image of the AOA indicator from SPOT camera and processed results..............................36 3-15. AOA indicator calibration curve..........................................................................................36 4-1. Flight test setup......................................................................................................... ..............42 4-2. Topographic representation of the wing in an undeformed state...........................................42 4-3. Chordwise sectional lines................................................................................................ ......43 4-4. Cross sectional view of wing at each corresponding sectional line......................................43 4-5. Cross sectional plots of flight-test SPO T data for pass 1: estimated 20.8 m/s and 4 AOA............................................................................................................................ .......44 4-6. Cross sectional plots of flight-test SPO T data for pass 2: estimated 26.9 m/s and 4 AOA............................................................................................................................ .......44

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84-7. Cross sectional plots of flight-test SPO T data for pass 3: estimated 19.9 m/s and 3 AOA............................................................................................................................ .......45 4-8. Cross sectional plots of flight-test SPO T data for pass 4: estimated 22.9 m/s and 4 AOA............................................................................................................................ .......45 4-9. Cross sectional plots of flight-test SPOT data for high AOA 1: 18 AOA and unknown airspeed....................................................................................................................... .......46 4-10. Cross sectional plot s of flight-test SPOT data for high AOA 2: 20 AOA and unknown airspeed..............................................................................................................46 4-11. Cross sectional plot s of flight-test SPOT data for high AOA 3: 24 AOA and unknown airspeed..............................................................................................................47 4-12. Cross sectional plots of flight-test SPOT data for negative AOA: -19 AOA and unknown airspeed..............................................................................................................47 4-13. Topographic plots of flight-test SPOT da ta for pass 1: estimated 20.8 m/s and 4 AOA............................................................................................................................ .......48 4-14. Topographic plots of wind tunnel VIC data for 20 m/s and 4 AOA...................................48 4-15. Topographic plots of flight -test SPOT data for pass 2: estimated 26.9 m/s and 4 AOA....49 4-16. Topographic plots of wind tunnel VIC data for 26 m/s and 4 AOA...................................49 4-17. Topographic plots of flight -test SPOT data for pass 3: estimated 19.9 m/s and 3 AOA....50 4-18. Topographic plots of wind tunnel VIC data for 20 m/s and 4 AOA...................................50 4-19. Topographic plots of flight -test SPOT data for pass 4: estimated 22.9 m/s and 4 AOA....51 4-20. Topographic plots of wind tunnel VIC data for 23 m/s and 4 AOA...................................51 4-21. Topographic plots of flight-test SPO T data for high AOA 1: 18 AOA and unknown airspeed....................................................................................................................... .......52 4-22. Topographic plots of flight-test SPO T data for high AOA 2: 20 AOA and unknown airspeed....................................................................................................................... .......52 4-23. Topographic plots of flight-test SPO T data for high AOA 3: 24 AOA and unknown airspeed....................................................................................................................... .......53 4-24. Topographic plots of flight-test SPOT data for negative AOA: -19 AOA and unknown airspeed..............................................................................................................53 4-25. Wind tunnel VIC data for 13 m/s and -10 AOA.................................................................54

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94-26. Wind tunnel VIC data for 13 m/s and -5 AOA...................................................................54 4-27. Wind tunnel VIC data for 13 m/s and 0 AOA....................................................................54 4-28. Wind tunnel VIC data for 13 m/s and 3 AOA....................................................................55 4-29. Wind tunnel VIC data for 13 m/s and 5 AOA....................................................................55 4-31. Wind tunnel VIC data for 13 m/s and 12 AOA..................................................................56 4-32. Wind tunnel VIC data for 13 m/s and 15 AOA..................................................................56 4-33. Amount of deformation data for the ha rd left turn 7 AOA unknown side slip and unknown airspeed..............................................................................................................57 4-34. Amount of deformation data for the ha rd right turn 9 AOA unknown side slip and unknown airspeed..............................................................................................................57 5-1. Example of thresholded image, taken from flight test pass1..................................................61 5-2. Image captured and processed for pass 1...............................................................................61 5-3. Pass 1 Cross section deformation with tolerance bounds and errorbars.................................61 5-4. Pass 2 Cross section deformation with tolerance bounds and errorbars.................................62 5-5. Pass 3 Cross section deformation with tolerance bounds and errorbars.................................62 5-6. Pass 4 Cross section deformation with tolerance bounds and errorbars.................................63 5-7. High AOA 1 Cross section deformation with tolerance bounds and errorbars......................63 5-8. High AOA 2 Cross section deformation with tolerance bounds and errorbars......................64 5-9. High AOA 3 Cross section deformation with tolerance bounds and errorbars......................64 5-10. Negative AOA Cross section deformation with tolerance bounds a....................................65 A-1. AOA indicator calibration curve for first run with CCD camera..........................................66 A-2. Tracking point calibration curves for first run with CCD camera........................................66 A-3. Image taken with CCD camera during the calibration process.............................................67 A-4. Image taken with CCD camera during th e calibration process with the AOA indicator installed...................................................................................................................... ........67

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10 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MEASUREMENT OF FLEXIBLE WING DEFORMATIONS IN FLIGHT By James D Davis December 2006 Chair: Peter Ifju Major: Mechanic al Engineering Adverse flying conditions such as wind gusts are an unavoidable reality and a concern for aircraft of any scale where out door flight is mission critical. In the realm of Micro Aerial Vehicles (MAVs), where relative low mass inertias and low flight speeds are prevalent almost by definition, handling characteristics in such typical conditions are of primary concern. In the interest of keeping the craft volume minimal and autopilot simp le these characteristics should be as inherent and unsupplemented as possible. With these realizations and in spiration from sailing technology, the University of Florida developed a thin significantly cambered flexib le membrane wing. The flexible wing design passively adapts to the changing f light conditions in such a way that it results in more stable and manageable flight characteristics. The behavior and characteristics of the flexible wing have been studied in theories, computations, and wind tunnels all of which ar e limited to steady or quasi steady state conditions. The re search presented in this thesis is an initial i nvestigation into developing a system to monitor and measure the de formational behavior of the flexible wing in flight as it responds to real worl d aerodynamic and inertial conditions.

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11 The method proposed and investigated is one of videogrammetry. A camera was placed on the tail of the aircraft oriented so that the wi ng was in the view. The wing was outfitted with tracking points and an angle of attack (AOA) i ndicator. The system was termed single point optical tracking (SPOT). SPOT wa s calibrated using the University of Floridas low speed, low turbulence wind tunnel and the visual image correlation (V IC) measurement system. A comparison of in flight deformation measuremen ts to wind tunnel measurements at a similar angle and airspeed was made with agreeable resu lts demonstrating the effectiveness and viability of the system. An error and se nsitivity analysis was performed.

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12 CHAPTER 1 INTRODUCTION 1.1 Challenges and Developments Adverse flying conditions such as wind gusts are an unavoidable reality and a concern for aircraft of any scale where out door flight is mission critical. In the realm of Micro Aerial Vehicles (MAVs), where relative low mass inertias and low flight speeds are prevalent almost by definition, handling characteristics in such typical conditions ar e of primary concern. Micro Aerial Vehicles are defined as any aircraft with a maximum dime nsion of less than 15cm [1]. With the given maximum dimension, and the fact pi lots do not come that small, MAVs are in the realm of Unmanned Aeri al Vehicles (UAVs). For micro scale aircraft typical flight sp eeds range between 15 to 25 mph, and on an average day gusts can vary the wind speed by more than 10 mph. These average conditions result in sudden and significant changes of not only airspeed but also angle of attack (AOA) and sideslip. For conventional rigid wing designs, these changes in flight conditions result in a proportional variation in the lift produced over a correspondi ng short period of time [2]. The combination of low inertias and considerable change s in lift can result in a rapid divergence from the intended flight path if left uncorrected. Stability and controllability are not the only problematic concerns faced by MAVs. The dimensions and flight speeds place the aircra ft in an aerodynamic region referred to as low Reynolds number (LRN) which is between 60,000 and 150,000. Laminar boundary layer separation is a common occurrence within this range re sulting in a drop in aerodynamic efficiency for conventional airfoils [2]. Early in the development of MAV scale ai rcraft, emphasis was pl aced on the latter problem with designs that tried to maximize aer odynamic efficiency such as rigid blended wing-

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13 fuselage and pure flying wings. These conventio nal designs proved to ha ve undesirable flight characteristics at these scal es, requiring control supplementa tion for even seasoned remote control (RC) pilots [2]. The primary mission of many UAV type craft is reconnaissance. The details of this mission could vary from bomb damage assessment to search and rescue to surveillance in a host of uninviting environments that would prove too close quartered or dangerous for larger manned aircraft. The list of missions and environments is quite extensive but al ways requires practicality and effectiveness from the platform selected to do the job. The mission and environmental niche that MAVs are slated to f ill are among the most demanding, with the ultimate goal being operable and deployable by a sing le person through an urban canyon and inside buildings while collecting data. For a MAV to meet the ultimate goal in a pract ical manner it is required to be flown by a remote pilot with minimal training or autonomousl y, both of which necessita te that the platform have reliable and benevolent flight characteristics [3]. In the interest of keeping the craft volume minimal and autopilot simple, these characteris tics should be as inherent and unsupplemented as possible. With these realizations and in spiration from sailing technology, the University of Florida MAV team implemented an alternate design op tion, a thin significantly cambered flexible membrane wing [4-6]. Previous work done by Was zak et al.[6], Shyy et al. [7-11], and Jenkins et al. [12] showed that a wing of this design would have more favorable aerodynamic performance in adverse flight conditions. The flexible wing design passively adapts to th e changing flight conditions in such a way it results in more stable and manageable flight char acteristics. This adaptation results in significant

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14 changes in wing geometry such as the dihedral wing twist, maximum camber, and chord wise location of maximum camber [6]. National Advisory Committee for Aeronaut ics (NACA) researchers found similar conclusions for transport scale aircraft. A technical note published in 1941 stated that a torsionally flexible wing reduces the vertical acceleration increment indu ced by wind gusts if the torsion axis is ahead of the aerodynamic locus. In addition, the percentage in the reduction of vertical acceleration was f ound to be far more dependent of gust shape and duration than that of gust velocity. It was also found that in some gust conditions torsionally flexible wings have a lower bending moment at the root of the wing as compared to a rigid counterpart. Results indicated that the torsionally flexible wing slightly increased the longitudinal stability of the aircraft in a gust. The NACA researchers conclu ded that this method of gust alleviation would be impractical for full-scale aircraft gi ven the design trends of the time [13]. Starting in 1997 the annual Internationa l Micro Air Vehicle Competition (IMAVC) has been a major source of inspiration for innova tive MAV designs and configurations. Major collegiate competitors have been the University of Florida (UF), University of Arizona, Brigham Young University and many others. The competition has historically consis ted of a surveillance category and either an e ndurance or payload category. The University of Florida successfully impl emented the flexible wing findings in 1999, winning the IMAVC. This marked a new step in MAV design. Previous ly designs generally focused on aerodynamic efficiency and incorporated a rigid flying wing and required the use of a stability augmentation system. With the flex ible wing and innovative c onstruction methods UF was able to develop a MAV of co mparable size that did not re quire the use of any stability augmentation system [2, 5].

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15 The UF MAV team has won first place in the last 8 consecutive IMAVC competitions establishing an impressive track record for the flexible wing of reliability, small size and big capabilities. The surveillance platform that UF fielded at the 2006 competition had a maximum dimension of 11.5 cm and has successfully flown even smaller in the past. The focus on minimizing the maximum dimensi on of the craft has lead to a spherical design space and almost circular wing planform Such planforms result in low aspect ratio (LAR) wings and tend to have unique perfor mance characteristics due to aerodynamic phenomena. 1.2 Motivation and Overview Flight-testing is a critical pha se of any aircraft developmen t. The information gathered during these flight tests is used to verify performance predictions or illuminate points of possible improvement for the next design ite ration. In the micro scale regime flight test results are often little more than pilot feed back and ground obs ervations, which although insightful, are highly qualitative. Miniature flight data record ers are commercially availabl e equipped with sensors that record airspeed, altitude, accelerations and can interface with any sensor small enough that has an analog voltage interface [14] Small telecommunication devi ces are also available that transmit the information to the ground instead of recording it onboard. To date, an effective AOA sensor has not been developed for this scale of operation. Currently, these systems are not small enough to fit on the smallest MAVs and are typically utilized on la rger, further developed platforms. The goal of this research is the initial de velopment and implementation of a method or system that would extend the information gathered from flight tests to the structural dynamics and deformations of the flexible wing in a quantit ative sense. This will enable an investigation

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16 into the behavior and performance of the wing as the craft is performing maneuvers such as dives, turns, stalls, spins, as well as straight and level flight all in calm and gusty conditions. Extending the investigational envelope into this dynamic arena will provide new insight to the behavior of the membrane wing, allowing for not only design improvements but also quantitative comparison and further validation of observa tions made in wind tunnel experiments and theoretical investigations. The platform selected for this research is the Micro Morphing Aerial Land Vehicle (MMALV). This platform was chosen for its av ailability, ease of system incorporation and low wing stiffness that allows relatively large magnitude displacements. The MMALV was developed at the University of Florida MAV la b in cooperation with Case Western University and Bio Robotics. The MMALV will be further described in later sections. The subsequent chapters of this paper will discuss the work completed and accomplishments made. The second ch apter will be a literature surv ey of relevant research into flexible wing MAVs and optical measurement systems utilized on flexible wing designs. The third chapter will detail the developed system, calibration method, and equipment used. The fourth chapter will discuss the flight test, data gathering, and data pro cessing with a presentation of the results. The fifth and final chapter wi ll present the conclusions drawn, recommendations for future work, and a discussion of the error and sensitivity study conducted.

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17 CHAPTER 2 LITERATURE SURVEY 2.1 Research Many theoretical and wind tunnel in vestigations have been made into the behavior of the UF flexible membrane wing and surrounding fl ow properties. Early theoretical and computational work by Jenkins et al. [12], Waszak et al. [6], and Shyy et al. [7, 8-11] showed that thin significantly cambered and flexible wings would perform better in the LRN range as compared to more trad itional airfoil designs. Extensive wind tunnel tests and experiments have been conducted on wings of various flexible designs, and the results have supporte d the theoretical findings on the performance characteristics. Albertani et al. [3, 4, 15-20] found that with an increase in velocity, corresponding dynamic pressure, or AOA, the tip of the flexible wing twists to a lower angle of incidence, the dihedral angle increases, the ma ximum camber increases, and the location of the maximum camber moves aft. The combinations of these changes re sult in a corresponding favorable change in pitching moment and lift that act to damp out sudden resulting accelerations of the vehicle, therefore obtaining a smoother flight as compared to an equivalent rigid wing [3]. Wind tunnel experiments performed by Sytsma [21] using various flow visualization techniques illuminated the flow characteristic s about the 15 cm span UF MAV wing designs. The findings supported the theoretical and computati onal work of Lian et al. [22-25] and Viieru [26], which illustrated flexible membrane aerodynamic interactions of a LAR UF MAV wing in LRN conditions, including the e ffect of tip vortices and th e laminar separation bubbles. For LAR wings the tip vortices cover a si gnificant percentage of the wing area and therefore are an important contri buting factor to the aerodynamic be havior. For wings that have an aspect ratio below 1.5, tip vortices form signi ficant low-pressure cells on the top surface of

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18 the wing resulting in a non-linear co ntribution to the total lift and increases the lift-curve slope as the angle of attack increases. Th is non-linear effect is considered one of the effectors responsible for the high stall angl e of attack [27]. 2.2 Deformation Measurement Methods 2.2.1 Visual Image Correlation Various methods of measuring the deflection an d final deformed shape of the flexible wing have been developed and implemented in the wind tunnel environment. The University of Florida has implemented the Visual Image Corre lation (VIC) system, which was developed at the University of South Carolina, to obtain el astic deformation measurements of wind tunnel models [3, 4, 17-20]. The VIC system was devel oped by Helm et al. [28] in the mid 1990s and provides a global shape and deformation measurem ent. The VIC system uses two cameras to obtain highly accurate 3D measurements of a surf ace prepared with a low luster high contrast random speckle pattern. Measurements, both in plane and out of plane, are obtained by a comparison of the test subject in the deformed stat e and a reference state. Error quantification is based on many variables and is different for each set up. Errors of 0.05 mm have been reported [28]. Calibration of the VIC system requi res the use of a calibrati on plate with a grid of markings at known intervals [3]. 2.2.2 Video Model Deformation With the development and refinement of so lid-state cameras and personal computers, a method termed Video Model Deformation system (VMD) was developed at NASAs transonic wind tunnel facility in the 1990s to measure wind tunnel model deformation [29]. The VMD is a single camera system that finds the centroids of ci rcular targets placed on the model at locations of interest in wind on and wind off conditi ons. By comparing th e wind on and wind off

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19 conditions, the deflection of the centroids can be calculated using collin earity equations. The collinearity equations relate the 2D image c oordinates to the 3D obj ect coordinates [29]. The calibration technique for VMD requires that the three Euler angles relating the camera orientation relative to the wi nd tunnel and distortion parameters be determined. These parameters are found through an iterative proces s from images taken of a calibration plate aligned with the tunnel axis at various known locations. In order to use the collinearity equations to convert from 3D space to a 2D imag e plane, the locations of the centroids of the circular targets must be known or precisely calculated in at least one of the directions [30]. The VMD system is still under development in an ongoing effort to refine and automate measurements [31-33]. This method was implemented at the Langley basic aerodynamic res earch tunnel (BART) to measure the deformation of the UF MAV flexible wing while gathering loads data to compute the stability derivatives and coefficients [6, 32]. The measurement method developed in this paper is similar to the VMD system and could be described as an in-flight version with an alternative calibration method. 2.2.3 Projection Moir Interferometry Projection moir interferometry (PMI) is an optically based global measurement technique that was custom adapted by NASA for use in wind tunnels. PMI is used to measure out-of-plane deformations of models. PMIs global measuremen t ability enables the collection of data to be acquired over the entire camera field-of-view, w ithout the use of targets or contacting the surface being measured [30]. The PMI system relies on a grill of equally spaced, parallel lines projected onto the wind tunnel model surface. The optical axis of the project or system is typically aligned such that it is perpendicular to the surface being measured. Imag es are gathered with a charged coupled device

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20 (CCD) camera equipped with a narrow bandpa ss filter that is matched to the projector illumination wavelength. The camera is positioned to view the model at a 30-45 angle inclined from the projector optical axis [30]. Camera perspective distortions are removed by image processi ng routines. Further image processing routines interfere the images with a generated reference grid. The resulting interferograms contain moir fringe s patterns. These patterns ar e further processed to obtain a quantitative, spatially continuous representation of the model surface shape or deformation [30]. This method was implemented at the Langley BA RT to measure the deformation of the UF MAV aeroelastic deformable wing while gathering loads data to compute the static stability derivatives and coefficients [6, 34]. 2.3 Flight Test Instrumentation Previous flight tests have incorporated the use of a Micro Data Acquisition System (MDAS) developed by NASA Langley re search facility specifically for MAV applications [35]. The MDAS incorporates 3-axis linear accelerome ters and 27 free analog voltage channels for any sensor that has the proper interface, such as airspeed, altitude, strain sensors, thermocouples, or servo potentiometer voltage [14]. The data is sampled at 50 to 100 Hz and is recorded in a 4 MB flash chip on board the craft, which can then downloaded to a PC at the end of each flight [36]. Information gathered from this system was implemented to examine stability and controllability for aircraft with wingspans of 12 and 24 that incorporated active wing warping for flight control [14, 35-38]. In the same investigations a ca mera was mounted looking at the wing, this was to monitor the morphing mechanism and observe flexible deformations [37]. No measurements of wing deformation were made.

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21 Autopilot systems have also been utilized to collect flight data. Autopilots require readings such as accelerations, global positions sy stem (GPS) location, and airspeed to carry out their function. The systems typica lly record the collected data on board or if equipped with a transmitter device can relay the telemetry informa tion to the ground station where it can then be recorded or examined in real time. A method of recording RC pilot control input during flight was developed by the UF MAV team. Tests were conducted on the same MAV desi gn with various stiffne ss wings, and center of gravity positions. The tests were also conducted in calm and gusty conditions. The system enables measurement and comparison of pilot workload and vehicle-handling qualities for various MAV wing designs [39].

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22 CHAPTER 3 SYSTEM LAYOUT 3.1 Platform The first generation MMALV had a 12 wingspa n and was of conventional aft tail design with the incorporation of the flexible membra ne wing concept. For the purpose of this investigation as well as supporting other ongoing research, the original MMALV was scaled up to a 16 wingspan. The new larger second gene ration MMALV, shown in Figure 3-1, allows for greater payload volume and weight. The MMA LVs wing is unique even among the UF MAV fleet in that it incor porates floating angled batten reinfo rcement (FA) for the membrane support structure. The term FA means that the battens are arranged in a radial angular pattern and are attached to the membrane material only instead of being aligned with the fuselage and attached to the leading edge like that of the batten reinfo rced (BR) designs. The FA design was chosen to allow for future development of a retracting wi ng feature. The various planform designs currently in use by the UF MAV team are shown in Figure 3-2. The MMALV makes use of an AstroFlight 010 electric motor controlled by a Phoenix-25 electronic speed controller made by Castle Cr eations and powered by a 3-cell 1350 mAh Lithium polymer battery pack. The craft is controlled solely by rudder and elevat or, which was actuated using micro servos manufactured by HiTec. 3.2 Camera Wing deformations are three dimensional, sp anwise, chordwise and vertical, which will from here on, be referred to as X Y and Z directi ons respectively. This directional convention is shown in Figure 3-3. Deflections in the Z directi on are typically at least one order of magnitude greater than the deflec tions in the other two. This is supported by the authors findings and observations from previous studies [3, 4, 17-20]. For simplicity, this work will only be

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23 concerned with deflections in the Z direction, wh ich will be referred to as W for the duration of this report. The investigated method of measuring the wi ng deformation of a MAV while in flight consisted of a small camera rigidly mounted on the ai rcrafts vertical stabili zer looking foward at the wing, which was outfitted with tracking points. The system has been termed Single Point Optical Tracking (SPOT). The proposed plan was to mount the camera in such a way that as much of the deformation as possible would be in the plane of the camera view, which would result in the highest resolution. With Z deflections being the only concern in this study a brief investigation into camera locati on revealed that mounting it hi gh and far aft on the vertical stabilizer would provide th e best vantage point. The camera was to be mounted external and on a stabilization surface, therefore it was deemed prudent to minimize the size of the camer a. The original camera selected was a color CCD snake type with a resolution of 380 lines. This camera was chosen for its form factor, in that the optical head and the processing board were mounted separately connected by a wire. This camera is presented in Figure 3-4. Unfortunate ly, during preparations for the flight tests the author accidentally electrically destroyed the two CCD cameras ordered, the second trying to figure out what went wrong with the first. Due to time constraints, a suitable subs titute was found on hand, a complementary metaloxide-semiconductor (CMOS) type camera. The CMOS camera used has a comparable resolution and size to the CCD but falls short in other areas of quality, such as sharpness and color clarity. The vertical stabilizer had to be extended and stiffened in order to accommodate the camera. This was accomplished by adhering a multip le layer carbon plate to the existing vertical

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24 surface using cyanoacrylate (CA), glue typica lly used by model builders. A shim was constructed and installed in orde r to achieve a proper viewing a ngle. The camera was secured to the shim with CA and tied with Kevlar thread for the flight tests. The camera location and mounting is presented in Figure 3-5. With the relatively low loads involved, the vertical tail being stiffened and the camera securely attached it was assumed rigid so as that there was no movement of the camera relative to the fuselage or wing root. No per ceptible relative motion was observed during the tests th at would suggest otherwise. 3.3 Tracking Points The primary source of data for this study was taken from image processing therefore attention had to be paid to color selection. The color of the wing was determined by the requirements of the VIC system, a dull tan with fl at black speckles. These colors are used to reduce glare and provide distinguishable markings that the VIC software can locate and track. With these constraints in mind, a bright orange st icker material typically used to make visual marking on MAVs was selected for the tracking points. Using a hole punch for convenience and consistency the bright orange stic ker material was cut into -inch diameter circles. These circles were then securely adhered to the wing at a regular interval using CA, resulting in a local stiffening of the membrane material. This local stiffening was deemed acceptable given the scope of this work. Two patterns were investigated, one aligned with the batten structure of the wing and the other aligned with the camera view. The former was intended to mark the areas suspected to have the maximum deflection. The latter was inte nded to ease processing. The two patterns are shown in Figure 3-6.

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25 3.4 Angle of Attack Indicator In order to establish the validity of SPOT, data taken in steady level flight at a measured velocity and AOA would be reproduced in th e wind tunnel and corresponding measurements taken with the VIC to enable a comparison. To accomplish this goal two obstacles needed to be negotiated, finding the AOA and airspeed of the MMALV during flight. To that end, an AOA indicator was devised. The methodology used for th e airspeed will be deta iled in later sections. The AOA indicator was a simple weathervane ty pe that was mounted on the wing tip with a bracket fabricated from piano wire. The indicator was positioned above the wing surface a distance equivalent to one chord length at the span location wher e it was mounted. This location was chosen to place the indicator in the free stream airflow as much as possible, away from the propeller wash and aerodynamic effects of the wi ng. With location of the hinge point at the indicator, the twisting of the wi ng in flight was found to have lit tle or no effect on the reading. The indicator and its mounting are presented in Figure 3-7. The indicator was statically balanced to approximately horizontal and proved very responsive, indicating AOA changes even at a wa lking pace. Measurement was taken from the indicator optically using the prev iously discussed camera. The sa me bright orange marking tape was used on the indicator as was on the tracking dots. The method of calibrating and extracting the reading will be discu ssed in a later section. 3.5 Deformation Measurement Calibration The calibration methodology for deformation m easurement used was comparative based utilizing both VIC and SPOT. The VIC system was chosen for its ease of implementation and accuracy. The surface preparations required by VIC prohibited the presence of the SPOT tracking points during use. Therefore, both of the systems could not be employed at the same

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26 time. The solution devised to obtain consistent defl ections with use of either system at separate times was to make use of the wind tunnel. The University of Floridas Mechanical and Aerospace Engineering Departments closed loop wind tunnel was used. This tunnel is an Engineering Laboratory Design (ELD) model 407B re-circulating type wind tunnel, which is loca ted in room 125 of MAE-A, UF building 725. The tunnel has two test sections th at can be utilized, a small s ection of 0.61 m x 0.61 m x 2.44 m and a large section of 0.838 m x 0.838 m x 2.44 m. An optical glass ce iling was used for the wind tunnel portion of this research. Further detail s and a flow field characterization of the tunnel with both test sections are reported by Sytsma [21]. The VIC was used to measure the model 3D ge ometry, as well as the in-plane and out-ofplane displacements. To capture the 3D geometry of a subject, the system utilizes synchronized cameras, each looking from a different viewing angles at the same target. The cameras were installed over the wind tunnel l ooking through the optical glass cei ling, as shown in Figure 3-8. The cameras were calibrated through the glass ce iling to ensure minimal distortion effects. The VIC determines the displacements of th e specimen by tracking the deformation of a random speckle pattern applied on the surface. The speckle pattern acquired by the digital cameras before and during loading is processed by finding the region in a deformed image that maximizes the normalized cross-correlation score w ith respect to a small subset of the reference image, which was taken when no load was applied at each angle measured [20]. Two continuous 250-Watt lamps were used to illuminate the wing surface. The background color and sheen on the wings surface wa s chosen to minimize noise that can result from glare and interfere with proper image processing. Further details on the application of the

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27 VIC system in wind tunnel experi ments are reported in [3, 4, 1720]. The combination of this wind tunnel and VIC system has been pr eviously utilized by Albertani [3]. The MMALV was equipped with a mounting br acket and installed on the wind tunnel sting balance. To avoid errors due to inconsis tent results the propeller was removed during the calibration process. The wind tunne l was then run at a constant ve locity of 13 m/s, as indicated by the tunnel instrumentation, and an AOA sweep was performed. The sweep was made taking data at 0, 3, 5, 10, 12, and 15 degrees AOA. On th e first run, the VIC was utilized to measure the shape and deformation of the MMALVs fl exible wing. Next, the same platform was outfitted with the tracking points and AOA indicat or and the wind tunnel run was duplicated. The results from the collected VIC data are shown in a later section. The presented VIC data has a tetrahedron superimposed on it re presenting the outline of the SP OT data for clarification and spatial referencing. Video from the onboard camera was recorded on a Sony digital recorder and later transferred to the computer where still frame im ages were pulled. The images taken from the video were then processed through a custom Matla b code written by the author. The code found the centroids of each tracking point in pixels w ith reference to the image plane using the image processing toolbox commands incorporated into Ma tlab. These centroids were then sorted and stored in a specific order to ease future processing. The locations of the centroids of the tracking points were determined for each angle of attack and a reference wind off condition. Utilizi ng this data the deflectio n of the centroid of each tracking point relative to th e camera view plane could be determined in pixels. These deflections were stored in the same order esta blished for the tracking points. The numbered order of the tracking points along with the locati on of each centeroid is shown in Figure 3-9. A

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28 brief investigation was made into the referenc e condition and it was found that the pitch angle had minimal or no effect on the location of the ce ntroids in the image plane, and therefore only one reference image was needed. The calibration curves established for each tracking point is a comparison of the displacement of each centeroid location in mm, from the VIC data, and the corresponding displacement in pixels, from the SPOT data. In order to find the desire d data points from the X Y Z locations and U V W displacements of the VI C data field, the X Y locations of the tracking point centroids needed to be found. The index that corresponds to the X Y location of the centroids would be the same index for the correct Z U V and W data. With the X Y locations in mm and the centeroid locations in pixels, a common basis needed to be found. This was accomplished by processing and comparing images taken of the MMALV wing from the VIC cameras with the tr acking points installed and images produced by the VIC program with the data field overlaid. Exam ples of these images are shown in Figure 3-10 and 3-11. The closest data point to the centeroid location of interest was used, since the VIC data is a continuous and subtly varying surface the possibl e error introduced was considered minimal. The calibration curves for each tracking point and a bar plot of the normalized residuals for each curve is presented in Figure 3-12. A linear assumption was made for the calibra tion curves. This assumption is supported from the calibration performed with the original CCD camera. The resulting curves from this first data set also showed a linear tendency. Th e results from the CCD based system calibration are presented in Appendix A.

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29 The VIC software computes an origin and orie ntation for each data set and arranges the output data relative to it. Due to the change in angle and other variables, the orientation of the output data from one measurement to the next was not the same. A standard origin and orientation was chosen, full-fiel d rotation and translation matri ces were used to achieve the alignment with the angles being derived from each data set. Each VIC data set was properly aligned before it was utilized. A data set before and after alignment is presented in Figure 3-13. 3.6 AOA Indicator calibration The measurement taken from the AOA indicator also required processing the captured images from the SPOT camera in the wind tunnel. In order to extract the data the pixels containing the orange marking tape were taken as data points. These data points were then placed on a scatter plot and a linear fit made thr ough them. The angle of the slope of this linear fit was termed the indicated angle. An exampl e is presented in Figure 3-14. The commanded angle of the wind tunnel was take n as the actual AOA and was m easured with respect to the chordline of the wing root and the floor of the wind tunnel. The indicated angle was plotte d against the actual angle for the three velocities and six angles investigated. Another lin ear fit was made thr ough the resulting scatte r plot of 18 data points and was used as the AOA calibration curv e. The AOA calibration curve is shown in Figure 3-15. A linear fit was assumed for th e AOA indicator calibration curve based on the simplified reasoning that the angl e shown from the cameras perspective was a rotational change of coordinates from the actual angle of the indicator, which would not introduce any nonlinearity. The AOA indicator calibration curve from th e original CCD camera is presented in Appendix A. This curve serves to support th e linear assumption in the same way as the deflection calibration curves.

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30 Figure 3-1. 16 Wingspan second generation MMALV. Figure 3-2. Various Planform Designs in use by UF MAV team: Rigid (A), Batten Reinforced (B), Perimeter Reinforced (C), and Floating Angled (D).

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31 Figure 3-3. Directional convention utilized. Figure 3-4. Color CCD snake type camera. Figure 3-5. Camera location and mounting.

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32 Figure 3-6. The two tracking point patterns inves tigated, suspected maximum deflection (A), and ease of processing (B). Figure 3-7. The AOA indicator and its mounting.

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33 Figure 3-8. VIC system installation and setup. Figure 3-9. The numbered order of the tracki ng points and the locati on of each centroid.

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34 Figure 3-10. Example of imag e of MMALV through VIC camera w ith VIC data field overlaid, this is the standard output from the VIC software. Figure 3-11. Image of MMALV through VIC camera with tracking points installed.

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35 Figure 3-12. Calibration curves for each tracking point.

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36 Figure 3-13. A VIC data set before and after alignment. Figure 3-14. Image of the AOA indicator from SPOT camera and processed results. Figure 3-15. AOA indicator calibration curve.

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37 CHAPTER 4 FLIGHT TEST 4.1 Flight Test Setup The flight test was conducted on the UF campus in a field typically utilized for flighttesting of other UF MAV designs. The test wa s conducted in the late afternoon, when lighting conditions were more favorable. The craft wa s flown by a RC pilot with visual contact. The method used to estimate the flight sp eed involved two markers set at 15.24 m apart and a fixed camera approximately centered betw een the two markers and perpendicularly sat back at a distance of approximately 60 m. The te st setup is shown in Figure 4-1. With the flight path being from one marker to the other, a cros swind condition steady at 3 m/s and gusting to 4.5 m/s prevailed as reported by a weather st ation that was also located on campus. The SPOT equipped MMALV was flown over the two markers as straight and level as possible. Four such passes were made and each was in view of the fixed camera. The estimated velocity was found by examining the video of the fi xed camera that was reco rding at the standard rate of 30 frames per second. The largest contributing sources of errors invol ved in calculating the airspeed are parallax and temporal resolution. The parallax error is du e to the possibility of the platform not flying directly over the markers but in front or behind the markers relati ve to the fixed camera. From the perspective of the fixed camera the same, kno wn, distance would be traveled even though the actual distance traveled would be longer or shorter. Assuming th e flight path was maintained within a corridor of 3 m either side of the markers, a difference of 1.5 m was possible from the assumed 15.24 m and the actual distance traveled. The temporal resolution is a result of the camer a utilizing the standard frame rate of 30 frames per second. As the frames were used to measure the time it took the craft to cross the

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38 markers this resolution had a dir ect effect on the estimated airspeed. A quantified estimation of the two error sources discussed was found by ar tificially changing measurements taken by the amounts prescribed of 1.5 m in distance and 1/30th of a second. The er ror estimations are presented in Table 4-1 along with the nomina lly estimated airspeed and AOA for each pass. Various maneuvers were performed after the passes were made. The maneuvers included left and right banked turns, stalls, dives, and a spin. During the flight, the maneuvers were noted in the order performed. Due to the poor image quality of the CMOS camera and problems with lighting, results could not be extracted for all ma neuvers. Measurements could be made for one negative AOA, three high AOA, one hard left and one hard right turn maneuvers as well as the four level passes. These results will be presented in subsequent sections. The video feed from SPOT was recorded on a UF MAV lab ground station, which is equipped with a Sony digital reco rder, video receiver and two fl at panel antennas. The same onboard CMOS camera discussed previously was us ed. The recorded vide o was later transferred to the computer where the still images were captu red in the same manner as previously discussed for the wind tunnel calibration data. 4.2 Processing Results The images captured from the test flight had to be processed individually with custom threshold adjustments for each due to the vary ing lighting conditions encountered during the flight. The processed images were then run through the same centroid locating algorithm used previously. By comparing the located centroids and the locati on of the reference centroids, a difference was found between the two in pixels of displacement. These pixels of displacement were then put into the appropriate calibration equation for the correspon ding tracking point to find the deflection in mm. The same reference image used in the wind tunnel was used to calculate the in flight results.

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39 Due to deflections of an unanticipated magnit ude on some of the images the forward most row of tracking points were not vi sible on two of the maneuvers i nvestigated, the right and left rolls. For these maneuvers, only the porti on of the wing visible was processed. The method previously described to find the AOA of the MMALV was implemented on the same image used to obtain the deflection m easurements. The AOA calculated utilizing the calibration curve was rounded to the nearest intege r. The resulting resolution proved adequate for the purpose of this research and confiden tly encompassed possible errors from aerodynamic and optical influences. A preliminary error and sensitivity analysis was performed on some of the computational aspects of the system. These aspects include the image thresholding, cen troid-locating algorithm and the statistical error in the calibration equations The analyses performed will be discussed in more detail in the conclusi on section of this report. 4.3 Observations The video captured from the SPOT camera reve als new insight into the dynamic behavior of the flexible wing. Most of the deflection take s place near the tip of th e wing as is shown in nearly all of the following figures. Deflecti on in this outboard area was expected based on previously conducted studies that were reviewed in the first chapter of this report. The leading edge spar cannot be observed in the SPOT camera view however, the bracket attaching the AOA indicator to th e spar was visible. Throughout the flight, this bracket was observed changing angle relative to the camera, this indicated that the leading edge spar undergoes regular torsional deformations. This defo rmation is readily apparent with the onset of a vibration condition. Several vibration modes were observed throughout the flight, most of them appearing in the outboard section and tip of the wing. These vibration modes appear to occur at relatively low

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40 AOA. This reveals that the observe d vibration is a situation of fl ow separation instead of a stall condition. The current state of the system is not of high enough fidelity to withdraw detailed or quantitative conclusions on such rapid dynamics. A similar state was observed for the same craft in the wind tunnel portion of this work. A vibration mode was observed at 0 degree AOA a nd 26 m/s flow velocity. The vibrations subsided as the AOA was increased to 4 degrees, this coupled with observations made by Sytsma [21] it is believed that the vibration was due to flow sepa ration along the lower surface. 4.4 Discussion of Deformations and Plots The wing design utilized as the subject of the presented work featured combination characteristics documented by Albertani et al [3, 4, 17, 18, and 20] for the perimeter and the batten reinforced wings. The MMALV wing exhi bited the twisting, or wash out, deformation tendencies of the batten reinforced design and the changes in camber of the perimeter reinforced designs. This behavior can be attributed to the floating angled batten conf iguration as well as the significant flexibility of the structur al members of this particular wing. A topographic representation of the wing in an undeformed state is shown in Figure 4-2. This geometric data was gathered utilizing the VIC system and is oriented as discussed earlier. The measurements from the SPOT system are pr esented in multiple methods to aid in the interpretation of the results. The wing was sectionalized with lines that we re aligned with the tracking points in the chord wise direction. This divi sion is shown in Figure 4-3. A cr oss section view of the wing at each line was found from the VIC data of the undefo rmed state. The cross sections are shown in Figure 4-4. The measurement data from both SPOT and VIC is presented in two forms, the amount of out of plane deformation, and the deformed shap e. The amount of deformation data from the

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41 SPOT system is superimposed over an image of the wing for spatial orientation. The displacement of each tracking point as measured with SPOT was added to the height of the corresponding location in the undeformed state to find the deformed shape. The deformed shape data collected from the SPOT system is presente d in cross sectional pl ots with the undeformed cross sections previously discussed in figures 45 thru 4-12. The data presented in the deformed cross sectional plots is also s hown topographically in figures 4-13 thru 4-24. The data for the four passes is presented with the corresponding VIC data fr om the wind tunnel tests for comparison in figures 4-13 thru 4-20. The presented VIC data collected during the wind tunnel portion of this investigation has a tetrahedron superimposed on it representing the outline of the SPOT data for clarification and spatial referencing. The first wind tunnel run wa s made at 13 m/s and at -10, -5, 0, 3, 5, 10, 12, and 15 degrees, the measurements amassed were uti lized to generate the calibration curves. The VIC data collected at 13 m/s is presented in figur es 4-25 thru 4-32 to illu strate the effects of various AOA on wing deformations. This was done to enable a metric for a general comparison of the high and negative AOA SPOT data presented in figures 4-21 thru 4-24. Data collected from the flight test for a hard right and left turn is presented in figures 4-33 thru 4-34 due to deformed portions of the wing blocking the camer a view of the forward most row of tracking points data could not be collect ed for the entire wing area. The second wind tunnel run conducted at 20, 23, and 26 m/s at 0 and 4 degree AOA was made after the flight test was conducted and th e flight speed and AOA fo r each pass calculated. The data from the second run was obtained to faci litate a comparison of da ta gathered from the VIC and SPOT at the same conditions of airs peed and AOA. The data from the SPOT shows a remarkable agreement with the VIC data. The minor differences that are apparent could be attributed to the dynamic effects of the quasi st eady state flight conditi ons, which would effect

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42 wing deformations and AOA readings. These dynami c effects were not measured or monitored. Even with the differences, the results are remarkab ly similar in shape and magnitude attesting to the validity of the system and method utilized. Table 4-1. Calculated airspeed and AOA of level passes with error estimations. Errors Pass AOA (degrees) Airspeed (m/s) Paralax (%) Temporal resolution (%) 1 4 20.79 5.00 4.76 2 4 26.93 5.00 6.26 3 3 19.90 5.00 4.55 4 4 22.85 5.00 5.26 Figure 4-1. Flight test setup. Figure 4-2. Topographic representation of the wing in an undeformed state.

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43 Figure 4-3. Chordwise sectional lines. Figure 4-4. Cross sectional view of wi ng at each corresponding sectional line.

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44 Figure 4-5. Cross sectional plots of flight-test SPOT data for pass 1: estimated 20.8 m/s and 4 AOA. Figure 4-6. Cross sectional plots of flight-test SPOT data for pass 2: estimated 26.9 m/s and 4 AOA.

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45 Figure 4-7. Cross sectional plots of flight-test SPOT data for pass 3: estimated 19.9 m/s and 3 AOA. Figure 4-8. Cross sectional plots of flight-test SPOT data for pass 4: estimated 22.9 m/s and 4 AOA.

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46 Figure 4-9. Cross sectional plots of flight -test SPOT data for high AOA 1: 18 AOA and unknown airspeed. Figure 4-10. Cross sectional plots of fli ght-test SPOT data fo r high AOA 2: 20 AOA and unknown airspeed.

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47 Figure 4-11. Cross sectional plots of fli ght-test SPOT data fo r high AOA 3: 24 AOA and unknown airspeed. Figure 4-12. Cross sectional plots of flight-t est SPOT data for negative AOA: -19 AOA and unknown airspeed.

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48 Figure 4-13. Topographic plots of flight-test SPOT data for pa ss 1: estimated 20.8 m/s and 4 AOA. Figure 4-14. Topographic plots of wind t unnel VIC data for 20 m/s and 4 AOA.

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49 Figure 4-15. Topographic plots of flight-test SPO T data for pass 2: estimated 26.9 m/s and 4 AOA. Figure 4-16. Topographic plots of wind t unnel VIC data for 26 m/s and 4 AOA.

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50 Figure 4-17. Topographic plots of flight-test SPO T data for pass 3: estimated 19.9 m/s and 3 AOA. Figure 4-18. Topographic plots of wind t unnel VIC data for 20 m/s and 4 AOA.

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51 Figure 4-19. Topographic plots of flight-test SPO T data for pass 4: estimated 22.9 m/s and 4 AOA. Figure 4-20. Topographic plots of wind t unnel VIC data for 23 m/s and 4 AOA.

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52 Figure 4-21. Topographic plots of flight -test SPOT data for high AOA 1: 18 AOA and unknown airspeed. Figure 4-22. Topographic plots of flight -test SPOT data for high AOA 2: 20 AOA and unknown airspeed.

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53 Figure 4-23. Topographic plots of flight -test SPOT data for high AOA 3: 24 AOA and unknown airspeed. Figure 4-24. Topographic plots of flight-t est SPOT data for negative AOA: -19 AOA and unknown airspeed.

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54 Figure 4-25. Wind tunnel VIC da ta for 13 m/s and -10 AOA. Figure 4-26. Wind tunnel VIC data for 13 m/s and -5 AOA. Figure 4-27. Wind tunnel VIC data for 13 m/s and 0 AOA.

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55 Figure 4-28. Wind tunnel VIC data for 13 m/s and 3 AOA. Figure 4-29. Wind tunnel VIC data for 13 m/s and 5 AOA. Figure 4-30. Wind tunnel VIC data for 13 m/s and 10 AOA.

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56 Figure 4-31. Wind tunnel VIC data for 13 m/s and 12 AOA. Figure 4-32. Wind tunnel VIC data for 13 m/s and 15 AOA.

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57 Figure 4-33. Amount of deformation data for the hard left turn 7 AOA unknown side slip and unknown airspeed. Figure 4-34. Amount of deformation data for th e hard right turn 9 AOA unknown side slip and unknown airspeed.

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58 CHAPTER 5 CONCLUSIONS AND RECOMENDATIONS Flexible wings make use of inherent elastic properties of the wing fo r alleviation of gust loads. With the torsion axis of a wing of low torsional rigidity located ahead of the aerodynamic center for that wing a passively deformable syst em is created. This passively deformable systems reaction is directly dependent on the wing loading and results in a washout condition. This adaptive washout reduces the total lift and bending moment at the wing root therefore reducing the dynamic response of the over all aircra ft to sudden and temporary changes in flight conditions. The SPOT system has proven to be effectiv e at obtaining quantitative deformation information of a flexible wing in flight. This system is a valuable addition to the test instrumentation already utilized for the characte rization of the flexible wing MAV. Information gathered with this system has provided new insight s into the behavior of the flexible wing design as well as the flight envelope for this class of aircraft. 5.1 Discussion of Error and Sensitivity Analysis The sensitivity analysis performed on the image thresholding, and centeroid-locating algorithm was accomplished by artificially moving the deformed location of the centeroid up and down by one pixel and recalculating the displacement Changing the threshold parameters in the program would typically change the selected area around each tracking point equally in all directions. The centeroid was then calculated from the selected areas. The selected areas, typically comprising of 200 or more pixels, were generally arranged in an elliptical form. An example of a thresholded image is shown in Figure 5-1. Considering the magnitude of the area involve d and even changes i nduced by the threshold parameters it was concluded that a tolerance of one pi xel is a reasonable if not conservative

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59 assumption. The top and bottom lines marked by circles and squares are the centroid location tolerance bounds. The final effect of this tolera nce is different for each point due to the differing slopes of the calibration curves. Errors induced by the linear assumption of the calibration eq uations are plotted as error bars and were calculated utilizi ng the Matlab statistical toolbox. The possible error calculated and presented with the error bars relates to th e goodness of the linear fit to the calibration data points collected and is related to the norm of the residuals presente d with the calibrations curves in Figure 3-12. The previously presented cross s ectional plots of each data set taken with the SPOT system are presented again with the erro r bars and pixel tole rance bounds included in Figures 5-3 thru Figure 5-10. As mentioned in a previous section to obtain the VIC meas urement during the calibration process the closest data point to the centeroid location of interest was used, since the VIC data is a continuous and subtly varying surface th e possible error introduced was minimal. 5.2 Recommendations Further research is needed to refine the SPOT system. Recommendations include the use of a high quality camera, more robust image pr ocessing procedure, and implementation of a flight data recorder to reco rd airspeed and accelerations. It is strongly recommended that a quality CCD camera be used if possible. Superior qualities, such as sharpness and color clarity w ould ease image processing as well as increase the accuracy of the centroid locations. In additi on, the camera should be positioned such that the maximum wing deflection does not obstruct the view of any of the trackin g points. In addition, the calibration curves should be expande d to include negative deflections. It is also recommended that research be conducted into a more robust image processing procedure than the simple technique implemented for this initial investigation. With a more

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60 robust image processing procedure in place and fu rther refinement of the developed code the system could be automated to analyze each frame of a flight video. This capability would greatly increase the volume of information ga thered and the understanding of flexible wing dynamics. It is also recommended that i nvestigations be con ducted into different combinations of the wing skin and tracking point colorations that wo uld enable the simultaneous use of the VIC and the SPOT. During the flight test, at certain attitudes, the red i carex would glow through the tan paint with a color similar to the orange used for the tracking points making automated differentiation difficult. Possibiliti es include the use of light outsi de the visible spectra such as using a special camera filter and markings that fluoresce in ultra violet or infrared. Use of the VIC and SPOT simultaneously woul d greatly reduce the time consumption of the calibration procedure and woul d eliminate the need to use th e wind tunnel. The wind tunnel was utilized to obtain a repeatable global deflec tion of the flexible wi ng. If the two systems could be used simultaneously, the requirement of repeatability would be eliminated and another method of global deformation could be implemen ted in the lab to provide the information necessary for calibration. Implementation of a flight data recorder such as the Micro Data Acquisition system previously mentioned would greatly expand the overall capabilities and depth of information. The challenge that would be posed by such ut ilization is a common pr oblem for flight test equipment, time synchronization. Possibilities incl ude mounting multiple pitot tubes, one in the typical forward position, and th e rest facing other directions. Such an arrangement could measure air speed and possibly gusts or at least provide an indi cator of a gust encounter aside from the dynamic response of the platform.

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61 Figure 5-1. Example of thresholded imag e, taken from flight test pass1. Figure 5-2. Image captured and processed for pass 1. Figure 5-3. Pass 1 Cross section deformati on with tolerance bounds and errorbars.

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62 Figure 5-4. Pass 2 Cross section deformati on with tolerance bounds and errorbars. Figure 5-5. Pass 3 Cross section deformati on with tolerance bounds and errorbars.

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63 Figure 5-6. Pass 4 Cross section deformati on with tolerance bounds and errorbars. Figure 5-7. High AOA 1 Cross section deforma tion with tolerance bounds and errorbars.

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64 Figure 5-8. High AOA 2 Cross section deforma tion with tolerance bounds and errorbars. Figure 5-9. High AOA 3 Cross section deforma tion with tolerance bounds and errorbars.

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65 Figure 5-10. Negative AOA Cross section deformation with tolerance bounds a

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66 APPENDIX A CALIBRATION OF CCD CAMERA Shown below are the calibrations results using original CCD camera. These initial results are presented to further illustrate the lineari ty of the calibration cu rves using for the SPOT system. The repeatability of the calibration met hod is revealed with duplication of the linearity in the calibration curves utilizi ng two different camera types. Figure A-1. AOA indicator calibration curv e for first run with CCD camera. Figure A-2. Tracking point calibration cu rves for first run with CCD camera.

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67 Figure A-3. Image taken with CCD came ra during the calibration process. Figure A-4. Image taken with CCD camera dur ing the calibration process with the AOA indicator installed.

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68 LIST OF REFERENCES 1. Mueller, T. J., editor, Proceedings of the Conference on Fixed, Flapping and Rotary Wing Vehicles at Very Low Re ynolds Numbers, Notre Dame University, Indiana, June 5-7, 2000. 2. Ifju, P. G., Ettinger, S., Jenkins, D., and Martinez, L., Composite Materials for Micro Air Vehicles, SAMPE Journal, Vol. 37, 2001, pp. 7-12. 3. Albertani, R. Experimental Aerodyna mic and Static Elastic Deformation Characterization of Low Aspect Ratio Flexib le Fixed Wings Applied to Micro Aerial Vehicles., Ph.D. Dissertation, Universi ty of Florida, Gainesville, FL, 2005. 4. Albertani, R., Boria, F., Bowman, S., Clax ton, Crespo, A., Francis, C., Ifju, P., Johnson, B., Jung, S., Lee, K. H., Morton, M., and Sy tsma, M., Development of Reliable and Mission Capable Micro Air Ve hicles, University of Florida, MAE Dept., 9th International MAV Compet ition, South Korea, 2005. 5. Ifju, P. G, Jenkins, D. A., Ettinger, S., Lia n, Y., Waszak, M. R., and Shyy, W., FlexibleWing-Based Micro Air Vehicles, AIAA 2002-0705. 6. Waszak, M. R., Jenkins, L. N., and Ifju, P. G ., Stability and Control Properties of an Aeroelastic Fixed Wing Micro Aerial Vehicle, AIAA 2001-4005. 7. Shyy, W, Berg, M., and Ljungqvist D., Flapping and Flexible Wings for Biological and Micro Vehicles. Progress in Aerosp ace Sciences Vol. 35, (1999), pp. 455. 8. Shyy, W., Jenkins, D. A., and Smith, R. W., Study of Adaptive Shape Airfoils At Low Reynolds Number in Oscillatory Fl ow, AIAA Journal, Vol. 35, 1997, pp.1545-1548. 9. Shyy, W., Klevebring, F., Nilsson, M., Sloan, J., Carroll, B., and Fuentes, C. A Study of Rigid and Flexible Low Reynol ds Number Airfoils, Jour nal of Aircraft, Vol. 36, 1999, pp.523-529. 10. Shyy, W., Klevebring, F., Nilsson, M., Sloan, J., Carroll, B., and Fuentes, C., Rigid and Flexible Low Reynolds Number Airfoils, Journal of Aircraft, Volume 36, No.3, MayJune 1999. 11. Shyy, W., and Smith, R., A Study of Flexible Airfoil Aerodynamics with Application to Micro Air Vehicles, AIAA Paper 97-1933. 12. Jenkins D. A., Shyy, W., Sloan, J., Klevebri ng, F., and Nilsson, M., Airfoil Performance at Low Reynolds Numbers for Micro Air Vehi cle Applications," Thirteenth Bristol International RPV/UAV Conference, University of Bristol, 1998. 13. Shufflebarger, C. C., Tests of a Gust-All eviating Wing in the Gust Tunnel, T.N. No. 802, NACA, 1941.

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69 14. Abdulrahim, M., From Flight Tests to Ve hicle Design: Implementation of the Micro Data Acquisition System in Micro Air Vehicl es, Journal of Undergraduate Research July 2002. 15. Albertani, R., Hubner, J. P., Ifju, P.G ., Lind, R., and Jackowski, J., Experimental Aerodynamics of Micro Air Vehicles, SA E World Aviation Congress and Exhibition, Reno, NV, 2004. 16. Albertani, R., Hubner, P., Ifju, P., Lind, R., and Jackowski, J., Wind Tunnel Testing of Micro Air Vehicles at Low Reynolds Numbers SAE Journal 2004-01-3090. 17. Albertani, R., Stanford, B., Hubner, J. P., and Ifju, P., Aer odynamic Characterization and Deformation Measurements of a Flex ible Wing Micro Air Vehicle, SEM Annual Conference, Portland, OR, 2005. 18. Albertani, R., Stanford, B., Hubner, J. P., Lind, R. and Ifju, P., Experimental Analysis of Deformation for Flexible-Wing Micro Ai r Vehicles, AIAA SDM Conference, Austin, TX, 2005. 19. Albertani, R., Stanford, B., Hubner, J. P., a nd Ifju, P., Characteriz ation of Flexible Wing MAV s: Aeroelastric and Propulsion Eff ects on Flying Qualities, AIAA Atmospheric Flight Mechanics Conferen ce, San Francisco, CA, 2005. 20. Albertani, R., Stanford, B., Hubner, P., Ifju, P., and Lind, R., Wind Tunnel System Characterization Applied to Po wered Micro Aerial Vehicles with LAR Fixed Flexible Wings, 20th Bristol UAV Systems Conference, April 2006. 21. Sytsma, M., Aerodynamic Flow Characterization of Micro Ai r Vehicles Utilizing Flow Visualization Methods. MS Thesis, Univ ersity of Florida, Gainesville, FL, 2006. 22. Lian, Y., Membrane and Adaptively-Shaped Wings for Micro Air Vehicles. Ph.D. Dissertation, University of Florida, Gainesville, FL, 2003. 23. Lian, Y., and Shyy, W., Three-Di mensional Fluid-Structure In teractions of a Membrane Wing for Micro Air Vehicle A pplications, AIAA Paper 2003-1726. 24. Lian, Y., Shyy, W., and Ifju, P. G., Mem brane Wing Model for Micro AirVehicles, AIAA Journal, Volume 41, No. 12, Dec. 2003, pp.2492-2494. 25. Lian, Y., Shyy, W., Viieru, D., Zhang, B ., Membrane Wing Aerodynamics for Micro Air Vehicles Progress in Aero space Sciences 39 (2003) 425. 26. Viieru, D., Albertani, R., Li an Y., Shyy W., and Ifju P., Effect of Tip Vortex on Wing Aerodynamics of Micro Ai r Vehicles, AIAA-12805-511, 2005.

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70 27. Mueller, T. J., and DeLaurier J. D., Aer odynamics of Small Vehicles, Annual Review of Fluid Mechanics, Vol. 35, 2003, pp. 89-111. 28. Helm, J. D., McNeill, S. R. and Sutton, M. A., Improved 3-D Image Correlation for Surface Displacement Measurement, Optic al Engineering, Volume 35(7), 1996, pp. 1911-1920. 29. Burner, A., Wahls, R., and Goad, W., W ing Twist Measurements at the National Transonic Facility. NASA Technical Memorandum 110229. 30. Burner, A. W., Fleming, G. A., and Hoppe, J. C., Comparison of Three Optical Methods for Measuring Model Deformation, AIAA-2000-0835, January 2000. 31. Burner A. W., and Graves, S. G. Developm ent of an Intelligent Videogrammetric Wind Tunnel Measurement System, 2001. Confer ence on Optical Diagnostics for Fluids, Solids, and Combustion, SPIE Vol. 4448, pp 120-131. 32. Burner, A. W., and Liu, T., Videogrammetric Model Deformation Measurement Technique, Journal of Aircra ft, Vol. 38, no. 3, May-June 2001. 33. Burner, A. W., Liu T., DeLoach, R., Uncer tainty of Videogrammetric Techniques used for Aerodynamic Testing, AIAA-2002-2794. June 2002. 34. Fleming, G., Bartram, S., Waszak, M., and Je nkins, L., Projection Moir Interferometry Measurements of Micro Air Vehi cle Wings, SPIE Paper No. 4448-16. 35. Abdulrahim, M., Garcia, H., and Lind, R., Flight Characteristics of Shaping the Membrane Wing of a Micro Air Vehicle, J ournal of Aircraft, Vol. 42, No. 1, JanuaryFebruary 2005. 36. Garcia, H. M., Control of Micro Air Ve hicles Using Wing Morphing, MS Thesis, University of Florida, Gainesville, FL, 2003. 37. Abdulrahim, M., "Flight Performance Char acteristics of a Biologically-Inspired Morphing Aircraft," AIAA Paper 2005-345. 38. Abdulrahim, M., Dynamic Characteristics of Morphing Micro Air Vehicles, MS Thesis, University of Flor ida, Gainesville, FL, 2004. 39. Jenkins, D. A., Ifju., P. J., Abdulrahi m, M., and Olipra, S. Assessment of Controllability of Micro Air Vehicles, MAV Conference, Bristol, UK, April 2001.

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71 BIOGRAPHICAL SKETCH James D. Davis was born in a small Alabama town and raised in an even smaller Alabama town not far away. Growing up in a rural unincor porated area, he did some of the typical things like playing in the woods, riding his bike, and going to the river. He usually kept busy by helping his parents around the property and lending a hand wherev er possible in building the house his parents still live in toda y. He tried his legs at runni ng track and cross-country, which only ended in shin splints, sore knees, and short-te rm friends but it did aid in the discovery of his flat feet, which would later k eep him out of the Marines. Like many people growing up in small towns, he knew there had to be more somewhere else. After a brief interest in cars, he knew he wanted to do something mechanical. The fall following his high school graduation, he attended a technical school for aircraft maintenance from which he had received a pamphlet a few mo nths prior to his graduation. The school was in yet another small Alabama town and this is wh ere he discovered aviation. Not long before finishing the two-year program and earning his ai rframe and power plant mechanics certificate he decided he could do more than turn a wrench for a living, so he tu rned his attention to aerospace engineering. Staying in-state, he attended Auburn Universi ty where he made several accomplishments including assisting in the desi gn and development of a VTOL UAV with a team headed by Dr. Ron Barrett. The platform was almost a commerci al success. While at Auburn, he was also the team captain of Auburns first entry to the SA E Aerodesign Heavy lift competition. Fielding an aircraft James co-designed the team won the east competition and placed second in the west competition. That was the closest any team had come to winning both competitions, rookie or otherwise.

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72 A few weeks before his graduation ceremony from Auburn, he started work as a civil servant for the US Air Force at Eglin ABF in an internship program that included earning a masters degree. With the constraints on school selection from the Air Force, he attended the University of Florida. At UF, he successfully st ruggled to complete the course requirements in the single calendar year allotted by the internsh ip program. While attending UF James worked with the UF MAV team and Dr. Peter Ifju from which he learned of the flexible wing design on which this thesis is based. He is now looking fo rward to continuing his career in aviation at the Air Force Research Lab developing the future of UAVs. His next academic goal is to earn a pilots license and never stop learning.


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Permanent Link: http://ufdc.ufl.edu/UFE0017640/00001

Material Information

Title: Measurement of Flexible Wing Deformations in Flight
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0017640:00001

Permanent Link: http://ufdc.ufl.edu/UFE0017640/00001

Material Information

Title: Measurement of Flexible Wing Deformations in Flight
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0017640:00001


This item has the following downloads:


Full Text











MEASUREMENT OF FLEXIBLE WING DEFORMATIONS IN FLIGHT


By

JAMES D. DAVIS













A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2006

































This thesis is dedicated to my family who has supported me as much as possible through
the years. To my Father for teaching me how to work. To my mother for teaching me patients
and persistence. To my sister for teaching me survival and compassion. And to the rest of my
family for all the life lessons offered through the years.

I also dedicate this thesis to all the teachers, instructors, professors, classmates, and
coworkers I have had the honor to know and work with. For all of the lessons, challenges, and
clarifications.

I would not be where I am without any of you. Thank you.









ACKNOWLEDGMENTS

This work was made possible by the US Air force civil service internship program

PALACE Acquire thru which I attended the University of Florida. Also, I thank the professors

at the University of Florida specifically Dr. Peter Ifju for advising me through the one calendar

year I was allotted to complete the required course work. I would also like to acknowledge the

USAF AFRL/MN for supporting the completion of this thesis in a timely manor. In addition, I

thank every one on the UF MAV team for all the help and support.

I would also like to recognize my family for helping me anyway possible. Finally I thank

my dog, Adian, who I rescued from the Alachua County Humane Society, for the badly needed

distractions and unconditional love. Hang in there little buddy, I promise things will get better.










TABLE OF CONTENTS

page

A CK N O W LED G M EN TS ................................................................. ........... ............. 3

LIST OF TA BLES ...................... ....................................................................................... ..... 6

LIST O F FIG U RE S ................................................................. 7

ABSTRAC T ................................................. ............... 10

CHAPTER

1 IN TR O D U C T IO N ................................................................................ 12

1.1 Challenges and D evelopm ents .............................................................. .... 12
1.2 M motivation and Overview ............................................................ ............... 15

2 LITERATURE SURVEY................. .................................. 17

2 .1 R research ................... ........................................................................17
2.2 Deform action M easurem ent M methods ..................................................................... 18
2.2.1 V isual Im age C orrelation.............................................................. ...............18
2.2.2 V ideo M odel D reform action ............................................. ............................18
2.2.3 Projection M oire Interferom etry .................... .................... .......... ............... 19
2.3 Flight Test Instrum entation................................................................................. ........ 20

3 SY STEM LA Y O U T ................................. ..........................................22

3.1 Platform .................................................. ..................22
3.2 Cam era .............. ................ ... .. ............ ............ .... .... ............... 22
3.3 Tracking Points ........................ ...... .............................. ........ 24
3.4 A ngle of A attack Indicator ....................................................................... ...................25
3.5 Deformation M easurem ent Calibration ............................................ ............... 25
3.6 A O A Indicator calibration ........................................ ............................................29

4 F L IG H T T E S T .................................................................................................................. 3 7

4.1 Flight Test Setup .................................................................................... ..................37
4 .2 P ro c e ssin g R e su lts .......................................................................................................3 8
4.3 O observations ............... .. ..........................39
4.4 Discussion of Deformations and Plots ............................. ...................... 40

5 CONCLUSIONS AND RECOMENDATIONS ........................................58

5.1 Discussion of Error and Sensitivity Analysis .......................................................58
5.2 R ecom m endations ............................................................................. ............ .. 59



4









APPENDIX: CALIBRATION OF CCD CAMERA ..................... ............... 66

L IS T O F R E F E R E N C E S ...................................................................................... ....................6 8

B IO G R A PH IC A L SK E T C H ............................................................................... .....................7 1










LIST OF TABLES


Table


4-1. Calculated airspeed and AOA of level passes with error estimations...............................42


page









LIST OF FIGURES


Figure page

3-1. 16" W ingspan second generation M M ALV ........................................................................30

3-2. Various Planform Designs in use by UF MAV team: Rigid (A), Batten Reinforced (B),
Perimeter Reinforced (C), and Floating Angled (D). .............................. ................30

3-3. D directional convention utilized. ..................................................................... ..................31

3-4. C olor C C D snake type cam era. ..................................................................... ...................31

3-5. Cam era location and m counting ........................................................................ 31

3-6. The two tracking point patterns investigated, suspected maximum deflection (A), and
ease of processing (B) ................................ ............ ............ .. ...... 32

3-7. The AOA indicator and its m counting. ............................................. ........................... 32

3-8. V IC system installation and setup. ............................................................. .....................33

3-9. The numbered order of the tracking points and the location of each centroid ........ ........ 33

3-10. Example of image of MMALV through VIC camera with VIC data field overlaid, this
is the standard output from the VIC software........................................... ...............34

3-11. Image of MMALV through VIC camera with tracking points installed ............................34

3-13. A VIC data set before and after alignment. ............................................................... 36

3-14. Image of the AOA indicator from SPOT camera and processed results............................36

3-15. A OA indicator calibration curve. ............................................... .............................. 36

4 1 F lig h t te st setu p ................................................................................................................. 4 2

4-2. Topographic representation of the wing in an undeformed state. ................ .... ........... 42

4-3. C hordw ise sectional lines. .......................................................................... ......................43

4-4. Cross sectional view of wing at each corresponding sectional line. ....................................43

4-5. Cross sectional plots of flight-test SPOT data for pass 1: estimated 20.8 m/s and 40
A O A .......................................................... .................................... 44

4-6. Cross sectional plots of flight-test SPOT data for pass 2: estimated 26.9 m/s and 40
A O A .......................................................... .................................... 44









4-7. Cross sectional plots of flight-test SPOT data for pass 3: estimated 19.9 m/s and 30
A O A .......................................................... .................................... 4 5

4-8. Cross sectional plots of flight-test SPOT data for pass 4: estimated 22.9 m/s and 40
A O A .......................................................... .................................... 4 5

4-9. Cross sectional plots of flight-test SPOT data for high AOA 1:180 AOA and unknown
airspeed .......................................................................................... 46

4-10. Cross sectional plots of flight-test SPOT data for high AOA 2: 200 AOA and
unknown airspeed. .................................... .. ... ... .. .................. 46

4-11. Cross sectional plots of flight-test SPOT data for high AOA 3: 240 AOA and
unknown airspeed. .................................... .. ... ... .. .................. 47

4-12. Cross sectional plots of flight-test SPOT data for negative AOA: -190 AOA and
unknown airspeed. .................................... .. ... ... .. .................. 47

4-13. Topographic plots of flight-test SPOT data for pass 1: estimated 20.8 m/s and 40
A O A .......................................................... .................................... 4 8

4-14. Topographic plots of wind tunnel VIC data for 20 m/s and 40 AOA............... ...............48

4-15. Topographic plots of flight-test SPOT data for pass 2: estimated 26.9 m/s and 40 AOA....49

4-16. Topographic plots of wind tunnel VIC data for 26 m/s and 40 AOA............... ...............49

4-17. Topographic plots of flight-test SPOT data for pass 3: estimated 19.9 m/s and 30 AOA....50

4-18. Topographic plots of wind tunnel VIC data for 20 m/s and 40 AOA............... ...............50

4-19. Topographic plots of flight-test SPOT data for pass 4: estimated 22.9 m/s and 40 AOA....51

4-20. Topographic plots of wind tunnel VIC data for 23 m/s and 40 AOA............... ............... 51

4-21. Topographic plots of flight-test SPOT data for high AOA 1: 180 AOA and unknown
airspeed ........................................................ ...................................52

4-22. Topographic plots of flight-test SPOT data for high AOA 2: 200 AOA and unknown
airspeed ........................................................ ...................................52

4-23. Topographic plots of flight-test SPOT data for high AOA 3: 24 AOA and unknown
airspeed ........................................................ ...................................53

4-24. Topographic plots of flight-test SPOT data for negative AOA: -190 AOA and
unknown airspeed. .................................... .. ... ... .. .................. 53

4-25. W ind tunnel VIC data for 13 m/s and -100 AOA. ...................................... ............... 54









4-26. Wind tunnel VIC data for 13 m/s and -5 AOA. ........................................ ............... 54

4-27. Wind tunnel VIC data for 13 m/s and 0 AOA. ...................................... ............... 54

4-28. W ind tunnel VIC data for 13 m/s and 3 AOA. ..................................................... 55

4-29. W ind tunnel VIC data for 13 m/s and 5 AOA. ..................................................... 55

4-31. W ind tunnel VIC data for 13 m/s and 12 AOA. ..................................... ............... 56

4-32. Wind tunnel VIC data for 13 m/s and 15 AOA. ..................................... ............... 56

4-33. Amount of deformation data for the hard left turn 70 AOA unknown side slip and
unknown airspeed. ........................ ........ .. ... ... .. .................. 57

4-34. Amount of deformation data for the hard right turn 90 AOA unknown side slip and
unknown airspeed. ........................ ........ .. ... ... .. .................. 57

5-1. Example of thresholded image, taken from flight test passl ..........................................61

5-2. Im age captured and processed for pass 1. ........................................ ........................ 61

5-3. Pass 1 Cross section deformation with tolerance bounds and errorbars...............................61

5-4. Pass 2 Cross section deformation with tolerance bounds and errorbars.............................62

5-5. Pass 3 Cross section deformation with tolerance bounds and errorbars.............................62

5-6. Pass 4 Cross section deformation with tolerance bounds and errorbars.............................63

5-7. High AOA 1 Cross section deformation with tolerance bounds and errorbars....................63

5-8. High AOA 2 Cross section deformation with tolerance bounds and errorbars....................64

5-9. High AOA 3 Cross section deformation with tolerance bounds and errorbars....................64

5-10. Negative AOA Cross section deformation with tolerance bounds a..................................65

A-1. AOA indicator calibration curve for first run with CCD camera.......................................66

A-2. Tracking point calibration curves for first run with CCD camera................... ........... 66

A-3. Image taken with CCD camera during the calibration process. .............. ......... ..........67

A-4. Image taken with CCD camera during the calibration process with the AOA indicator
in stalled ......................................................... ................................. 6 7















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

MEASUREMENT OF FLEXIBLE WING DEFORMATIONS IN FLIGHT

By

James D Davis

December 2006

Chair: Peter Ifju
Major: Mechanical Engineering

Adverse flying conditions such as wind gusts are an unavoidable reality and a concern for

aircraft of any scale where out door flight is mission critical. In the realm of Micro Aerial

Vehicles (MAVs), where relative low mass inertias and low flight speeds are prevalent almost by

definition, handling characteristics in such typical conditions are of primary concern. In the

interest of keeping the craft volume minimal and autopilot simple these characteristics should be

as inherent and unsupplemented as possible.

With these realizations and inspiration from sailing technology, the University of Florida

developed a thin significantly cambered flexible membrane wing. The flexible wing design

passively adapts to the changing flight conditions in such a way that it results in more stable and

manageable flight characteristics. The behavior and characteristics of the flexible wing have

been studied in theories, computations, and wind tunnels all of which are limited to steady or

quasi steady state conditions. The research presented in this thesis is an initial investigation into

developing a system to monitor and measure the deformational behavior of the flexible wing in

flight as it responds to real world aerodynamic and inertial conditions.









The method proposed and investigated is one ofvideogrammetry. A camera was placed on

the tail of the aircraft oriented so that the wing was in the view. The wing was outfitted with

tracking points and an angle of attack (AOA) indicator. The system was termed single point

optical tracking (SPOT). SPOT was calibrated using the University of Florida's low speed, low

turbulence wind tunnel and the visual image correlation (VIC) measurement system. A

comparison of in flight deformation measurements to wind tunnel measurements at a similar

angle and airspeed was made with agreeable results demonstrating the effectiveness and viability

of the system. An error and sensitivity analysis was performed.









CHAPTER 1
INTRODUCTION

1.1 Challenges and Developments

Adverse flying conditions such as wind gusts are an unavoidable reality and a concern for

aircraft of any scale where out door flight is mission critical. In the realm of Micro Aerial

Vehicles (MAVs), where relative low mass inertias and low flight speeds are prevalent almost by

definition, handling characteristics in such typical conditions are of primary concern. Micro

Aerial Vehicles are defined as any aircraft with a maximum dimension of less than 15cm [1].

With the given maximum dimension, and the fact pilots do not come that small, MAVs are in the

realm of Unmanned Aerial Vehicles (UAVs).

For micro scale aircraft typical flight speeds range between 15 to 25 mph, and on an

average day gusts can vary the wind speed by more than 10 mph. These average conditions

result in sudden and significant changes of not only airspeed but also angle of attack (AOA) and

sideslip. For conventional rigid wing designs, these changes in flight conditions result in a

proportional variation in the lift produced over a corresponding short period of time [2]. The

combination of low inertias and considerable changes in lift can result in a rapid divergence from

the intended flight path if left uncorrected.

Stability and controllability are not the only problematic concerns faced by MAVs. The

dimensions and flight speeds place the aircraft in an aerodynamic region referred to as low

Reynolds number (LRN) which is between 60,000 and 150,000. Laminar boundary layer

separation is a common occurrence within this range resulting in a drop in aerodynamic

efficiency for conventional airfoils [2].

Early in the development of MAV scale aircraft, emphasis was placed on the latter

problem with designs that tried to maximize aerodynamic efficiency such as rigid blended wing-









fuselage and pure flying wings. These conventional designs proved to have undesirable flight

characteristics at these scales, requiring control supplementation for even seasoned remote

control (RC) pilots [2].

The primary mission of many UAV type craft is reconnaissance. The details of this

mission could vary from bomb damage assessment to search and rescue to surveillance in a host

of uninviting environments that would prove too close quartered or dangerous for larger manned

aircraft. The list of missions and environments is quite extensive but always requires practicality

and effectiveness from the platform selected to do the job. The mission and environmental niche

that MAVs are slated to fill are among the most demanding, with the ultimate goal being

operable and deployable by a single person through an urban canyon and inside buildings while

collecting data.

For a MAV to meet the ultimate goal in a practical manner it is required to be flown by a

remote pilot with minimal training or autonomously, both of which necessitate that the platform

have reliable and benevolent flight characteristics [3]. In the interest of keeping the craft volume

minimal and autopilot simple, these characteristics should be as inherent and unsupplemented as

possible.

With these realizations and inspiration from sailing technology, the University of Florida

MAV team implemented an alternate design option, a thin significantly cambered flexible

membrane wing [4-6]. Previous work done by Waszak et al.[6], Shyy et al. [7-11], and Jenkins

et al. [12] showed that a wing of this design would have more favorable aerodynamic

performance in adverse flight conditions.

The flexible wing design passively adapts to the changing flight conditions in such a way it

results in more stable and manageable flight characteristics. This adaptation results in significant









changes in wing geometry such as the dihedral, wing twist, maximum camber, and chord wise

location of maximum camber [6].

National Advisory Committee for Aeronautics (NACA) researchers found similar

conclusions for transport scale aircraft. A technical note published in 1941 stated that a

torsionally flexible wing reduces the vertical acceleration increment induced by wind gusts if the

torsion axis is ahead of the aerodynamic locus. In addition, the percentage in the reduction of

vertical acceleration was found to be far more dependent of gust shape and duration than that of

gust velocity. It was also found that in some gust conditions torsionally flexible wings have a

lower bending moment at the root of the wing as compared to a rigid counterpart. Results

indicated that the torsionally flexible wing slightly increased the longitudinal stability of the

aircraft in a gust. The NACA researchers concluded that this method of gust alleviation would

be impractical for full-scale aircraft given the design trends of the time [13].

Starting in 1997 the annual International Micro Air Vehicle Competition (IMAVC) has

been a major source of inspiration for innovative MAV designs and configurations. Major

collegiate competitors have been the University of Florida (UF), University of Arizona, Brigham

Young University and many others. The competition has historically consisted of a surveillance

category and either an endurance or payload category.

The University of Florida successfully implemented the flexible wing findings in 1999,

winning the IMAVC. This marked a new step in MAV design. Previously designs generally

focused on aerodynamic efficiency and incorporated a rigid flying wing and required the use of a

stability augmentation system. With the flexible wing and innovative construction methods UF

was able to develop a MAV of comparable size that did not require the use of any stability

augmentation system [2, 5].









The UF MAV team has won first place in the last 8 consecutive IMAVC competitions

establishing an impressive track record for the flexible wing of reliability, small size and big

capabilities. The surveillance platform that UF fielded at the 2006 competition had a maximum

dimension of 11.5 cm and has successfully flown even smaller in the past.

The focus on minimizing the maximum dimension of the craft has lead to a spherical

design space and almost circular wing planform. Such planforms result in low aspect ratio

(LAR) wings and tend to have unique performance characteristics due to aerodynamic

phenomena.

1.2 Motivation and Overview

Flight-testing is a critical phase of any aircraft development. The information gathered

during these flight tests is used to verify performance predictions or illuminate points of possible

improvement for the next design iteration. In the micro scale regime, flight test results are often

little more than pilot feed back and ground observations, which although insightful, are highly

qualitative.

Miniature flight data recorders are commercially available equipped with sensors that

record airspeed, altitude, accelerations and can interface with any sensor small enough that has

an analog voltage interface [14]. Small telecommunication devices are also available that

transmit the information to the ground instead of recording it onboard. To date, an effective

AOA sensor has not been developed for this scale of operation. Currently, these systems are not

small enough to fit on the smallest MAVs and are typically utilized on larger, further developed

platforms.

The goal of this research is the initial development and implementation of a method or

system that would extend the information gathered from flight tests to the structural dynamics

and deformations of the flexible wing in a quantitative sense. This will enable an investigation









into the behavior and performance of the wing as the craft is performing maneuvers such as

dives, turns, stalls, spins, as well as straight and level flight all in calm and gusty conditions.

Extending the investigational envelope into this dynamic arena will provide new insight to the

behavior of the membrane wing, allowing for not only design improvements but also quantitative

comparison and further validation of observations made in wind tunnel experiments and

theoretical investigations.

The platform selected for this research is the Micro Morphing Aerial Land Vehicle

(MMALV). This platform was chosen for its availability, ease of system incorporation and low

wing stiffness that allows relatively large magnitude displacements. The MMALV was

developed at the University of Florida MAV lab in cooperation with Case Western University

and Bio Robotics. The MMALV will be further described in later sections.

The subsequent chapters of this paper will discuss the work completed and

accomplishments made. The second chapter will be a literature survey of relevant research into

flexible wing MAVs and optical measurement systems utilized on flexible wing designs. The

third chapter will detail the developed system, calibration method, and equipment used. The

fourth chapter will discuss the flight test, data gathering, and data processing with a presentation

of the results. The fifth and final chapter will present the conclusions drawn, recommendations

for future work, and a discussion of the error and sensitivity study conducted.









CHAPTER 2
LITERATURE SURVEY

2.1 Research

Many theoretical and wind tunnel investigations have been made into the behavior of the

UF flexible membrane wing and surrounding flow properties. Early theoretical and

computational work by Jenkins et al. [12], Waszak et al. [6], and Shyy et al. [7, 8-11] showed

that thin significantly cambered and flexible wings would perform better in the LRN range as

compared to more traditional airfoil designs.

Extensive wind tunnel tests and experiments have been conducted on wings of various

flexible designs, and the results have supported the theoretical findings on the performance

characteristics. Albertani et al. [3, 4, 15-20] found that with an increase in velocity,

corresponding dynamic pressure, or AOA, the tip of the flexible wing twists to a lower angle of

incidence, the dihedral angle increases, the maximum camber increases, and the location of the

maximum camber moves aft. The combinations of these changes result in a corresponding

favorable change in pitching moment and lift that act to damp out sudden resulting accelerations

of the vehicle, therefore obtaining a smoother flight as compared to an equivalent rigid wing [3].

Wind tunnel experiments performed by Sytsma [21] using various flow visualization

techniques illuminated the flow characteristics about the 15 cm span UF MAV wing designs.

The findings supported the theoretical and computational work of Lian et al. [22-25] and Viieru

[26], which illustrated flexible membrane aerodynamic interactions of a LAR UF MAV wing in

LRN conditions, including the effect of tip vortices and the laminar separation bubbles.

For LAR wings the tip vortices cover a significant percentage of the wing area and

therefore are an important contributing factor to the aerodynamic behavior. For wings that have

an aspect ratio below 1.5, tip vortices form significant low-pressure cells on the top surface of









the wing resulting in a non-linear contribution to the total lift and increases the lift-curve slope as

the angle of attack increases. This non-linear effect is considered one of the effectors responsible

for the high stall angle of attack [27].

2.2 Deformation Measurement Methods

2.2.1 Visual Image Correlation

Various methods of measuring the deflection and final deformed shape of the flexible wing

have been developed and implemented in the wind tunnel environment. The University of

Florida has implemented the Visual Image Correlation (VIC) system, which was developed at

the University of South Carolina, to obtain elastic deformation measurements of wind tunnel

models [3, 4, 17-20]. The VIC system was developed by Helm et al. [28] in the mid 1990s and

provides a global shape and deformation measurement. The VIC system uses two cameras to

obtain highly accurate 3D measurements of a surface prepared with a low luster high contrast

random speckle pattern. Measurements, both in plane and out of plane, are obtained by a

comparison of the test subject in the deformed state and a reference state. Error quantification is

based on many variables and is different for each set up. Errors of 0.05 mm have been

reported [28]. Calibration of the VIC system requires the use of a calibration plate with a grid of

markings at known intervals [3].

2.2.2 Video Model Deformation

With the development and refinement of solid-state cameras and personal computers, a

method termed Video Model Deformation system (VMD) was developed at NASA's transonic

wind tunnel facility in the 1990s to measure wind tunnel model deformation [29]. The VMD is a

single camera system that finds the centroids of circular targets placed on the model at locations

of interest in wind on and wind off conditions. By comparing the wind on and wind off









conditions, the deflection of the centroids can be calculated using collinearity equations. The

collinearity equations relate the 2D image coordinates to the 3D object coordinates [29].

The calibration technique for VMD requires that the three Euler angles relating the camera

orientation relative to the wind tunnel and distortion parameters be determined. These

parameters are found through an iterative process from images taken of a calibration plate

aligned with the tunnel axis at various known locations. In order to use the collinearity

equations to convert from 3D space to a 2D image plane, the locations of the centroids of the

circular targets must be known or precisely calculated in at least one of the directions [30]. The

VMD system is still under development in an ongoing effort to refine and automate

measurements [31-33].

This method was implemented at the Langley basic aerodynamic research tunnel (BART)

to measure the deformation of the UF MAV flexible wing while gathering loads data to compute

the stability derivatives and coefficients [6, 32]. The measurement method developed in this

paper is similar to the VMD system and could be described as an in-flight version with an

alternative calibration method.

2.2.3 Projection Moire Interferometry

Projection moire interferometry (PMI) is an optically based global measurement technique

that was custom adapted by NASA for use in wind tunnels. PMI is used to measure out-of-plane

deformations of models. PMI's global measurement ability enables the collection of data to be

acquired over the entire camera field-of-view, without the use of targets or contacting the surface

being measured [30].

The PMI system relies on a grill of equally spaced, parallel lines projected onto the wind

tunnel model surface. The optical axis of the projector system is typically aligned such that it is

perpendicular to the surface being measured. Images are gathered with a charged coupled device









(CCD) camera equipped with a narrow bandpass filter that is matched to the projector

illumination wavelength. The camera is positioned to view the model at a 300-450 angle inclined

from the projector optical axis [30].

Camera perspective distortions are removed by image processing routines. Further image

processing routines "interfere" the images with a generated reference grid. The resulting

interferograms contain moire fringes patterns. These patterns are further processed to obtain a

quantitative, spatially continuous representation of the model surface shape or deformation [30].

This method was implemented at the Langley BART to measure the deformation of the UF

MAV aeroelastic deformable wing while gathering loads data to compute the static stability

derivatives and coefficients [6, 34].

2.3 Flight Test Instrumentation

Previous flight tests have incorporated the use of a Micro Data Acquisition System

(MDAS) developed by NASA Langley research facility specifically for MAV applications [35].

The MDAS incorporates 3-axis linear accelerometers and 27 free analog voltage channels for

any sensor that has the proper interface, such as airspeed, altitude, strain sensors, thermocouples,

or servo potentiometer voltage [14]. The data is sampled at 50 to 100 Hz and is recorded in a 4

MB flash chip on board the craft, which can then downloaded to a PC at the end of each flight

[36].

Information gathered from this system was implemented to examine stability and

controllability for aircraft with wingspans of 12" and 24" that incorporated active wing warping

for flight control [14, 35-38]. In the same investigations a camera was mounted looking at the

wing, this was to monitor the morphing mechanism and observe flexible deformations [37]. No

measurements of wing deformation were made.









Autopilot systems have also been utilized to collect flight data. Autopilots require

readings such as accelerations, global positions system (GPS) location, and airspeed to carry out

their function. The systems typically record the collected data on board or if equipped with a

transmitter device can relay the telemetry information to the ground station where it can then be

recorded or examined in real time.

A method of recording RC pilot control input during flight was developed by the UF MAV

team. Tests were conducted on the same MAV design with various stiffness wings, and center of

gravity positions. The tests were also conducted in calm and gusty conditions. The system

enables measurement and comparison of pilot workload and vehicle-handling qualities for

various MAV wing designs [39].









CHAPTER 3
SYSTEM LAYOUT

3.1 Platform

The first generation MMALV had a 12" wingspan and was of conventional aft tail design

with the incorporation of the flexible membrane wing concept. For the purpose of this

investigation as well as supporting other ongoing research, the original MMALV was scaled up

to a 16" wingspan. The new larger second generation MMALV, shown in Figure 3-1, allows for

greater payload volume and weight. The MMALV's wing is unique even among the UF MAV

fleet in that it incorporates floating angled batten reinforcement (FA) for the membrane support

structure. The term FA means that the battens are arranged in a radial angular pattern and are

attached to the membrane material only instead of being aligned with the fuselage and attached

to the leading edge like that of the batten reinforced (BR) designs. The FA design was chosen to

allow for future development of a retracting wing feature. The various planform designs

currently in use by the UF MAV team are shown in Figure 3-2.

The MMALV makes use of an AstroFlight 010 electric motor controlled by a Phoenix-25

electronic speed controller made by Castle Creations and powered by a 3-cell 1350 mAh Lithium

polymer battery pack. The craft is controlled solely by rudder and elevator, which was actuated

using micro servos manufactured by HiTec.

3.2 Camera

Wing deformations are three dimensional, spanwise, chordwise and vertical, which will

from here on, be referred to as X Y and Z directions respectively. This directional convention is

shown in Figure 3-3. Deflections in the Z direction are typically at least one order of magnitude

greater than the deflections in the other two. This is supported by the author's findings and

observations from previous studies [3, 4, 17-20]. For simplicity, this work will only be









concerned with deflections in the Z direction, which will be referred to as W for the duration of

this report.

The investigated method of measuring the wing deformation of a MAV while in flight

consisted of a small camera rigidly mounted on the aircraft's vertical stabilizer looking forward at

the wing, which was outfitted with tracking points. The system has been termed Single Point

Optical Tracking (SPOT). The proposed plan was to mount the camera in such a way that as

much of the deformation as possible would be in the plane of the camera view, which would

result in the highest resolution. With Z deflections being the only concern in this study a brief

investigation into camera location revealed that mounting it high and far aft on the vertical

stabilizer would provide the best vantage point.

The camera was to be mounted external and on a stabilization surface, therefore it was

deemed prudent to minimize the size of the camera. The original camera selected was a color

CCD snake type with a resolution of 380 lines. This camera was chosen for its form factor, in

that the optical head and the processing board were mounted separately connected by a wire.

This camera is presented in Figure 3-4. Unfortunately, during preparations for the flight tests the

author accidentally electrically destroyed the two CCD cameras ordered, the second trying to

figure out what went wrong with the first.

Due to time constraints, a suitable substitute was found on hand, a complementary metal-

oxide-semiconductor (CMOS) type camera. The CMOS camera used has a comparable

resolution and size to the CCD but falls short in other areas of quality, such as sharpness and

color clarity.

The vertical stabilizer had to be extended and stiffened in order to accommodate the

camera. This was accomplished by adhering a multiple layer carbon plate to the existing vertical









surface using cyanoacrylate (CA), glue typically used by model builders. A shim was

constructed and installed in order to achieve a proper viewing angle. The camera was secured to

the shim with CA and tied with Kevlar thread for the flight tests. The camera location and

mounting is presented in Figure 3-5. With the relatively low loads involved, the vertical tail

being stiffened and the camera securely attached, it was assumed rigid so as that there was no

movement of the camera relative to the fuselage or wing root. No perceptible relative motion

was observed during the tests that would suggest otherwise.

3.3 Tracking Points

The primary source of data for this study was taken from image processing therefore

attention had to be paid to color selection. The color of the wing was determined by the

requirements of the VIC system, a dull tan with flat black speckles. These colors are used to

reduce glare and provide distinguishable markings that the VIC software can locate and track.

With these constraints in mind, a bright orange sticker material typically used to make visual

marking on MAVs was selected for the tracking points. Using a hole punch for convenience and

consistency the bright orange sticker material was cut into 1'/-inch diameter circles. These circles

were then securely adhered to the wing at a regular interval using CA, resulting in a local

stiffening of the membrane material. This local stiffening was deemed acceptable given the

scope of this work.

Two patterns were investigated, one aligned with the batten structure of the wing and the

other aligned with the camera view. The former was intended to mark the areas suspected to

have the maximum deflection. The latter was intended to ease processing. The two patterns are

shown in Figure 3-6.









3.4 Angle of Attack Indicator

In order to establish the validity of SPOT, data taken in steady level flight at a measured

velocity and AOA would be reproduced in the wind tunnel and corresponding measurements

taken with the VIC to enable a comparison. To accomplish this goal two obstacles needed to be

negotiated, finding the AOA and airspeed of the MMALV during flight. To that end, an AOA

indicator was devised. The methodology used for the airspeed will be detailed in later sections.

The AOA indicator was a simple weathervane type that was mounted on the wing tip with

a bracket fabricated from piano wire. The indicator was positioned above the wing surface a

distance equivalent to one chord length at the span location where it was mounted. This location

was chosen to place the indicator in the free stream airflow as much as possible, away from the

propeller wash and aerodynamic effects of the wing. With location of the hinge point at the

indicator, the twisting of the wing in flight was found to have little or no effect on the reading.

The indicator and its mounting are presented in Figure 3-7.

The indicator was statically balanced to approximately horizontal and proved very

responsive, indicating AOA changes even at a walking pace. Measurement was taken from the

indicator optically using the previously discussed camera. The same bright orange marking tape

was used on the indicator as was on the tracking dots. The method of calibrating and extracting

the reading will be discussed in a later section.

3.5 Deformation Measurement Calibration

The calibration methodology for deformation measurement used was comparative based

utilizing both VIC and SPOT. The VIC system was chosen for its ease of implementation and

accuracy. The surface preparations required by VIC prohibited the presence of the SPOT

tracking points during use. Therefore, both of the systems could not be employed at the same









time. The solution devised to obtain consistent deflections with use of either system at separate

times was to make use of the wind tunnel.

The University of Florida's Mechanical and Aerospace Engineering Department's closed

loop wind tunnel was used. This tunnel is an Engineering Laboratory Design (ELD) model 407B

re-circulating type wind tunnel, which is located in room 125 ofMAE-A, UF building 725. The

tunnel has two test sections that can be utilized, a small section of 0.61 m x 0.61 m x 2.44 m and

a large section of 0.838 m x 0.838 m x 2.44 m. An optical glass ceiling was used for the wind

tunnel portion of this research. Further details and a flow field characterization of the tunnel

with both test sections are reported by Sytsma [21].

The VIC was used to measure the model 3D geometry, as well as the in-plane and out-of-

plane displacements. To capture the 3D geometry of a subject, the system utilizes synchronized

cameras, each looking from a different viewing angles at the same target. The cameras were

installed over the wind tunnel looking through the optical glass ceiling, as shown in Figure 3-8.

The cameras were calibrated through the glass ceiling to ensure minimal distortion effects.

The VIC determines the displacements of the specimen by tracking the deformation of a

random speckle pattern applied on the surface. The speckle pattern acquired by the digital

cameras before and during loading is processed by finding the region in a deformed image that

maximizes the normalized cross-correlation score with respect to a small subset of the reference

image, which was taken when no load was applied at each angle measured [20].

Two continuous 250-Watt lamps were used to illuminate the wing surface. The

background color and sheen on the wing's surface was chosen to minimize noise that can result

from glare and interfere with proper image processing. Further details on the application of the









VIC system in wind tunnel experiments are reported in [3, 4, 17-20]. The combination of this

wind tunnel and VIC system has been previously utilized by Albertani [3].

The MMALV was equipped with a mounting bracket and installed on the wind tunnel

sting balance. To avoid errors due to inconsistent results the propeller was removed during the

calibration process. The wind tunnel was then run at a constant velocity of 13 m/s, as indicated

by the tunnel instrumentation, and an AOA sweep was performed. The sweep was made taking

data at 0, 3, 5, 10, 12, and 15 degrees AOA. On the first run, the VIC was utilized to measure

the shape and deformation of the MMALV's flexible wing. Next, the same platform was

outfitted with the tracking points and AOA indicator and the wind tunnel run was duplicated.

The results from the collected VIC data are shown in a later section. The presented VIC data has

a tetrahedron superimposed on it representing the outline of the SPOT data for clarification and

spatial referencing.

Video from the onboard camera was recorded on a Sony digital recorder and later

transferred to the computer where still frame images were pulled. The images taken from the

video were then processed through a custom Matlab code written by the author. The code found

the centroids of each tracking point in pixels with reference to the image plane using the image

processing toolbox commands incorporated into Matlab. These centroids were then sorted and

stored in a specific order to ease future processing.

The locations of the centroids of the tracking points were determined for each angle of

attack and a reference wind off condition. Utilizing this data the deflection of the centroid of

each tracking point relative to the camera view plane could be determined in pixels. These

deflections were stored in the same order established for the tracking points. The numbered

order of the tracking points along with the location of each centeroid is shown in Figure 3-9. A









brief investigation was made into the reference condition and it was found that the pitch angle

had minimal or no effect on the location of the centroids in the image plane, and therefore only

one reference image was needed.

The calibration curves established for each tracking point is a comparison of the

displacement of each centeroid location in mm, from the VIC data, and the corresponding

displacement in pixels, from the SPOT data. In order to find the desired data points from the X

Y Z locations and U V W displacements of the VIC data field, the X Y locations of the tracking

point centroids needed to be found. The index that corresponds to the X Y location of the

centroids would be the same index for the correct Z U V and W data.

With the X Y locations in mm and the centeroid locations in pixels, a common basis

needed to be found. This was accomplished by processing and comparing images taken of the

MMALV wing from the VIC cameras with the tracking points installed and images produced by

the VIC program with the data field overlaid. Examples of these images are shown in Figure

3-10 and 3-11.

The closest data point to the centeroid location of interest was used, since the VIC data is a

continuous and subtly varying surface the possible error introduced was considered minimal.

The calibration curves for each tracking point and a bar plot of the normalized residuals for each

curve is presented in Figure 3-12.

A linear assumption was made for the calibration curves. This assumption is supported

from the calibration performed with the original CCD camera. The resulting curves from this

first data set also showed a linear tendency. The results from the CCD based system calibration

are presented in Appendix A.









The VIC software computes an origin and orientation for each data set and arranges the

output data relative to it. Due to the change in angle and other variables, the orientation of the

output data from one measurement to the next was not the same. A standard origin and

orientation was chosen, full-field rotation and translation matrices were used to achieve the

alignment with the angles being derived from each data set. Each VIC data set was properly

aligned before it was utilized. A data set before and after alignment is presented in Figure 3-13.

3.6 AOA Indicator calibration

The measurement taken from the AOA indicator also required processing the captured

images from the SPOT camera in the wind tunnel. In order to extract the data the pixels

containing the orange marking tape were taken as data points. These data points were then

placed on a scatter plot and a linear fit made through them. The angle of the slope of this linear

fit was termed the indicated angle. An example is presented in Figure 3-14. The commanded

angle of the wind tunnel was taken as the actual AOA and was measured with respect to the

chordline of the wing root and the floor of the wind tunnel.

The indicated angle was plotted against the actual angle for the three velocities and six

angles investigated. Another linear fit was made through the resulting scatter plot of 18 data

points and was used as the AOA calibration curve. The AOA calibration curve is shown in

Figure 3-15. A linear fit was assumed for the AOA indicator calibration curve based on the

simplified reasoning that the angle shown from the camera's perspective was a rotational change

of coordinates from the actual angle of the indicator, which would not introduce any non-

linearity.

The AOA indicator calibration curve from the original CCD camera is presented in

Appendix A. This curve serves to support the linear assumption in the same way as the

deflection calibration curves.





































Figure 3-1. 16" Wingspan second generation MMALV.


Carbon fiber main structure










abon fikrbakn s nranc


Figure 3-2. Various Planform Designs in use by UF MAV team: Rigid (A), Batten Reinforced
(B), Perimeter Reinforced (C), and Floating Angled (D).



























Figure 3-3. Directional convention utilized.


Figure 3-4. Color CCD snake type camera.


Figure 3-5. Camera location and mounting.


























Figure 3-6. The two tracking point patterns investigated, suspected maximum deflection (A), and
ease of processing (B).


Figure 3-7. The AOA indicator and its mounting.











250-Watt lamp |


VIC cameras


Optical glass
ceiling








MMALV






Figure 3-8. VIC system installation and setup.


Figure 3-9. The numbered order of the tracking points and the location of each centroid.






























Figure 3-10. Example of image of MMALV through VIC camera with VIC data field overlaid,
this is the standard output from the VIC software.


Figure 3-11. Image of MMALV through VIC camera with tracking points installed.















Tracking Point 1



05
0 ,," ", ,


0 1 2 3
Track ng Point 5

14 *
1 2
0 8
0
15 2 25
Tracking Point 9
2
15

05

2 3 4 5 6
Tracking Point 13
3
2
1 -
0 .
0 5 10
Tracking Point 17
3


2


4 45 5 55 6


Tracking Point 21
4
3 _
2 -


4 B 8 10
Tracking Point 25


4



4 6 8 10
Tracking Point 29
6 --,

4
2 -

5 10 15
Tracking Point 33
6

4


8 10 12
Tracking Point 37
5 ----- -
43 4


4 B 8


Tracking Point 2



05

o 1+,
1 2 3
Tracking Point B



05 -


0 06 1
Tracking Point 10

2
15 _4+-'
1 5 ,
05
3 4 5
Tracking Point 14
3
2 /


0
0 2 4 6 8
Tracking Point 18
2
15


1 15 2 25


Tracking Point 22
4

3

2

5 7 8 9
Tracking Point 26






6 7 8 9
Tracking Point 30


4

2
6 8 10 12
Tracking Point 34

4

3


4 5 6 7
Norm of Residuals for each Tacking Point




05 2
10 20 30


Tracking Point 3




05 ,

1 15 2 25 3
Tracking Point 7
2

1


0 2 4 6
Tracking Point 11

2
15 +4
1
3 35 4 45 5
Tracking Point 16
3
2 -4-

-A -

2 4 6 B
Tracking Point 19
4

2


0 5 10


Tracking Point 23
35
3
23 --' -
25 6.
2

4 45 5 55 6
Tracking Point 27
3
25
2 A
15
2 3 4
Tracking Point 31
45
4
35

25
6 7 8 9
Tracking Point 35
8
6 -
4 -
2
H iF 12 14 1i iF


Tracking Point 4
15
16
I A

05
2 25 3 35
Tracking Point 8
2



0
2 4 B
Tracking Point 12
2

156 *'


15 2 25 3
Tracking Point 16
3

2 *'


34567
3 4 6 6 7
Tracking Point 20
4

2


4 -- ----"---,^
2 4 6 8 10


Tracking Point 24

4

2 .


2 4 6 8 10 12 14
Tracking Point 28
6
4 +*,
2

5 10 15
Tracking Point 32

6
4 *
2-
6 B 10 12 14 16
Tracking Point 36
6


4

7 R 9 in 11


Y Axis Deflection in mm from VIC data + Data points
X Axis Deflection in pixels from SPOT data --- Linear fit


Figure 3-12. Calibration curves for each tracking point.












Unaligned


66m


-Be -40
B 80


Aligned


lC

'Co


150


Figure 3-13. A VIC data set before and after alignment.


0 10 23 3B 46 56 1 7) 0

Figure 3-14. Image of the AOA indicator from SPOT camera and processed results.

Angle of Attack Calibration Curve
15 Wind Tunnel Data
Linear Fit


Figure 3-15. AOA indicator calibration curve.


Indicated ang : 7.3055 degrees


7









CHAPTER 4
FLIGHT TEST

4.1 Flight Test Setup

The flight test was conducted on the UF campus in a field typically utilized for flight-

testing of other UF MAV designs. The test was conducted in the late afternoon, when lighting

conditions were more favorable. The craft was flown by a RC pilot with visual contact.

The method used to estimate the flight speed involved two markers set at 15.24 m apart

and a fixed camera approximately centered between the two markers and perpendicularly sat

back at a distance of approximately 60 m. The test setup is shown in Figure 4-1. With the flight

path being from one marker to the other, a crosswind condition steady at 3 m/s and gusting to 4.5

m/s prevailed as reported by a weather station that was also located on campus.

The SPOT equipped MMALV was flown over the two markers as straight and level as

possible. Four such passes were made and each was in view of the fixed camera. The estimated

velocity was found by examining the video of the fixed camera that was recording at the standard

rate of 30 frames per second.

The largest contributing sources of errors involved in calculating the airspeed are parallax

and temporal resolution. The parallax error is due to the possibility of the platform not flying

directly over the markers but in front or behind the markers relative to the fixed camera. From

the perspective of the fixed camera the same, known, distance would be traveled even though the

actual distance traveled would be longer or shorter. Assuming the flight path was maintained

within a corridor of 3 m either side of the markers, a difference of + 1.5 m was possible from the

assumed 15.24 m and the actual distance traveled.

The temporal resolution is a result of the camera utilizing the standard frame rate of 30

frames per second. As the frames were used to measure the time it took the craft to cross the









markers this resolution had a direct effect on the estimated airspeed. A quantified estimation of

the two error sources discussed was found by artificially changing measurements taken by the

amounts prescribed of 1.5 m in distance and 1/30th of a second. The error estimations are

presented in Table 4-1 along with the nominally estimated airspeed and AOA for each pass.

Various maneuvers were performed after the passes were made. The maneuvers included

left and right banked turns, stalls, dives, and a spin. During the flight, the maneuvers were noted

in the order performed. Due to the poor image quality of the CMOS camera and problems with

lighting, results could not be extracted for all maneuvers. Measurements could be made for one

negative AOA, three high AOA, one hard left and one hard right turn maneuvers as well as the

four level passes. These results will be presented in subsequent sections.

The video feed from SPOT was recorded on a UF MAV lab ground station, which is

equipped with a Sony digital recorder, video receiver and two flat panel antennas. The same

onboard CMOS camera discussed previously was used. The recorded video was later transferred

to the computer where the still images were captured in the same manner as previously discussed

for the wind tunnel calibration data.

4.2 Processing Results

The images captured from the test flight had to be processed individually with custom

threshold adjustments for each due to the varying lighting conditions encountered during the

flight. The processed images were then run through the same centroid locating algorithm used

previously. By comparing the located centroids and the location of the reference centroids, a

difference was found between the two in pixels of displacement. These pixels of displacement

were then put into the appropriate calibration equation for the corresponding tracking point to

find the deflection in mm. The same reference image used in the wind tunnel was used to

calculate the in flight results.









Due to deflections of an unanticipated magnitude on some of the images the forward most

row of tracking points were not visible on two of the maneuvers investigated, the right and left

rolls. For these maneuvers, only the portion of the wing visible was processed.

The method previously described to find the AOA of the MMALV was implemented on

the same image used to obtain the deflection measurements. The AOA calculated utilizing the

calibration curve was rounded to the nearest integer. The resulting resolution proved adequate

for the purpose of this research and confidently encompassed possible errors from aerodynamic

and optical influences.

A preliminary error and sensitivity analysis was performed on some of the computational

aspects of the system. These aspects include the image thresholding, centroid-locating algorithm

and the statistical error in the calibration equations. The analyses performed will be discussed in

more detail in the conclusion section of this report.

4.3 Observations

The video captured from the SPOT camera reveals new insight into the dynamic behavior

of the flexible wing. Most of the deflection takes place near the tip of the wing as is shown in

nearly all of the following figures. Deflection in this outboard area was expected based on

previously conducted studies that were reviewed in the first chapter of this report.

The leading edge spar cannot be observed in the SPOT camera view however, the bracket

attaching the AOA indicator to the spar was visible. Throughout the flight, this bracket was

observed changing angle relative to the camera, this indicated that the leading edge spar

undergoes regular torsional deformations. This deformation is readily apparent with the onset of

a vibration condition.

Several vibration modes were observed throughout the flight, most of them appearing in

the outboard section and tip of the wing. These vibration modes appear to occur at relatively low









AOA. This reveals that the observed vibration is a situation of flow separation instead of a stall

condition. The current state of the system is not of high enough fidelity to withdraw detailed or

quantitative conclusions on such rapid dynamics.

A similar state was observed for the same craft in the wind tunnel portion of this work. A

vibration mode was observed at 0 degree AOA and 26 m/s flow velocity. The vibrations

subsided as the AOA was increased to 4 degrees, this coupled with observations made by Sytsma

[21] it is believed that the vibration was due to flow separation along the lower surface.

4.4 Discussion of Deformations and Plots

The wing design utilized as the subject of the presented work featured combination

characteristics documented by Albertani et al [3, 4, 17, 18, and 20] for the perimeter and the

batten reinforced wings. The MMALV wing exhibited the twisting, or wash out, deformation

tendencies of the batten reinforced design and the changes in camber of the perimeter reinforced

designs. This behavior can be attributed to the floating angled batten configuration as well as the

significant flexibility of the structural members of this particular wing.

A topographic representation of the wing in an undeformed state is shown in Figure 4-2.

This geometric data was gathered utilizing the VIC system and is oriented as discussed earlier.

The measurements from the SPOT system are presented in multiple methods to aid in the

interpretation of the results.

The wing was sectionalized with lines that were aligned with the tracking points in the

chord wise direction. This division is shown in Figure 4-3. A cross section view of the wing at

each line was found from the VIC data of the undeformed state. The cross sections are shown in

Figure 4-4.

The measurement data from both SPOT and VIC is presented in two forms, the amount of

out of plane deformation, and the deformed shape. The amount of deformation data from the









SPOT system is superimposed over an image of the wing for spatial orientation. The

displacement of each tracking point as measured with SPOT was added to the height of the

corresponding location in the undeformed state to find the deformed shape. The deformed shape

data collected from the SPOT system is presented in cross sectional plots with the undeformed

cross sections previously discussed in figures 4-5 thru 4-12. The data presented in the deformed

cross sectional plots is also shown topographically in figures 4-13 thru 4-24. The data for the

four passes is presented with the corresponding VIC data from the wind tunnel tests for

comparison in figures 4-13 thru 4-20.

The presented VIC data collected during the wind tunnel portion of this investigation has a

tetrahedron superimposed on it representing the outline of the SPOT data for clarification and

spatial referencing. The first wind tunnel run was made at 13 m/s and at -10, -5, 0, 3, 5, 10, 12,

and 15 degrees, the measurements amassed were utilized to generate the calibration curves. The

VIC data collected at 13 m/s is presented in figures 4-25 thru 4-32 to illustrate the effects of

various AOA on wing deformations. This was done to enable a metric for a general comparison

of the high and negative AOA SPOT data presented in figures 4-21 thru 4-24. Data collected

from the flight test for a hard right and left turn is presented in figures 4-33 thru 4-34 due to

deformed portions of the wing blocking the camera view of the forward most row of tracking

points data could not be collected for the entire wing area.

The second wind tunnel run conducted at 20, 23, and 26 m/s at 0 and 4 degree AOA was

made after the flight test was conducted and the flight speed and AOA for each pass calculated.

The data from the second run was obtained to facilitate a comparison of data gathered from the

VIC and SPOT at the same conditions of airspeed and AOA. The data from the SPOT shows a

remarkable agreement with the VIC data. The minor differences that are apparent could be

attributed to the dynamic effects of the quasi steady state flight conditions, which would effect










wing deformations and AOA readings. These dynamic effects were not measured or monitored.

Even with the differences, the results are remarkably similar in shape and magnitude attesting to

the validity of the system and method utilized.

Table 4-1. Calculated airspeed and AOA of level passes with error estimations.
Errors
AOA Airspeed
Pass (degrees) (m/s) Paralax (%) Temporal resolution (%)
1 4 20.79 5.00 4.76
2 4 26.93 5.00 6.26
3 3 19.90 5.00 4.55
4 4 22.85 5.00 5.26


Fixed Camera Ground Station Markers






... ....
,......... ..:. ..






Figure 4-1. Flight test setup.




10










7Figure 4-2. Topographic representation of the wing in an unreformed state.
3







Figure 4-2. Topographic representation of the wing in an undeformed state.










Line 1 ULine 2
-Line 3
L~ine5


,8
,Line 9


Figure 4-3. Chordwise sectional lines.

Line 1 Line 2 Line 3
60
50 40 40
20 20
0 0 0
-20 -20
-50 -40 -40
0 100 0 60 100 0 50 100
Line 4 Line 5 Line 6
40 40 40
20 20 20
0 0 0
-20 -20 -20

0 50 100 0 50 100 0 50 100
Line 7 Line 8 Line 9


0 50 0 50 0 50
Figure 4-4. Cross sectional view of wing at each corresponding sectional line.













Line 1 Line 2 Line 3
12
10 1 10






0 50 100 150 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Line 4 Line 5 Line 6










Line 7 Line 8 Line 9
12 12 -12
o C










4 10 10 10
6 6 6
4 4 4
2 2 2





0 20 40 60 0 100 20 0 20 40 0 6 100 0 10 20 30 60 10






Deformed location of tracking points Undefonned cross sections
Dimensions in mm



Figure 4-5. Cross sectional plots of flight-test SPOT data for pass 1: estimated 20.8 m/s and 4

AOA.
Line 1 Line 2 Line 3





12 12
























0 20 4 60 BO 100 120 0 20 40 60 BO 100 0 20 40 GO BO 100
Line 7 Line B Line 9
6





















0 20 40 60 60 0 20 40 60 0 10 20 30 40 50



SDeformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-6. Cross sectional plots of flight-test SPOT data for pass 2: estimated 26.9 m/s and 40
AOA.
Line 1 Line 2 Line 3
12
10 10 12


6 6 6
4 4 4


0 50 100 160 0 20 40 60 60 100 120 0 20 40 60 60 100 120

Line 4 Line 5 Line 6


10 10

6



S21C 46 60 06 100 120 0 26 40 [C 66 1CC 0 20 46 60 6 0 100

Line 7 Line 6 Line 9

10
10 10 8

66

C 20 40 [C 60 0 20 4C [C 0 11 20 3C 46 50
t< Deformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-6. Cross sectional plots of flight-test SPOT data for pass 2: estimated 26.9 r/s and 40

AOA.
























0 50 100 150 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Line 4 Line 5 Line 6

1214 14
10 12 12






0 20 40 60 80 100 120 0 20 40 so 80 100 0 20 40 60 80 100

Line 7 Line 8 Line 9
10







10 1
14 4












0 20 4 0 0 00 0 20 40 60 0 10 20 30 40 50

SDeformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-7. Cross sectional plots of flight-test SPOT data for pass 3: estimated 19.9 m/s and 3

AOA.

Lne Line 1 Line 3
10 12








0 60 100 150 0 20 40 B0 80 100 120 0 20 40 G0 BO 100 120

Line 4 Line 5 Line 6
S1212
1 10 10
8 8 0 8
6 6 a
4 C4 4








0 2 40 6 0 100 1 20 40 60 80 100 0 20 4 0 A0 0 100









15 145
10 12
6 6
4 4 4






















AOA.
2 2 2
0 20 40 10 610 100 10 210 40 60 80 120 0 20 40 5 0 80 100

Lne7 Line 3 Line 9
11
10










Dimensions in mm













Line 2


0 50 100 150 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Line 4 Line 5 Line 6

10 10 10
86 6


4 4 4
2 2 2
0 20 40 BO 80 100 120 0 20 40 60 80 100 0 20 40 BO 80 100

Line 7 Line 8 Line 9

10 11C




4 E
2 44
0 20 40 60 80 0 20 40 60 0 10 20 30 40 50
-< Deformed location of tacking points Undeformed cross sections
Dimensions in mm



Figure 4-9. Cross sectional plots of flight-test SPOT data for high AOA 1: 180 AOA and

unknown airspeed.


Line 1 Line 2 Line 3

10 10 10



4 4 4
+ \6
2 2 2

0 50 100 150 0 20 40 60 80 100 120 0 20 40 60 80 100 120

Line 4 Line 5 Line 6
10 10 10

6 6

4 4 4
22 2
0 20 40 60 80 100 120 0 20 40 60 86 100 0 20 40 60 80 100

Line 7 Line B Line 9

10 10 10




4 5
2 4 4
0 20 40 60 80 0 20 40 60 0 10 20 30 40 50
K Deformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-10. Cross sectional plots of flight-test SPOT data for high AOA 2: 200 AOA and

unknown airspeed.


Line 1


Line 3













Line 1 Line 2 Line 3








0 50 100 150 0 20 40 60 80 100 120 0 20 40 BO 80 100 120
Line 4 Line 6 Line 6
10 10 10








4 4 4
2 2 2











0 20 40 6 0 80 100 120 0 20 40 6 0 80 100 0 20 40 6 0 80 100
LLine ine 8 Line 9
10 10 16






/ 8
6 0 6

4 4 4







0 2 0 040 80 0 20 40 60 0 10 20 30 40 50






Deformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-11. Cross sectional plots of flight-test SPOT data for high AOA 3: 24 AOA and

unknown airspeed.
LLine ine 2 Line 3
10 1 1


















LDeformede 4 L ine Lnformede 6

10 -- --- 10o
0 0


10








-10 -10
Line Line Lie


-10 10 10
10 -10






-20 0 2






I-3 0 3 0 -1 53
0 20 40 60 0 20 4 0 0 4 0 5 0






# Deformed location of tracking points Undeforned cross sections
Line Dimensions in
60 10






-1
0 20 40 00 00 20 40 00 0 16 20 00 40 00
44 Deformed location of tracking points Undeformed cross sections
Dimensions in mm



Figure 4-12. Cross sectional plots of flight-test SPOT data for negative AOA: -19 AOA and

unknown airspeed.




















i.~
4~


'I -.
-. We


* r*4


Amount of deformation Deformed shape


Figure 4-13. Topographic plots of flight-test SPOT data for pass 1: estimated 20.8 m/s and 40
AOA.


Amount of deflection Deformed shape


Figure 4-14. Topographic plots of wind tunnel VIC data for 20 m/s and 40 AOA.


16

14

12

-10








I


I
~b' ~I
.r.r r- L *i'
~7~p; ~.c
t~' .
C'* L r
'rC~~
''
F~
,I ..
B~?ur

I ""I
~II


























Amount of deformation Deformed shape

Figure 4-15. Topographic plots of flight-test SPOT data for pass 2: estimated 26.9 m/s and 40
AOA.




14










Amount of deformation 7 Deformed shape

Figure 4-16. Topographic plots of wind tunnel VIC data for 26 m/s and 40 AOA.












*'Ci "P


a':
:" i, r%' ..
f ... .V .
.a -'s
y; |ikfairy*
* I.*' '^ ^ ^ ^ ^ IJ


...a. '..,I ,. i

rWU-__ B N0
Amount of deformation Deformed shape

Figure 4-17. Topographic plots of flight-test SPOT data for pass 3: estimated 19.9 m/s and 30
AOA.


14

12

10







Amount of deflection Deformed shape

Figure 4-18. Topographic plots of wind tunnel VIC data for 20 m/s and 40 AOA.














bpi F"~


Amount of deformation Deformed shape -

Figure 4-19. Topographic plots of flight-test SPOT data for pass 4: estimated 22.9 m/s and 40
AOA.




14
10







4


Amount of deformation Deformed shape

Figure 4-20. Topographic plots of wind tunnel VIC data for 23 m/s and 40 AOA.


~td~ u.~ ..; : r., :;.
~`:,~:s'F
Ih~l
=L'~. L~. ,. :i

..
:i
`"















r- r d I** I
* md
*.' .0


*1 **,
fc H*.'''


Deformed shape


Figure 4-21. Topographic plots of flight-test SPOT data for high AOA 1: 180 AOA and
unknown airspeed.


- .. .1
o il -A/


b .
-Kr
14 "

I "j


.~


Amount of deforma n


Figure 4-22. Topographic plots of flight-test SPOT data for high AOA 2: 200 AOA and
unknown airspeed.


~d~.
r



1~


~r~lt~"
r










3,6
U "







Figure 4-23. Topographic plots of flight-test SPOT data for high AOA 3: 240 AOA and
unknown airspeed.
unknown airspeed.


Amount of deformation Deformed shape
Figure 4-24. Topographic plots of flight-test SPOT data for negative AOA: -19 AOA and
unknown airspeed.

















-4



-10

12
-14
Amount of deformation z"

Figure 4-25. Wind tunnel VIC data for


Amount of deformation

Figure 4-26. Wind


2





a
0


-2
7








tunnel VIC
tunnel VIC


7r


Deformed shape

13 m/s and -10 AOA.


Deformed shape
data for 13 m/s and -5 AOA.


2 5






05






Amount of deformation Deformed shape

Figure 4-27. Wind tunnel VIC data for 13 m/s and 00 AOA.


Him


12


1


-4





-4
4E


4




2
1z1i 1I
I """'














F3 0





































Figure 4-29. Wind tunnel VIC data for 13 m/s and 5 AOA.
9
25

2 i 2







05

Amount of deformation Deformed shape

Figure 4-28. Wind tunnel VIC data for 13 m/s and 30 AOA.


12
35
10










05


Amount of deformation Deformed shape

Figure 4-29. Wind tunnel VIC data for 13 mrn/s and 50 AOA.



12

10












Amount of deformation Deformed shape

Figure 4-30. Wind tunnel VIC data for 13 mrn/s and 100 AOA.












6
12



4








0
Amount of deformation Deformed shape

Figure 4-31. Wind tunnel VIC data for 13 m/s and 120 AOA.




1 12













Amount of deformation Deformed shape

Figure 4-32. Wind tunnel VIC data for 13 m/s and 150 AOA.


































I Z scale I
(mm)


Figure 4-33. Amount of deformation data for the hard left turn 70 AOA unknown side slip and
unknown airspeed.


IZ scale I
(mm)
Figure 4-34. Amount of deformation data for the hard right turn 90 AOA unknown side slip and
unknown airspeed.









CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS

Flexible wings make use of inherent elastic properties of the wing for alleviation of gust

loads. With the torsion axis of a wing of low torsional rigidity located ahead of the aerodynamic

center for that wing a passively deformable system is created. This passively deformable

system's reaction is directly dependent on the wing loading and results in a washout condition.

This adaptive washout reduces the total lift and bending moment at the wing root therefore

reducing the dynamic response of the over all aircraft to sudden and temporary changes in flight

conditions.

The SPOT system has proven to be effective at obtaining quantitative deformation

information of a flexible wing in flight. This system is a valuable addition to the test

instrumentation already utilized for the characterization of the flexible wing MAV. Information

gathered with this system has provided new insights into the behavior of the flexible wing design

as well as the flight envelope for this class of aircraft.

5.1 Discussion of Error and Sensitivity Analysis

The sensitivity analysis performed on the image thresholding, and centeroid-locating

algorithm was accomplished by artificially moving the deformed location of the centeroid up and

down by one pixel and recalculating the displacement. Changing the threshold parameters in the

program would typically change the selected area around each tracking point equally in all

directions. The centeroid was then calculated from the selected areas. The selected areas,

typically comprising of 200 or more pixels, were generally arranged in an elliptical form. An

example of a thresholded image is shown in Figure 5-1.

Considering the magnitude of the area involved and even changes induced by the threshold

parameters it was concluded that a tolerance of one pixel is a reasonable if not conservative









assumption. The top and bottom lines marked by circles and squares are the centroid location

tolerance bounds. The final effect of this tolerance is different for each point due to the differing

slopes of the calibration curves.

Errors induced by the linear assumption of the calibration equations are plotted as error

bars and were calculated utilizing the Matlab statistical toolbox. The possible error calculated

and presented with the error bars relates to the goodness of the linear fit to the calibration data

points collected and is related to the norm of the residuals presented with the calibrations curves

in Figure 3-12. The previously presented cross sectional plots of each data set taken with the

SPOT system are presented again with the error bars and pixel tolerance bounds included in

Figures 5-3 thru Figure 5-10.

As mentioned in a previous section to obtain the VIC measurement during the calibration

process the closest data point to the centeroid location of interest was used, since the VIC data is

a continuous and subtly varying surface the possible error introduced was minimal.

5.2 Recommendations

Further research is needed to refine the SPOT system. Recommendations include the use

of a high quality camera, more robust image processing procedure, and implementation of a

flight data recorder to record airspeed and accelerations.

It is strongly recommended that a quality CCD camera be used if possible. Superior

qualities, such as sharpness and color clarity would ease image processing as well as increase the

accuracy of the centroid locations. In addition, the camera should be positioned such that the

maximum wing deflection does not obstruct the view of any of the tracking points. In addition,

the calibration curves should be expanded to include negative deflections.

It is also recommended that research be conducted into a more robust image processing

procedure than the simple technique implemented for this initial investigation. With a more









robust image processing procedure in place and further refinement of the developed code the

system could be automated to analyze each frame of a flight video. This capability would

greatly increase the volume of information gathered and the understanding of flexible wing

dynamics.

It is also recommended that investigations be conducted into different combinations of the

wing skin and tracking point colorations that would enable the simultaneous use of the VIC and

the SPOT. During the flight test, at certain attitudes, the red icarex would glow through the tan

paint with a color similar to the orange used for the tracking points making automated

differentiation difficult. Possibilities include the use of light outside the visible spectra such as

using a special camera filter and markings that fluoresce in ultra violet or infrared.

Use of the VIC and SPOT simultaneously would greatly reduce the time consumption of

the calibration procedure and would eliminate the need to use the wind tunnel. The wind tunnel

was utilized to obtain a repeatable global deflection of the flexible wing. If the two systems

could be used simultaneously, the requirement of repeatability would be eliminated and another

method of global deformation could be implemented in the lab to provide the information

necessary for calibration.

Implementation of a flight data recorder such as the Micro Data Acquisition system

previously mentioned would greatly expand the overall capabilities and depth of information.

The challenge that would be posed by such utilization is a common problem for flight test

equipment, time synchronization. Possibilities include mounting multiple pitot tubes, one in the

typical forward position, and the rest facing other directions. Such an arrangement could

measure air speed and possibly gusts or at least provide an indicator of a gust encounter aside

from the dynamic response of the platform.

































Figure 5-1. Example of thresholded image, taken from flight test passl.


Figure 5-2. Image captured and processed for pass 1.


Lme 2


ne3


Line 4 Line 5 Line 6

12 12 -2 -
10 10 10
8 8 a
6 5 6



0 20 40 B60 B 100 120 0 20 40 60 80 100 0 20 40 60 80 100

Line 7 Line Line 9
15 14
12 1
10 10
6 8
6 6
4 4
0 20 40 6 BO0 0 20 40 O 0 10 20 30 40 50
Undeformed cross sections u Upper pixel tolerance bound
Deformed cross sections -o- Lower pixel tolerance bound
Dimensions in mm
Figure 5-3. Pass 1 Cross section deformation with tolerance bounds and errorbars.














Line 2


- /




0 50 100 15[

Line 4




2-

4
2
0 20 40 60 80 100 120


0 20 40 60 80 100

Line 8


10


5

20 40 60 80 0
Undeformed cross sections
Deformed cross sections


Line 5


12
10
8


4
2
0 20 40 B0 80 100 120

Line


0 20 40 B0 80 100

Line 9


40 60 0 10 20 30 40 50

SUpper pixel tolerance bound
-U- Lower pixel tolerance bound


Dimensions in mm
Figure 5-4. Pass 2 Cross section deformation with tolerance bounds and errorbars.


Line 1
12
10 -
8
F-
4


0 50 100 150

Line 4
14
12
10



4
2
0 20 40 60 80 100 120

Line 7

16


10


6


0 20 40 60 80
Undeformed cross secti

Defonned cross section


ine 2


Line 3


Line 6


0 20 40 60 80 100


0 20 40 60 80


Line 8 Line 9

0




6

5 4
0 20 40 60 0 10 20 30 40 50

ons D Upper pixel tolerance bound

s -- Lower pixel tolerance bound


Dimensions in mm
Figure 5-5. Pass 3 Cross section deformation with tolerance bounds and errorbars.


-Ine 5














Line 2
12 1 .



6
4
2

0 20 40 60 80 100 120

Line 5


Line 7




10


5


0 20 40 BO BD
Undeformed cross secti
Deformed cross section


Line 8 Line 9
12
60
^n 10

110 8

164


0 20 40 60 0 10 20 30 40 50
ons Upper pixel tolerance bound
s -- Lower pixel tolerance bound


Dimensions in mm
Figure 5-6. Pass 4 Cross section deformation with tolerance bounds and errorbars.


Line 1


Line 4


10


6
4
2
40 60 80 100 120

Line 7



8

6

4

20 40 60 80
Undeformed cross section:
Deformed cross sections


Line 2










20 40 60 80 100 120


Line 5


Line 8


0 "


Line 3


10
6









4
2

0 20 40 60 80 10 120

Line 6







10
4












I ^


20 40 60 0 10 20
Upper pixel tolerance bound
-o- Lower pixel tolerance bound


30 40 50


Dimensions in mm
Figure 5-7. High AOA 1 Cross section deformation with tolerance bounds and errorbars.


Line 3


Line 4


Line 6













Li e 1


0 50 100 150 0 20 40 80 80 100 120


Line 5

10 L --0


6 //
4
2
0 20 40 60 80 100


10 a 0 y
8
6
4
2
0 20 40 60 80 100 120

Line 6

10


6

4

2
0 20 40 60 80 100


Line 7


Line 9


0 20 40 60 80 0
Undeformed cross sections
Deformed cross sections


20 40 60 0 10 20 30 40 50
D Upper pixel tolerance bound

-o- Lower pixel tolerance bound


Dimensions in mm
Figure 5-8. High AOA 2 Cross section deformation with tolerance bounds and errorbars.


4 %/
2 /

0 50 100 150

Line 4

3 7







0 20 40 60 80 100 120

Line 7



3





0 20 40 60 80
Undeformed cross sect
Deformed cross section


Line 2


Line 3

10


6

4 2-
2
0 20 40 60 80 100 120


Line 5


0 20 40 60 80 100


0 20 40 80 0B 100


Lne 8 Line 9
12

10
8
6

44

0 20 40 60 0 10 20 30 40 50
ions Upper pixel tolerance bound
is -- Lower pixel tolerance bound


Dimensions in mm
Figure 5-9. High AOA 3 Cross section deformation with tolerance bounds and errorbars.






















50 100 15C

Line 4








3 20 40 60 80 100 120

Line 7








3 20 40 60 80


Undeformed cross sections
Deformed cross sections


10


0




0 20 40 60 80 100 120

Line 5
10

0

-10

20

0 20 40 60 80 100

Line 8
10

0
-10
-20
-30
,- :.


Dimensions in mm
Figure 5-10. Negative AOA Cross section deformation with tolerance bounds a














































65


Line 3








20 40 60 80 100 120


Line 6


0 20 40 60 80 100

Line 9




10
-5
-10
-15 r


20 40 60 0 10 20 30 40 5C
D Upper pixel tolerance bound
-a- Lower pixel tolerance bound


0
















APPENDIX A

CALIBRATION OF CCD CAMERA



Shown below are the calibrations results using original CCD camera. These initial results



are presented to further illustrate the linearity of the calibration curves using for the SPOT



system. The repeatability of the calibration method is revealed with duplication of the linearity



in the calibration curves utilizing two different camera types.


Angle of Attack Calibration curve


Wind Tunnel Data
Linearized Fit


-15 -10 -5 0 5 10 15 20 25
Indicated Angle


Figure A-1. AOA indicator calibration curve for first run with CCD camera.


Do 3





1 2 3 4



1 2


35 4 45
Dot 1





Dot 18


Dot 18





Norm of Residuals
4 2 W
02

5 10 15 20


Dot 4 Dot 5

2 2






12 22 0 2 4 6 8
Dot 9 Dot 10








5 10 1
Dot 19 Dot 20
4 3








0 10 20 14 16 18 20


-t in9 d Dl Dat
-- nerlzed Fit


Figure A-2. Tracking point calibration curves for first run with CCD camera.


Dot 2

12

08
06
I 2
Dot 7


2
1 5
5 6 7
Dot 12


2

6 7 8 9
Dot 17




8 10 12 14
Dot 22




15 20 25


Dot 1




0
0 05 1 15
Dot 6



1
3 4 5
Dot 11





Dot 16




8 10 12 14
Dot 21




10 20 30

































ltgure A-J. Image taken with cu) camera during the calibration process.


Figure A-4. Image taken with CCD camera during the calibration process with the AOA
indicator installed.









LIST OF REFERENCES


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Wing Vehicles at Very Low Reynolds Numbers," Notre Dame University, Indiana, June
5-7, 2000.

2. Ifju, P. G., Ettinger, S., Jenkins, D., and Martinez, L., "Composite Materials for Micro
Air Vehicles," SAMPE Journal, Vol. 37, 2001, pp. 7-12.

3. Albertani, R. "Experimental Aerodynamic and Static Elastic Deformation
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4. Albertani, R., Boria, F., Bowman, S., Claxton, Crespo, A., Francis, C., Ifju, P., Johnson,
B., Jung, S., Lee, K. H., Morton, M., and Sytsma, M., "Development of Reliable and
Mission Capable Micro Air Vehicles," University of Florida, MAE Dept., 9th
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Wing-Based Micro Air Vehicles," AIAA 2002-0705.

6. Waszak, M. R., Jenkins, L. N., and Ifju, P. G., "Stability and Control Properties of an
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7. Shyy, W, Berg, M., and Ljungqvist, D., "Flapping and Flexible Wings for Biological and
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9. Shyy, W., Klevebring, F., Nilsson, M., Sloan, J., Carroll, B., and Fuentes, C. "A Study of
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10. Shyy, W., Klevebring, F., Nilsson, M., Sloan, J., Carroll, B., and Fuentes, C., "Rigid and
Flexible Low Reynolds Number Airfoils," Journal of Aircraft, Volume 36, No.3, May-
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at Low Reynolds Numbers for Micro Air Vehicle Applications," Thirteenth Bristol
International RPV/UAV Conference, University of Bristol, 1998.

13. Shufflebarger, C. C., "Tests of a Gust-Alleviating Wing in the Gust Tunnel," T.N. No.
802, NACA, 1941.










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of Deformation for Flexible-Wing Micro Air Vehicles," AIAA SDM Conference, Austin,
TX, 2005.

19. Albertani, R., Stanford, B., Hubner, J. P., and Ifju, P., "Characterization of Flexible Wing
MAV' s: Aeroelastric and Propulsion Effects on Flying Qualities," AIAA Atmospheric
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Wing for Micro Air Vehicle Applications," AIAA Paper 2003-1726.

24. Lian, Y., Shyy, W., and Ifju, P. G., "Membrane Wing Model for Micro AirVehicles,"
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33. Burner, A. W., Liu, T., DeLoach, R., "Uncertainty of Videogrammetric Techniques used
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35. Abdulrahim, M., Garcia, H., and Lind, R., "Flight Characteristics of Shaping the
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36. Garcia, H. M., "Control of Micro Air Vehicles Using Wing Morphing," MS Thesis,
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BIOGRAPHICAL SKETCH

James D. Davis was born in a small Alabama town and raised in an even smaller Alabama

town not far away. Growing up in a rural unincorporated area, he did some of the typical things

like playing in the woods, riding his bike, and going to the river. He usually kept busy by

helping his parents around the property and lending a hand wherever possible in building the

house his parents still live in today. He tried his legs at running track and cross-country, which

only ended in shin splints, sore knees, and short-term friends but it did aid in the discovery of his

flat feet, which would later keep him out of the Marines.

Like many people growing up in small towns, he knew there had to be more somewhere

else. After a brief interest in cars, he knew he wanted to do something mechanical. The fall

following his high school graduation, he attended a technical school for aircraft maintenance

from which he had received a pamphlet a few months prior to his graduation. The school was in

yet another small Alabama town and this is where he discovered aviation. Not long before

finishing the two-year program and earning his airframe and power plant mechanics certificate

he decided he could do more than turn a wrench for a living, so he turned his attention to

aerospace engineering.

Staying in-state, he attended Auburn University where he made several accomplishments

including assisting in the design and development of a VTOL UAV with a team headed by Dr.

Ron Barrett. The platform was almost a commercial success. While at Auburn, he was also the

team captain of Auburn's first entry to the SAE Aerodesign Heavy lift competition. Fielding an

aircraft James co-designed the team won the east competition and placed second in the west

competition. That was the closest any team had come to winning both competitions, rookie or

otherwise.









A few weeks before his graduation ceremony from Auburn, he started work as a civil

servant for the US Air Force at Eglin ABF in an internship program that included earning a

master's degree. With the constraints on school selection from the Air Force, he attended the

University of Florida. At UF, he successfully struggled to complete the course requirements in

the single calendar year allotted by the internship program. While attending UF James worked

with the UF MAV team and Dr. Peter Ifju from which he learned of the flexible wing design on

which this thesis is based. He is now looking forward to continuing his career in aviation at the

Air Force Research Lab developing the future of UAV's. His next academic goal is to earn a

pilots license and never stop learning.