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Brian Muldoon [email protected]
Cell: 210-865-4217 2017 Legacy Lane
College Station, TX, 77840
Project Portfolio
Table of Contents ......................................................................................................................... 1
Aero Design Team ............................................................................................................ 2 o Structural Design Team Lead o *2017-2018 Design Report Attached (pg.11-40)
The Boeing Company - Internship.................................................................................. 3 o Systems Engineering Intern
Zodiac Aerospace β Enviro Systems Internship............................................................ 4 o Design Engineering Intern
Formula One Design Team.............................................................................................. 5 o Aerodynamics Engineer
Flexible Mold (EcoMold) Research Team ..................................................................... 6 o Modeling & Analysis Lead
Air Force Research Labs.................................................................................................. 7 o Undergraduate Research Assistant
Visual Cortex Instruments .............................................................................................. 8 o Principal Mechanical Designer
Quadcopter Hobbyist ...................................................................................................... 9 o FPV Racing o Videography/Photography
Physics Demonstrator .................................................................................................... 10 o Real Physics Live YouTube Series o Just Add Science Street Demonstrations o Physics & Engineering Festivals
Aero Design Team 2018-2019 Technical Report...........................................................11
o Received 1st Place in Design Report Competition
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Aero Design Team, College Station, TX May 2016 β May 2018
Team Goal: Design, build and fly a radio-controlled aircraft to carry as much payload as possible in the form of tennis balls and metallic plates.
Structural Design Team Lead, Society of Automotive Engineers
β’ Figure 1: The 2017 Texas A&M Aero Design Team with the competition RC aircraft. The aircraft had a 9.5 ft. wingspan and could take off fully loaded in 140ft. The team achieved the structural goals for the 2017 aircraft in lifting a 22-pound payload with a 11-pound empty weight of the aircraft. Received 2nd in Design and 3rd overall at the international SAE West design competition.
β’ Figure 2: The 2018 Aero Design Team Aircraft after takeoff. With a 12ft. wing span, the aircraft can take off in 180ft. carrying 29.5 lbs. Empty aircraft structural weight is 15 lbs. I led the structural design for this aircraft designing the largest and most efficient wing ever built for the Texas A&M Aero Design Team. Received 1st place in design and 4th place overall at the international SAE East design competition.
β’ Figure 3: The 2018 aircraft wing required (blue) and actual (red) second moment of area as a function of span for the implemented tapered spar structural design. As structures lead, I worked to optimize the wing box configuration and spar geometry across wing span to minimize mass as much as possible.
β’ Figure 4: 2018 Aero Design Team Aircraft structural material breakdown by mass.
YouTube Video: βTAMU SAE AERO 2018β β Video & Edit by Brian Muldoon Link: https://www.youtube.com/watch?v=TIZ0CGVwys4
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The Boeing Company, Seattle, WA May 2018 β August 2018
Systems Engineering Intern
*Note: Images of the work that I directly did with Boeing are not available due to propriety information release agreements.
Detailed Project Descriptions 777X Systems Testing Lab
β’ Analyzed airplane level intersystem failures, cascading effects, flight deck effects, crew workload and procedures, to comply with Federal Aviation Regulation 25.1309 for complex integrated airplane system failures. οΏ½
β’ Frequently communicating with diverse teams of Boeing Technical Fellows in propulsion systems, structures and aerodynamics.
β’ Supported integrated testing with the 777X airplane zero systems testing lab and engineering flight deck simulator (Ecab).
Special Assignment β Fuselage Automated Upright Build Improvement β’ Assisted manufacturing engineers in assessing requirements maturity and
production statement of work for the Fuselage Automated Upright Build (FAUB) automated production system. οΏ½
β’ Communicated and presented FAUB process improvement conclusions to a diverse audience including program level executives, manufacturing management, and technical subject matter experts. οΏ½
Airbus A320 Horizontal Stabilizer Tear Down οΏ½ β’ Collaborate with a team of interns to derive the requirements for a horizontal
stabilizer composite rib design through teardown procedures. οΏ½ β’ Analyze the design trades between A320 and 777-300ER composite rib design and
properly document conclusions within a Structures Core Community of Practice journal entry.
Figure 1: A photo of me outside the Everett, WA production facilityοΏ½
*777X photo renders courtesy of Boeing Figure 1
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Zodiac Aerospace β Enviro System, Seminole, OK May 2017 β August 2017
Design Engineering Intern
β’ Figure 1: Graphical user interface (GUI) for turbofan performance and weight estimation tool I created using Python. Based off of fan diameter and operating speed the program will predict airflow performance specifications, air temperature increase across the fan, as well as an approximate fan component weight.
β’ Figure 2: Catalog drawing for a vapor cycle system fan used for customer
communication of designs. This drawing is now available on the Enviro Systems website for the public.
β’ Figure 3: Recorded wind tunnel testing data showing static pressure as a function of
fan airflow. This airflow performance curve is now available on the Enviro Systems website for customers and the public to view.
β’ Figure 4: A photo of me smiling while learning how to operate the fan wind βtunnel
test chamber.
Figure 1 Figure 2
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Figure 3
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Formula One Design Team, Texas A&M August 2018 β June 2019
Aerodynamics Engineer, Society of Automotive Engineers β’ Figure 1: Shows the 2019 full car aerodynamics package including a front wing, rear
wing, nosecone, side wings and an under tray with diffuser. I designed and analyzed the front wing component which is expected to produce approximately 60 pounds of downforce at the average speed of 40 mph.
β’ Figure 2: Figure and plot showing the analysis I performed for the front wing to
determine optimal ride height location in ground effect. The plot shown represents downforce (lift) in pounds as a function of the ground distance to chord length ratio.
β’ Figure 3: Aerodynamic performance curve for the front wing. Operating speeds should
not exceed 70 mph resulting in a theoretical max downforce of just over 200 pounds.
β’ Figure 4: A photo of me attempting to drive the 2018 car around a test track while hitting many cones.
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Flexible Mold Research Team, Texas A&M August 2017 β May 2018
Team Goal: Research and develop a prototype flexible mold surface which can be re-used in the manufacturing and forming processes for composite layups and concrete panels to help solve one of the 14 engineering grand challenges; repair and improve urban infrastructure.
Design & Analysis Lead
β’ Figure 1: Photo render of the unique final ball joint design with βflower petalβ head used to smooth contours when actuators are deflected. We arrived at this design after many iterations due to the sharp contours shown in figure 3.
β’ Figure 2: Rendered model of the finalized prototype. The clear top mold surface is composed of a hyperelastic material which is to support the material and withstand the applied actuation displacements.
β’ Figure 3: Finite element stress plot showing that the first iteration of the βflower petalβ head caused sharp contour points leading the team to re-design the component.
β’ Figure 4: Poster presentation setup for the Texas A&M engineering project showcase.
YouTube Video: βFlexiForm EcoMold - Aggie Challenge - TAMU Project Showcaseβ Link: https://www.youtube.com/watch?v=WiQsz1yl9Gs
Video & Edit by Brian Muldoon
Awards o 1st Place Grand Challenge Research Project at the Texas A&M Engineering
Project Showcase β Boeing Company Award
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Air Force Research Labs, College Station, TX May 2017 β August 2017
Research Task: Determine the effects of equal channel angular extrusion on martensitic steels given varying material tempering and extrusion shear direction.
Undergraduate Research Assistant
β’ Figure 1: Charpy impact test specimens demonstrating the effect of tempering (950 β to 1050 β) on the ductility of the specimen. The 1050 β samples were noted to have larger shear lips denoting a greater elongation before failure.
β’ Figure 2: AF96 steel alloy material sample image under scanning electron microscope highlighting the etched grain structure.
β’ Figure 3: Charpy impact energy testing results validating the assumptions that were made from inspecting the material specimens. Plots were created in MATLAB.
β’ Figure 4: Micro hardness measurement sets between different samples of AF96 material samples which were extruded in two different directions.
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Visual Cortex Instruments, LLC, Texas A&M August 2016 β Present
Work Task: Design a motion tracking framework which will provide means to float objects, record their motion in real-time, and superimpose motion vectors over-top the objects for analysis. I was contracted as the Principal Mechanical Design engineer for this operation which received funding to become a startup company and sell products to Texas A&M for their Mechanics labs. Principal Mechanical Designer
β’ Figure 1: Computer designed configuration for the first prototype motion tracking framework setup. The white box in the center of the system is an air table which can float most objects below 200 grams in mass. The gantry system which surrounds the air table is computer numerically controlled for tracking objects and recording magnetic field intensity.
β’ Figure 2: An object placed in circular motion about the center of the air table with superimposed velocity and acceleration vectors plotted on the video playback in real-time.
β’ Figure 3: A round object rolling without slipping down a ramp demonstrating vectors of velocity and acceleration at the outer points of the wheel.
β’ Figure 4: Experimental motion tracking framework prototype setup.
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Quadrotor Hobbyist May 2017 - Present
First Person View (FPV) Recreational Racing β’ Assembled circuit boards such as flight controllers, power distribution boards and
electronic speed controls with soldering β’ Explored the capabilities of virtual reality video and calibration of radio transmission for
the quadcopter performance. β’ Compete in local races throughout closed courses with my friends. β’ Working towards a commercial FAA quadrotor pilots license.
Figure 1: The first FPV quadrotor I have ever assembled entirely myself. The image includes the first-person view goggles (top) the quadrotor itself (left) and the radio transmitter (right). This setup was built for under $220.
Figure 1
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Physics Demonstrator, Texas A&M May 2016 - Present Real Physics Live YouTube Series
β’ Figure 1: A photo of me acting in the YouTube video βSquare Wheeled Tricycleβ which was created within the βReal Physics Liveβ Educational YouTube series.
YouTube Video Link: https://www.youtube.com/watch?v=t1dilz7naUA&list=PLLCSkX2hwUSez2Hm8smYieg_74l87Z0d4&index=21 Just Add Science Street Demonstrations
β’ Figure 2: Dipping balloon animals into liquid nitrogen with a man and his son in downtown Bryan to show the temperature effects on gas density.
Texas A&M Physics and Engineering Festival
β’ Figure 3: I am lighting my hand on fire with methane bubbles for the physics and engineering festival in April 2016 to demonstrate the Leidenfrost Effect.
β’ Figure 4: Running the Tesla Coil demonstration in the basement of the Texas A&M
Mitchell Institute of Physics. I have presented the Tesla Coil to over 2000 people who have visited the University to see the Physics and Engineering festival.
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2018 SAE Aero Design East
Texas A&M Aero Design Team -- Regular Class-- Team 019
Technical Design Report
Texas A&M University -- College Station, Texas
February 1, 2018
Team Members:Collin Haun
Lane Kirstein
Kanika Gakhar
Michael Cornman
Trevor Blair
Robert Baldwin
Brian Muldoon
Jonathan Chiu
Hugo Giordano
David Gordon
Alec Bridges
Jorge Sanchez
Jacob Evans
Bretta Winters
Terrence Matelski
Dakota Medley
Anton Oelmann
Joseph El-Ashkar
Tyler Bittner
Britton Bowlin
Brent Wooldridge
Leads:
Team Members:
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Table of Contents
Appendix A: Statement of Compliance ...................................................................................................... 2
List of Figures and Tables ...........................................................................................................................3
1.0 Executive Summary ...............................................................................................................................5
2.0 Design Philosophy & Schedule Summary .............................................................................................7
3.0 Design Layout & Trades ........................................................................................................................8
4.0 Loads, Assumptions & Environments, ...............................................................................................11
5.0 Aircraft Analysis ..................................................................................................................................12
6.0 Assembly and Subassembly, Test and Integration ..............................................................................24
7.0 Manufacturing ......................................................................................................................................25
8.0 Conclusion ...........................................................................................................................................27
Appendix B ................................................................................................................................................28
Appendix C ................................................................................................................................................28
Appendix D ................................................................................................................................................29
Appendix E ................................................................................................................................................29
Appendix F.................................................................................................................................................30
List of Figures
Figure 1: Airfoil Pareto Frontier ................................................................................................................................ 6
Figure 2: Design Philosophy ...................................................................................................................................... 7
Figure 3: Gantt Chart ................................................................................................................................................. 7
Figure 4: Texas A&M Overall Aircraft ..................................................................................................................... 8
Figure 5: Flight Score Analysis ................................................................................................................................. 9
Figure 6: Passenger and Luggage Arrangement ...................................................................................................... 11
Figure 7: Drag Polar, Critical Drag Coefficient, Lift vs Time, Lift vs Ground Distance ........................................ 12
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Figure 8: Flight Envelope ....................................................................................................................................... 13
Figure 9: Power, Propeller Efficiency, Wind Tunnel Thrust, Ecalc Thrust ............................................................. 14
Figure 10: Downwash on Empennage ..................................................................................................................... 17
Figure 11: Effective Rudder Area (Roskam, III) ..................................................................................................... 18
Figure 12: Smoke Testing to Reveal Wing Tail Interaction .................................................................................... 18
Figure 13: Wind Tunnel data for πΆππΏπ & πΆππΌ ......................................................................................................... 19
Figure 14: Torsional Loading, Lift Distribution ...................................................................................................... 20
Figure 15: Wing Tip Angle of Twist, Wing Tipp Deflection at 10Β° ........................................................................ 21
Figure 16: Spar Car Taper Decrement ..................................................................................................................... 22
Figure 17: Material Breakdown ............................................................................................................................... 23
Figure 18: Tensile Testing of Basswood .................................................................................................................. 24
Figure 19: Texas A&M SAE Plane in Flight ........................................................................................................... 25
Figure 20: Wing and Fuselage Jig............................................................................................................................ 26
Figure 21: Payload vs Altitude................................................................................................................................. 29
List of Tables
Table 1: Key Performance and Risk Analysis Parameters ......................................................................................... 5
Table 2: Cost Breakdown ........................................................................................................................................... 8
Table 3: Flight Score Sensitivities ........................................................................................................................... 10
Table 4: Comparison of S&C Derivatives .............................................................................................................. 16
Table 5: Static Margin Comparison ........................................................................................................................ 19
Table 6: Flying Modes ............................................................................................................................................. 20
Table 7: Aircraft Structural Margins ........................................................................................................................ 22
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1.0 Executive Summary
1.1. System Overview
The Texas A&M 2017-2018 SAE aircraft design was driven by the following Risk Code
Analysis (RCA) and Key Performance Parameters (KPP) in Table 1. The KPPs are the primary decision
criteria used to maximize individual flight score (profit), while the Risk Code shows a quantitative risk
associated with making each design decision, maximizing the number of successful flights (N) in the
final flight score. The RCA comprises of the Risk Analysis Parameter (RAP), which specifies the
affected category, and the Risk Priority Number (RPN), which was calculated using Lean Six Sigma
methods shown in Equation 1. The severity, occurrence, and detection parameters were rated from 1-10
for each risk.
Equation 1 π ππ = π ππ£ππππ‘π¦ β ππππ’ππππππ β πππ‘πππ‘πππ Risk Code Analysis: [RAP:RPN]
Table 1: Key Performance and Risk Analysis Parameters
1.2. Competition Projections/Conclusions
Numerical and experimental modeling of the competition aircraft at takeoff and climb predicted
a lifting capacity of 51 passengers and 25.5 lbs of luggage, within an operating envelope of +15 mph
winds, totaling 46.5 lbs. Assuming a fully loaded passenger bay, the projected score per flight is $6,375.
Assuming five complete flight rounds, the team projects the averaged final flight score to be 159.4
points per round.
Key Performance Parameters (KPP)
Risk Analysis Parameters (RAP) I. Flight Consistency
I. Rules
II. Maximizing lift to weight ratio
II. Ground Handling III. Minimizing drag
III. Aerodynamic
IV. Reliability
IV. Flight Loading V. Weight reduction
V. Pilot
VI. Ease of use
VI. Avionics VII. Simplicity of design
VII. Control
VIII. Importance of empirical testing
VIII. Safety
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Figure 1: Airfoil Pareto Frontier
1.3. Discriminators
Due to the newly implemented 12β wingspan limitation, developing discriminators to use in the
design and fabrication of the plane were critical in giving the team an edge in performance. The
Structures sub-team created a payload plate mounting mechanism that allowed for fine-tuning of the CG
location after final aircraft assembly via longitudinal threaded rods. The payload system is comprised of
high density steel plates suspended from the wing plate [KPP VI] [RCA: Incorrect CG Location β
VII:32].
The Avionics and Propulsion sub-team prioritized propeller efficiency to ensure that the 1000 W
power limit was not exceeded at takeoff. The team also focused on high propulsion efficiency at the
cruise airspeed of 27 mph. Preliminary propeller and motor analysis was conducted using a blade
element momentum theory code (Leishman, Section 3.3).
The Aerodynamics sub-team performed a trade study to aid in airfoil selection. We wrote a
BeziΓ©r-Parsec and BeziΓ©r parameterization code as a
12 variable airfoil design tool. A full factorial design
of experiment analyzed more than 40,000 airfoils in
the design space. A pareto front of feasible airfoils
was created, shown in Figure 1, and after narrowing
the design space, we used a genetic algorithm to
optimize airfoil selection. Airfoils were analyzed
using Xfoil and a multi-objective cost function
promoted designs that maximize L/D at high angles of attack and CL at low AOA [KPP II]. The cost
function used is shown in Appendix D, Equation 2. Several airfoils were found to improve the S1223βs
performance, however, many were not manufacturable because of numerical exploitation within Xfoil
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Figure 3: Gantt Chart
Figure 2: Design Philosophy
and risk associated with extremely thin trailing edges. Subsequently, the S1223 and an optimized airfoil
were tested in a wind tunnel at the analyzed Reynolds number. However, unsteady effects not modeled
in Xfoil or in CFD Reynolds-Average Navier-Stokes simulations resulted in an unforeseen low stall
angle of attack during wind tunnel testing, prompting the team to choose the S1223 to meet critical
deadlines. In future work, we intend to replace the analysis tool from Xfoil to an unsteady CFD analysis.
This could allow for superior airfoils to be designed for future years in the SAE AERO competition.
2.0 Design Philosophy & Schedule Summary
In order to satisfy the competition objectives the team implemented an iterative design
philosophy shown in Figure 2. The competition requirements drove preliminary sizing to maximize the
flight score. This design was refined through trade
studies, which provided quantitative data for system
integration of sub-team components. Bi-weekly
Preliminary Design Reviews ensured the team stayed
up to date on progress.
The Gantt Chart, seen in Figure 3, was
created to enforce the teamβs design philosophy. This chart contains hard deadlines for all trade studies
conducted during the design phase for sufficient time for build, wind tunnel testing, and flight testing.
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Table 2: Cost Breakdown
Table 2 shows the cost breakdown of the major components of the plane. The Systems
Administration sub-team monitored the teamβs budget to ensure the team had enough funds to not only
build two test planes and two competition planes, but also pay for supplies, transportation, and housing
during competition. Sub-team components were selected to fit within this budget.
3.0 Design Layout & Trades
3.1 Overall Design Layout and Size
Our fuselage design was driven by maximizing
passengers carried while minimizing drag [KPP III],
structural weight [KPP V], and preserving ease of
manufacturing [KPP VII]. We designed possible layouts
for the payload configurations to reduce fuselage frontal area and increase the packing factor of the
passengers to attain a larger overall flight score. Four and three ball rows were considered, with three
ball rows resulting in the lowest drag penalty. The fuselage and ball row design can be seen in Figure 4.
The fuselage truss is comprised of node points to create a network of two force, balsa wood
members [KPP V]. The grain is oriented parallel to the expected axial loading direction under
compression and tension to increase load bearing strength [RCA: Fuselage Member Failure -IV:64].
Figure 4: Texas A&M Overall Aircraft
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Figure 5: Flight Score Analysis
We began the empennage design with a trade study of tail configurations, which included a
conventional tail, T-tail, V-tail, and H-tail. The latter two had certain advantages but were determined to
be too heavy and too difficult to manufacture under high quality control standards [KPP V&VII]. We
analyzed the former two tail designs more thoroughly to determine which maximized the teamβs flight
score and chose the conventional tail, discussed further in Section 5.2.3. For the vertical and horizontal
stabilizers, we chose the NACA 0018 symmetric airfoil since it stalls 5ΒΊ after the wing, ensuring that the
airplane has pitch control, and can maintain maneuverability in the event of a wing stall [RCA:Wing
Stall-III:320]. The length of the fuselage defines the moment arm constraint for the control surfaces, and
historical reference data was used to determine tail volumes (Roskam, Part II). The size of the tail
surfaces was refined to meet static margin and πΆππ½ requirements. Preliminary models indicated that the
tail could be designed with no incidence angle to provide adequate longitudinal stability while
minimizing trim drag. However, we changed this angle to -4ΒΊ and increased the size of the tail by 33%
after further analysis and wind-tunnel testing, as discussed in Section 5.1.2.
3.2. Optimization and Sensitivity Analysis
To optimize the flight score, the team
calculated weight sensitivities, as listed in Table
3, and used these sensitivities to relate flight-
score and take-off weight, as seen in Equation 7.
We found that if the luggage weight alone was
increased, the revenue would be $47.60 per
pound. On the other hand, we found that if the
weight of the passengers, and hence the weight
of the luggage was increased, the revenue would increase by $101.60 per pound. Based on this analysis,
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Figure 5 shows that while adding extra luggage would significantly increase our take-off weight, it
would not help improve the flight score. Hence, the team aimed to eliminate empty cabin seats and carry
0.5 lbs of payload per passenger in order to maximize the flight score, as evident from Equation 3.
Additionally, the team found innovative ways of reducing weight [KPP V]. First, the Avionics
and Propulsion sub-team strategically chose the lightest Battery
Eliminator Circuit (BEC) available, the CC-5A BEC. The motor
requires 45A to run at full throttle, and a trade study determined
that using a higher rated Electronic Speed Control (ESC) could
improve efficiency as a result of running at cooler temperatures.
Therefore, the team chose the Phoenix Edge 75A ESC. We chose
the Thunder Power ProLite 3400 mAh 25C, which is the lightest available battery.
Second, the Structures sub-team reduced component weight in areas outside of predicted load
paths. The team used filleted holes in the middle of the wing mount plate and circular cutouts in the
wing ribs to reduce weight and eliminate stress concentrations. Areas of the fuselage were coated with
Coverite Microlite because, unlike the wing, the fuselage was not expected to experience much torsion,
owing to sufficient roll stability and tail loading [RCA: Lighter Mylar Film Failure - IV:40]. The
Microlite weighs 18.0 g/m^2 in comparison to Monokote which weighs 80.7 g/m^2, therefore
eliminating 0.23 lbs from the fuselage structure (Lewis). These weight reductions in the empty weight of
the plane allowed for a larger payload weight, which led to a flight score $11.50 higher.
3.3. Design Features and Details
The main landing gear is attached to the wing mount plate such that the location of the gear
relative to the CG renders an angle of 15Β° to meet the tipping criteria under taxi conditions. The impact
load due to landing is transferred from the mounting plate into both fore and aft wood-foam layered
Figure 3
Table 3: Flight Score Sensitivities
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Figure 6: Passenger and Luggage Arrangement
sections of the fuselage. The passengers are loaded from the top, above the wing. The payload is loaded
from underneath and mounts directly to the wing plate, as seen in Figure 6.
3.4. Interfaces and Attachments
We designed a detachable wing to simplify travel to
competition [KPP VI] [RCA: Damage During Transportation
- II:25]. In order to achieve the detachable design, the team
manufactured a layered foam-wood composite wing
mounting plate that directly attaches to fore and aft similarly
layered plates within the fuselage midsection. The layered
composite plate allows for integration of the wing assembly
and the fuselage, and is the primary interface of load transfer between the wing, landing gear, and
luggage payload mechanism.
4.0 Loads, Assumptions & Environments
4.1. Design Loads Derivations
The derivations of design landing loads required the team to assume typical landing procedure in
which the main landing gear of the aircraft would strike the ground first then slowly rotate forward until
the front nose gear makes contact. This assumes the main landing gear takes all of the landing loads
[RCA: Main Landing Gear Failure - V:200]. The landing gear system is comprised of a parabolic,
carbon fiber structure with 5β rubber wheels. The majority of landing gear stiffness is drawn from the
carbon fiber strut and is experimentally determined to be 58.2 lb/in. The wheels were assumed to
provide a damping ratio of 0.15 and a stiffness of 76.4 lb/in, which prevents compression, adding to the
clearance necessary for the propeller [RCA: Propeller Strike - V:540]. Using a dynamic analysis with a
downward velocity component of 5 ft/s, the peak acceleration of vibration is 2.87Gβs. Accounting for
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Figure 7: A) Drag Polar B) Critical Drag Coefficient C) Lift vs Time D) Lift vs Ground Distance
material inconsistency and approximate impact conditions, the team used a design load factor of 3Gβs to
size the foam-core of the wing plate for a 200 lbs load during the projected worst-case landing scenario.
4.2. Environmental Considerations
Since flight conditions vary with temperature, humidity, and air pressure, a thrust-density
relationship is generated empirically and used to predict static thrust in Lakeland, FL. The team
modified the density variable in the flight model to generate the density altitude graph as seen in Figure
21. This data was incorporated into the takeoff, DATCOM, and wind tunnel calculations to give precise
flying qualities and payload capacity for an accurate flight score estimation.
5.0 Aircraft Analysis
5.1. Analysis Techniques
5.1.1. Analytical Tools (CAD, FEM, CFD, etc.)
We initially sized the wing using class I methods satisfying the 50 lbs gross weight goal. We
selected the taper using XFLR5 to produce an elliptical lift distribution along the span of the wing. The
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Figure 8: Flight Envelope
team added geometric twist at the tips to prevent tip stall [RCA: Tip Stall - III:240]. We developed a
flight model to predict payload using a linear multi-step technique. The team used two-dimensional
kinematics to calculate the position, velocity, and acceleration of the aircraft during rollout, climb,
cruise, and turn, as seen in Figure 7C. Payload capacity was selected ensuring that lift is greater than
weight before the 200 ft runway expires and during a tailwind for wind speeds up to 15 mph, as seen in
Figure 7D [RCA: Take-off Distance - I:200]. Aerodynamic models from XFLR5, CFD, and wind tunnel
testing are implemented into the flight model during various stages of the design process.
We manufactured a 7/12th scale model of the competition plane to fit into the Oran Nicks Low
Speed Wind Tunnel on the Texas A&M campus. We conducted a dynamic pressure sweep to show that
the data is Reynolds number independent. Hence, all non-dimensional coefficients collected during
analysis could be simulated at any flight speed. The team also performed alpha and beta sweeps to
generate a drag polar, seen in Figure 7A, and calculate stability and control derivatives seen in Table 4.
5.1.2. Developed Models
The flight envelope shows aircraft performance at various airspeeds, as seen in Figure 8. The
flight envelope calculates the coefficient of lift required to maintain steady level flight. Using wind
tunnel data, we calculated drag and thrust as a function of velocity. The optimal speed to fly the aircraft
occurs where the difference between the thrust and drag
is maximized, at approximately 27 mph.
The critical drag coefficient is defined as the
value that results in a dimensional drag value equal to
the thrust available. For steady level flight, we graphed
the critical drag coefficient against the actual drag
coefficient as a function of airspeed. Figure 7B shows
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Figure 7: Flight Envelope
Figure 9: A) Power B) Propeller Efficiency C) Wind Tunnel Thrust D) Ecalc Thrust
that our drag coefficient is below the critical coefficient for all airspeeds in our flight envelope.
The Avionics and Propulsion sub-team used MATLAB to create a motor and propeller matching
program to compare the performance of different combinations of motors and propellers. We used APC
brand propellers for design and testing because of their standardized reported data and consistency in
production. Using polynomial interpolation, we modelled propeller and motor torques as a function of
RPM using manufacturer data (Massachusetts). We iterated through this process for each airspeed to
select the best combinations of propeller diameters, as compared in Figures 9D and 9B.
The available and required power are plotted in Figure 9A using data collected from wind tunnel
testing. The optimized airspeed for maximum power efficiency is approximately 31 mph. Using
efficiency data from Figure 9B we showed the 27β propeller to be 5.5 % more efficient than the 26β. For
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this reason, the SK3 6374-149KV motor and APC Electric E 27β x 13β propeller combination without a
spinner was chosen for the final selection.
The Stability and Controls sub-team used hand-calculations, XFLR5, and DATCOM models to
make preliminary empennage and control surface sizing decisions by calculating various derivatives.
We ensured that these derivatives compared favorably with those of the Cessna 172 and last yearβs
plane, as seen in Section 5.2.2. We also wrote MATLAB scripts to model downwash on the tail using
vortex lattice and lifting line techniques in order to validate effective AOA calculations and correct for
loss in tail efficiency due to downwash gradient. Furthermore, we tested empennage sizing decisions by
calculating moments needed to rotate the plane upon take-off and maintain dynamic stability in flight, as
seen in Equations 4 and 5 in Appendix C. These calculations resulted in an increase in the negative
incidence angle on the horizontal tail to -4ΒΊ and a forward shift of the main landing gear by 4.15β [RCA:
Take-off Distance Failure - I:240]. Successful flight testing showed that these design changes enabled
desirable stability and maneuverability characteristics.
5.2. Performance Analysis
5.2.1. Runway/Launch/Landing Performance
The motor is mounted at 2Β° to the right of the centerline of the fuselage. This thrust vector
creates a positive yawing moment that counteracts the moment created by the prop-wash during takeoff.
The prop-wash moment is largest at high thrust and low speed, so the motor mounting angle was
calculated using the static thrust and minimum takeoff velocity. P-factor, an asymmetric blade effect,
causes a negative yawing moment at low speeds and high angles of attack. Since our aircraft has tricycle
landing gear, the angle of attack remains small until after liftoff allowing this moment to be neglected
during takeoff [RCA: Gyroscopic Moments - VII:70]. To cancel an unwanted longitudinal pitching
16
moment, we mounted the motor 7Β° upward relative to the centerline of the fuselage to ensure the thrust
line goes through the center of gravity.
5.2.2. Flight and Maneuver Performance
The required servo torque for each surface was calculated using thin airfoil theory in a
MATLAB program. We assumed each control surface to be a flat plate deflected to 10Β°. The hinge
moment coefficient is found using Equation 6 in Appendix C. The required servo torque is found using
the hinge moment coefficients, dynamic pressure, surface dimensions, and pushrod geometry.
We chose Spektrum servos because they were the most consistent, economical, and lightweight
servos that provide the required torque. The
A5060 was selected for the ailerons, the
A4030 for the rudder and elevator, and the
A6150 for the nose gear [RCA: Servo
Failure - VI:36].
The team sized the control surfaces
using historical reference data for similar
aircrafts to obtain the control-surface to
wing/stabilizer area and chord ratios. The values were then revised based on spar placement
requirements and control derivative calculations in order to emulate the controllability of the Cessna 172
and last yearβs plane. The Cessna 172 was chosen because it is an industry standard as a beginner
aircraft and is stable and responsive such that it does not require exceptional pilot skills. The team
designed the elevator to be one continuous piece equal to the span of the horizontal stabilizer, allowing
for only one servo to control the elevator [KPP VII]. Necessary structural supports limited the relative
chord ratio of the elevator to 42% and the aileron to an average of 41% of the horizontal stabilizer and
Table 4: Comparison of S&C Derivatives
17
Figure 10: Downwash on Empennage
wing chord, respectively. The control power for all the control surfaces were proven sufficient during
flight testing.
A trade study was conducted to determine the wing mounting location and dihedral. A mid-
mount wing was chosen to increase passenger capacity by four and reduce conflicting geometry of
fastening hardware through the ball tray of the wing to the fuselage. The wing location is designed to
enclose the passengers above the wing mount plate and isolates passenger luggage below the wing
mount plate as per the competition rules [KPP VII]. The team decided to add dihedral because it
decreased the rolling moment coefficient from -0.013 to -0.083. A dihedral starting at the root would not
have been feasible using a hard-mount wing jig. To avoid breaking up the wing into discrete sections
and creating stress concentrations, an exponential dihedral of 5Β° was designed and manufactured. The
team found the roll stability to be sufficient (πΆππ½of -0.083 as compared to -0.089 of a Cessna 172) after
analyzing the aircraft with the new dihedral angle [RCA: Insufficient Roll Damping- VII:60].
5.2.3. Shading/Downwash
Analysis shows the horizontal stabilizers on the T-tail were outside more downwash than the
Standard tail, shown in Figure 10. This meant that the horizontal stabilizers generated less drag for the
same size stabilizers on the T-tail than on the Standard tail. There were
two major downsides, however: 1) the structure needed to hold the
empennage surfaces was heavier for the T-tail than for the Standard tail,
and 2) at high angles of attack, the separated airflow coming off of the
wing can pass over the elevators and render them ineffective, inducing a
deep stall leading to a departure from controlled flight, as seen in Figure
10. The deep stall effect was particularly troublesome in our case because our aircraft has little altitude
and time to recover from any loss of elevator control, and previous NASA research efforts (Taylor and
18
Figure 11: Effective Rudder Area (Roskam, III)
Figure 12: Smoke Testing to Reveal Wing Tail Interaction
Ray) were unable to find a suitable remedy other than avoiding parts of the flight envelope that could
lead to deep stall or departure. Ultimately, we chose the Standard tail for our aircraft. The Standard tail
had some distinct advantages over the other tail designs, namely
that the empennage surfaces were in line with the propeller,
increasing the dynamic pressure ratio at the tail and the
effectiveness of each surface. The Standard tail, was also simpler to
design and build than the other tail designs [KPP VII]. We decided
to place the horizontal stabilizer behind the vertical stabilizer to
prevent the reduction in effective rudder area as a result of the wake
from the horizontal stabilizer, as seen in Figure 11.
Initially, the Stability and Controls sub-team overestimated the static margin and undersized the
horizontal tail. This was caused by our vortex lattice code underestimating downwash and dynamic
pressure drop over the tail. However, smoke testing revealed that the tail was experiencing a significant
amount of downwash, as seen in Figure 12.
Moreover, the wind-tunnel test results showed us that we had a πΆππΌ of 0.14 and -5% static
margin, as seen in Figure 13B. Realizing that this is highly undesirable, the team analyzed smoke testing
results and found that shifting the wing from a high-mount location to a mid-mount location put the
wing and tail in approximately the same z-plane and increased the downwash over the tail [KPP VI].
At this point, we revised our downwash and tail efficiency calculations until the analytical values
19
Table 5: Static Margin Comparison
matched with experimental values from wind-tunnel data. We found that our true downwash gradient
was 0.56 and tail dynamic pressure ratio was 0.85. We used the revised downwash and tail efficiency
values to increase the size of the horizontal tail by 33%, move the horizontal tail lower on the fuselage,
and shift the center of gravity forward by 0.77β such that we ended up with a static margin of 9.10%.
We also conducted a trade study to evaluate the risk of reducing static margin in order to lower trim
drag, and found that by reducing the static margin by 3%, we were able to reduce trim drag by 0.1 lbs
[RCA: Reduced Static Margin β VII-40]. This, in addition to successful flight testing, allowed us to feel
confident about our low static margin (relative to last yearβs plane). A summary of static margins can be
seen in Table 5.
5.2.4. Dynamic & Static Stability
Our aircraft stability and control derivatives are compared to a Cessna 172, seen in Section 5.2.2.
All lateral and most longitudinal modes fell well within Level 1 (MIL-F-8785C). Short period natural
frequency is a Level 3. We decided that the risk of a Level 3 natural frequency would be acceptable for
short flights and for an RC aircraft, provided the damping is sufficient and the pilot is warned prior to
Figure 13: Wind Tunnel data for A) πͺππΉπ π©) πͺππΆ
20
flight. Settling for a Level 3 allowed us to have a smaller tail size, and hence, reduce weight and drag,
making the plane more competitive [KPP III]. Pilot feedback after successful flight testing indicated that
the aircraft could be comfortably controlled, trimmed, and was easy to fly. Damping ratios are
summarized below in Table 6 [RCA: Insufficient Dynamic Stability - VII:180].
5.2.5. Aeroelasticity
We calculated the local span wise lift coefficient using a vortex panel code. We then discretized
the wing into small areas, and calculated the total lift per unit span at various angles of attack. The area
under each curve in Figure 14B is the predicted lift at the cruise speed. The team used these values to
size the spars and chose the geometry for the given loading condition. Under a 2G turning procedure, the
wing must withstand a 140 lbs distributed load.
The wing was analyzed as a cantilever beam with a fixed boundary condition at the root section
of the fuselage. The spar caps are placed tangent to the airfoil surface in order to maximize the second
moment of area, ultimately strengthening the wing in both bending and shear. Under a maximum
operating lift distribution of 10ΒΊ AOA, the wing tip is predicted to deflect 4.3β as seen in Figure 15B.
Figure 14: A) Torsional Loading B) Lift Distribution
Table 6: Flying Modes
21
The local pitching moment of the wing is calculated using a vortex lattice model. The torsional
moment due to lift is calculated by multiplying the local lift vector by the distance from the center of
pressure to the shear center located at approximately 11% of the chord. The net torsional loads on the
wing are calculated by summing the moment due to lift and the pitching moments, seen in Figure 14A.
The structural design team evaluated an operating condition angle of twist for the wing tip to be -0.072ΒΊ
during level flight using thin walled torsion theory as seen Figure 15A.
During the build-phase, the team added medical tape to close the gaps between elevator hinges in
order to prevent airflow between the stabilizer and control surface, and thereby reduced the possibility of
flutter. No indication of flutter was seen during flight testing; therefore, the structures of the aircraft
were determined to be sufficiently rigid.
5.2.6. Lifting Performance, Payload Prediction, and Margin
The flight model predicts successful take off in 170 ft with a maximum gross weight of 50 lbs as
seen in Figure 6D. The model was used with wind speeds ranging from 0 to 15 mph. For high wind
speeds, a cruise angle of attack of 7Β° is required to maintain enough lift during a tail wind phase of
flight. For low wind speeds, a 7Β° rotation will be required to take off in 200 ft. The team will only fly at
a gross weight of 46.5 lbs. This reduction in payload gives a 10% margin of safety, which gives the team
full confidence that we can consistently fly all flight rounds validated through flight testing [KPP I]
Figure 15: A) Wing Tip Angle of Twist B) Wing Tip Linear Deflection at 10ΒΊ AOA
22
Figure 16: Spar Cap Taper Decrement
[RCA: Incorrect Payload Prediction - I:50]. The empty weight of the plane is 13.5 lbs, the inert payload
is 25.5 lbs, and the 51 passengers weigh 6.5 lbs.
5.3. Structural Analysis
The determining factor for wing box geometry was driven by the wing bending failure mode
which possessed the lowest margin. The critical margins for the aircraft may be seen in Table 7.
5.3.1. Applied Loads and Critical Margins Discussion
The structural analysis of the aircraft is a combination of Euler-Bernoulli beam theory and
closed-thin walled torsional analysis. The wing was analyzed
as a cantilever beam with all bending stresses taken in the
spar caps and all shear stresses taken by the spar webbing.
The primary structural element of the wing is a two-spar cap
system incorporating a trapezoidal taper along the span for
aerodynamic considerations, shown in Figure 16. The wing
box was designed using a 1.5 factor safety to account for
material inconsistencies and unexpected flight patterns.
The smooth leading-edge surface is made of a 1/32β
thick balsa wood sheets with the grain direction parallel the wingspan, thereby efficiently utilizing the
Table 7: Aircraft Structural Margins
23
Figure 17: Material Breakdown
bending characteristics of the material. To prevent the skin from sagging between ribs, the team
increased the stiffness of the wing at the stagnation point by adding a span wise leading-edge stringer.
Given an elliptic lift distribution, the required second moment of area for the wing spar caps decreases
as a function of the wingspan. After
noting this trend, the Structures sub-
team implemented a sequential spar
decrement to reduce the aircraft weight
and improve the bending characteristics,
as seen in Figure 16 [KPP V]. Webbing
thickness decreases along the span of
the aircraft due to similar shear stress
patterns and the required first area-
moment of the webbing.
The wing mounting plate located at the interface between the wing and fuselage is the primary
load bearing element. This component must withstand a static weight of the 25.5 lbs luggage payload
and the maximum condition of 3G impact upon landing. The team applied a factor of safety of 2 for this
component, because of the potential to nullify a flight round score [RCA: Mount Plate Fracture IV-560].
The mounting plate contains a lightweight foam core to increase the second area-moment and plywood
on the outer surface to decrease mass and increase bending stiffness.
The truss structure consists of square cross sectioned members of balsa. To design the structure,
the fuselage was constructed in ANSYS using beam elements that allowed iterations between different
truss designs. Using method of joints, critical members were checked to confirm our FEM. The stresses
on the aft fuselage members were analyzed assuming a two pound distributed load applied at the
24
elevator and a 1.25 pound rudder load. The team assumed a worst case 3-point landing where the nose
gear takes a maximum 3G loading with 20% of the aircraft total weight. We sized the nose truss
members by checking for large deflections, stresses exceeding material allowables, and buckling. The
team used a buckling factor of safety of 2 on the fuselage because of a variety of quality in the balsa
members.
5.3.2. Mass Properties
The Structures sub-team selected materials based on component failure risk. The materials
selection for the competition aircraft may be seen in Figure 17. The Structures sub-team selected
basswood for aircraft components that must hold primarily bending loads due to the materialβs large
specific strength of 20943 kip-in/slug
and ultimate strength required for
wing loading. The team chose
lightweight balsa wood for the
fuselage truss members because it has
a large specific strength of 17444 kip-
in/slug but did not require the
necessary ultimate strength and additional mass as that of the wing. The team tensile tested the
basswood used for spar caps as seen in Figure 18, and discovered a larger ultimate strength of 797 psi
than predicted value of 537 psi in the wood engineering handbook (Risbrudt).
6.0 Assembly and Subassembly, Test and Integration
Assembly and integration of major subsystems such as wing to fuselage, horizontal and vertical
tails into the empennage, and landing gear to the fuselage are discussed in Sections 3.3 and 3.4. The
fully assembled plane, in flight, can be seen in Figure 19.
Figure 18: Tensile Testing of Basswood
25
Figure 19: Texas A&M SAE Plane in Flight
The wiring and servos had to be
installed to avoid interfering with the removable
wing. The wiring harness running from servos
in the empennage of the plane stayed low in the
fuselage and were glued in place just short of
the nose. By gluing these wires in place, we
were able to ensure the empennage servos and
the motor were easily accessible for arming and disarming [RCA: Injury During Flight Testing -
VIII:50]. Furthermore, it ensured there was no excess wire in the system. The wing servo wiring
harnesses run over the top of the wing mount plate with enough length to reach their respective arming
plugs. The battery and receiver are secured with Velcro to structural members in the nose of the plane.
Flight testing was conducted on the first prototype of the plane [KPP VIII]. This testing proved
that our S&C calculations were correct and validated our payload prediction. A hard nose gear landing
on the third flight revealed minor structural issues that were resolved through substituting basswood for
balsa in certain stress concentration areas.
7.0 Manufacturing
High accuracy SolidWorks models of the wing incorporated the dihedral and geometric twist
specified by our Aerodynamics sub-team. We constructed the wing from ribs mounted to a jig. We cut
both the ribs and jigs with a CNC laser, which has a tolerance of .001β, to ensure high accuracy and ease
of manufacturing [KPP IV]. We then constructed the wing mounting plate from a section of foam
epoxied between two sheets of 1/16β birch plywood, which we then fit into slots between the root ribs to
minimize the outer mold line tolerance. To construct the leading and trailing edges, we curved thin balsa
sheets around the wing, which we then secured to the ribs with cyanoacrylate (CA) glue. This skin
26
allows the wing Monokote to follow the shape of our airfoil across the leading and trailing edges, which
also minimizes our outer mold line tolerance. We then set the spars into notches already cut into the ribs
by the CNC laser and glued them in while they were still on the jig to allow the wing to maintain its
dihedral and geometric twist. Throughout the manufacturing process, the team used pipettes to apply
glue to the plane, then sanded excess glue to reduce weight. The ribs and jigs for the control surfaces
were also cut with a CNC laser. They were then skinned, layered with Monokote, and hinged to the
trailing edge of the wing and empennage ribs.
The team also utilized a jig to build the fuselage truss, which allowed us to decrease the outer
mold line tolerance of our plane. This jig was made of multiple MDF (Medium Density Fibreboard)
sheets that have CNC laser-etched cutouts for the truss members, which allowed the team to place and
glue the members. The fuselage jig can be seen alongside the wing jig in Figure 20.
Figure 20: Wing and Fuselage Jig
27
8.0 Conclusion
The major design decisions of our plane were driven by KPPs and RCAs. First, the team added a
10% payload margin to ensure flight consistency [KPP I]. The team designed to an elliptic lift
distribution to aid in maximizing lift per unit weight [KPP II]. We designed the smallest tail and
fuselage possible while still allowing a carrying capacity of 51 passengers [KPP III]. The team utilized a
CNC laser machine to precision cut wing and tail components [KPP IV]. Weight was reduced through
material selection, tail sizing, lighter flight components, and strategic cutouts [KPP V]. The fuselage
wing joint, moveable payload mechanism, and detachable wing provides ease of use [KPP VI]. The
team constructed a straight leading edge and continuous control surfaces [KPP VII]. The use of
empirical testing allowed us to mitigate risks and to validate flight model predictions [KPP VIII].
Through multiple design iterations we were successful in creating a strong, consistent aircraft that we
feel confident will perform well at competition.
28
Appendix B- References
Budynas, Richard G., et al. Shigley's Mechanical Engineering Design. McGraw-Hill, 2011.
KasnakoΔlu, CoΕku. (2016). Investigation of Multi-Input Multi-Output Robust Control Methods to Handle Parametric
Uncertainties in Autopilot Design. PLOS ONE. 11. e0165017. 10.1371/journal.pone.0165017.
Leishman, Gordon J. Principles of Helicopter Aerodynamics. Cambridge University Press, 2006.
Lewis,David. βCovering Weights.β Covering Weights (Sorted by Weight), www.homefly.com
Massachusetts Institute of Technology, βPerformance of Propellers.β
Risbrudt, Christopher. Wood Handbook: Wood as an Engineering Material. Forest Products Soc., 2011.
Roskam, Jan. Airplane Design. DARcorporation, 1985.
Taylor, Robert T. and Edward J. Ray. βA Systematic Study of the Factors Contributing to Post-Stall Longitudinal Stability of
T-Tail Transport Configurations.β NASA Langley Research Center, Hampton,VA: Los Angeles, 1965.
United States, Congress, βMIL-F-8785C.β MIL-F-8785C, 1980. Linkopings University,
www.mechanics.iei.liu.se/edu_ug/tmme50/8785c.pdf.2017
Appendix C: List of Symbols
AOA- Angle of Attack
BEC- Battery Eliminator Circuit
CA- Cyanoacrylate
CFD- Computational Fluid Dynamics
CG- Center of Gravity
πΆππ½ - Lateral Stability Derivative
πΆππΏπ - Aileron Effectiveness
Derivative
πΆππ - Roll Damping Derivative
πΆππ- Longitudinal Stability
Derivative
πΆππΏπ - Elevator Effectiveness
Derivative
πΆππΌ β Pitching Coefficient w/
Angle of Attack
πΆππ½- Lateral Stability Derivative
CNC- Computer Numerical Control
πΆππΏπ - Rudder Effectiveness
Derivative
πΆππ - Yaw Damping Derivative
ESC- Electronic Speed Control
FEM- Finite Element Method
FSS- Final Flight Score
KPP- Key Performance Parameters
MDF- Medium Density Fibreboard
MPH- Miles per Hour
RAP- Risk Analysis Parameter
RC- Radio Controlled
RCA- Risk Code Analysis
RPM- Rotations per Minute
RPN- Risk Priority Number
29
Appendix D: List of Equations
Equation 2:
Equation 3: 140π
[β $100π + 50πΆ β $100πΈ]π1
Equation 4: πβππππππ π‘π πππ‘ππ‘π =βπ§πβπ+π§π·βπ·+πβ(π₯ππβπ₯ππ+ππβπ§ππ)βπΏπ€πβ(π₯ππβπ₯πππ€π+ππβπ§ππ)βπΆππππ€π
βοΏ½Μ οΏ½βππ€πππβπ+Μ πΌπ¦π¦ππβοΏ½ΜοΏ½
οΏ½Μ οΏ½β(π₯ππβπ₯ππβ+ππβπ§ππ)βπΆπΏβmax
Equation 5: πβππππππ π‘π π‘πππ =βπ§πβπ+π§π·βπ·+πβ(π₯ππβπ₯ππ)βπΏπ€πβ(π₯ππβπ₯πππ€π)βπΆππππ€π
βοΏ½Μ οΏ½βππ€πππβπΜ
οΏ½Μ οΏ½β(π₯ππβπ₯ππβ)βπΆπΏβcruise
Equation 6: πΆβ = βπΌ[πππ πβπΌ1 β πΌ2] β Ξ·[(1 β πβ
π) (πππ πβπΌ1 β πΌ2) + β (πππ πβπΌ3 β πΌ4)β
π=1
Equation 7: πΉπ = 125 βπππ βππΈβπΆπΈπ₯π‘ππβπΏπ’πππππβππππ
ππΆ
0.5βππππππΆ + ππππ
ππππ π ππππππ β
πππππ π ππππππ ππ#πππ π ππππππ
+ 50 β πΆπΈπ₯π‘ππβπΏπ’πππππ β 100πΈ
Appendix E: Technical Data Sheet
Payload=-0.0018x+33
This plot is discussed in Section 4.2
30
Appendix F: 11x17 D
rawing