Document
Statistical Wind - Tunnel Experimentation
Advancements for eVTOL Aircraft
Aero - Propulsive Model Development
Benjamin M. Simmons and Ronald C. Busan Flight Dynamics Branch NASA Langley Research Center AIAA SciTech Forum 08 – 12 January 2024
Contents
• Research motivation
• RAVEN background
• Static wind - tunnel testing
▪ Gravitational tare modeling ▪ Trim envelope determination ▪ Powered - airframe characterization
• Concluding remarks
• Questions/discussion
NASA RAVEN - SWFT wind - tunnel testing.
Software: ® • Design - Expert • SIDPAC Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 2
Research Motivation
• Distributed propulsion aircraft enabling Advanced Air Mobility (AAM) missions ▪ VTOL, STOL, and CTOL configurations ▪ Many control surfaces and propulsors ▪ Significant propulsion - airframe interactions • Conventional methods fail to efficiently NASA GL - 10 aircraft characterize complex aircraft • Design of experiments (DOE) and response surface methodology (RSM) are essential • Advance DOE/RSM strategies for characterization of complex aircraft • Aero - propulsive modeling for a new electric vertical takeoff and landing (eVTOL) aircraft NASA LA - 8 aircraft Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 3
RAVEN eVTOL Vehicle
• RAVEN – R esearch A ircraft for e V TOL E nabling Tech N ologies • Tilt - rotor eVTOL configuration with six variable - pitch proprotors • Vehicles at different scales • 24 independent control effectors ▪ Six proprotor speeds ( 𝑛 , 𝑛 , … , 𝑛 ) 1 2 6 ▪ Six collective angles ( 𝛿 , 𝛿 , … , 𝛿 ) 𝑐 𝑐 𝑐 1 2 6 ▪ Four nacelle tilt angles ( 𝛿 , 𝛿 , 𝛿 , 𝛿 ) 𝑡 𝑡 𝑡 𝑡 1 2 3 4 ▪ Six flaperons ( 𝛿 , 𝛿 , … 𝛿 ) 𝑓 𝑓 𝑓 1 2 6 ▪ Stabilator ( 𝛿 ) 𝑠 ▪ Rudder ( 𝛿 ) 𝑟 • Built for modeling/controls research 1. German, B. J., Jha, A., Whiteside, S. K. S., and Welstead, J. R., “Overview of the Research Aircraft for eVTOL Enabling techNologies (RAVEN) RAVEN control effector definitions.
Activity,” AIAA AVIATION Forum , AIAA Paper 2023 - 3924, June 2023.
Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 4 SWFT = S ubscale W ind - Tunnel and F light T est
RAVEN - SWFT Vehicle
• Wind - tunnel and flight - test research • Similar in scale and utility to the NASA LA - 8 • 28.6% scale version of 1000 - lb vehicle • 37 lbs , 5.7 ft wingspan, 19.5 in diam. proprotors Transition Cruise Hover Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 5
RAVEN - SWFT Wind - Tunnel Testing
Langley 12 - Foot Low - Speed Tunnel Static Full - Airframe Test Phases • Isolated proprotor test • Gravitational tare modeling • Static full - airframe test • Trim envelope determination • Dynamic testing (in progress) • Powered - airframe characterization Benefits • Flight simulation development • Flight control system design • Validation of prediction tools Proprotor Powered - airframe • Data/models that can be published RAVEN - SWFT wind tunnel tests.
1. Simmons, B. M., “Efficient Variable - Pitch Propeller Aerodynamic Model Development for Vectored - Thrust eVTOL Aircraft,” AIAA AVIATION Forum , AIAA Paper 2022 - 3817, June 2022.
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Gravitational Tare Characterization
• Internal strain - gage balance measures: Test time reduced by nearly 50% ▪ Aero - propulsive forces and moments ▪ Gravitational loads (i.e., aircraft weight) • Gravitational loads must be removed • Tare runs require additional test time • eVTOL aircraft have large moving components • Previous testing required many tare points • New gravitational tare modeling approach ▪ Application of DOE/RSM techniques ▪ Powered - airframe test factors: 𝛼 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 𝑡 𝑡 𝑡 𝑡 𝑓 𝑓 𝑠 1 2 3 4 1 6 ▪ 𝐼 - optimal response surface design (130 total points) ▪ Model identified to predict gravitational loads 2D slice of the 8 - factor tare ▪ Obviates most required tare test time experiment design.
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Gravitational Tare Model Validation
Isolated - airframe angle - of - attack sweep data collected
at ഥ 𝒒 = 3.5 psf using a traditional and modeled tare.
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Transition Trim Envelope Determination
Trim Envelope Determination Strategy • Proper design space limits are • Progressive testing (increasing airspeed) important for transition characterization • Identify response surface equations • Find control effector settings where: • Specifying boundaries around the trim o Lift = Aircraft Weight = 37 lbf envelope is an effective approach o Horizontal Thrust – Drag = 0 lbf o Pitching Moment = 0 ft - lbf • The trim envelope was determined • Free control variables: manually in previous wind - tunnel tests o Front collective ( 𝛿 ) 𝑐 front o Rear collective ( 𝛿 ) 𝑐 rear • New trim approach using DOE/RSM o Nacelle tilt ( 𝛿 ) 𝑡 ▪ Efficient, accurate, and mostly automated • Fixed control variables (swept): ▪ Testing with a reduced number of factors o Proprotor rotational speed ( 𝑛 = 𝑛 ) front rear o Outboard flaperon angle ( 𝛿 ) 𝑓 out ▪ Level, unaccelerated transition envelope o Inboard flaperon angle ( 𝛿 ) 𝑓 in ▪ Results inform subsequent aero - propulsive • Root - finding algorithm finds trim solutions characterization experiments • Near - real - time analysis capabilities Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 9
Trim Envelope Determination Experiment
• Eight dynamic pressure, ത 𝑞 , settings (low → high) • Testing up to the highest attainable ത 𝑞 • Seven test factors/explanatory variables: 1. Front motor command/rotational speed ( 𝑛 ) front 2. Rear motor command/rotational speed ( 𝑛 ) rear 3. Front collective pitch angle ( 𝛿 ) 𝑐 front 4. Rear collective pitch angle ( 𝛿 ) 𝑐 rear 5. Nacelle tilt angle ( 𝛿 ) 𝑡 6. Outboard flaperon deflection angle ( 𝛿 ) 𝑓 out 7. Inboard/ midboard flaperon deflection angle ( 𝛿 ) 𝑓 in • Frugal design strategy (56 points per ത 𝑞 setting) • 𝐼 - optimal response surface design 2D slice of the 7 - factor trim experiment design in coded units.
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Experimentally - Determined Trim Envelope
Nacelle Proprotor Tilt Angle rotational speed Rear Front Collective Collective Angle Angle 𝛼 = 𝛽 = 0° 𝛿 = 𝛿 = 0° 𝑠 𝑟 Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 11
Powered - Airframe Characterization
• Informed by the transition trim envelope determination results • Powered - airframe testing from hover through mid - transition • Eight dynamic pressure, ത 𝑞 , settings • 26 independent test factors at each ത 𝑞 setting ▪ Angle of attack ( 𝛼 ) ▪ Angle of sideslip ( 𝛽 ) ▪ Motor speed commands ( 𝜂 , 𝜂 , … , 𝜂 ) 𝑚 𝑚 𝑚 1 2 6 ▪ Collective pitch angles ( 𝛿 , 𝛿 , … , 𝛿 ) 𝑐 𝑐 𝑐 1 2 6 ▪ Nacelle tilt angles ( 𝛿 , 𝛿 , 𝛿 , 𝛿 ) 𝑡 𝑡 𝑡 𝑡 1 2 3 4 ▪ Flaperon deflection angles ( 𝛿 , 𝛿 , … 𝛿 ) 𝑓 𝑓 𝑓 1 2 6 ▪ Stabilator deflection angle ( 𝛿 ) 𝑠 ▪ Rudder deflection angle ( 𝛿 ) 𝑟 • Nested 𝐼 - optimal design (984 points per ത 𝑞 ) 1. Simmons, B. M., “Evaluation of Response Surface Experiment Designs for Distributed Propulsion 2D slice of the 26 - factor experiment Aircraft Aero - Propulsive Modeling,” AIAA SciTech Forum , AIAA Paper 2023 - 2251, Jan. 2023.
design in coded units.
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RAVEN - SWFT Wind - Tunnel Testing Video
Static RAVEN - SWFT DOE/RSM wind - tunnel testing (x20 speed).
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Powered - Airframe Model Identification
• Aero - propulsive modeling framework tailored to eVTOL aircraft ത 𝑞 , 𝑣 , 𝑤 • Flight condition variable: dynamic pressure ത 𝑞 (or freestream velocity 𝑉 ) 𝑛 , 𝑛 , … , 𝑛 1 2 6 • Explanatory variables: 𝛿 , 𝛿 , … , 𝛿 𝑐 𝑐 𝑐 1 2 6 𝑢 effects are captured by models being ▪ Body - axis velocity components ( 𝑣 , 𝑤 ) 𝛿 , 𝛿 , 𝛿 , 𝛿 𝑡 𝑡 𝑡 𝑡 developed at multiple ത 𝑞 settings 1 2 3 4 ▪ Proprotor rotational speeds ( 𝑛 , 𝑛 , … , 𝑛 ) 1 2 6 𝛿 , 𝛿 , … 𝛿 𝑓 𝑓 𝑓 1 2 6 ▪ Control deflection angles ( 𝛿 , 𝛿 , … , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , 𝛿 , … 𝛿 , 𝛿 , 𝛿 ) 𝑐 𝑐 𝑐 𝑡 𝑡 𝑡 𝑡 𝑓 𝑓 𝑓 𝑠 𝑟 1 2 6 1 2 3 4 1 2 6 𝛿 , 𝛿 𝑠 𝑟 • Response variables: ▪ Dimensional body - axis aero - propulsive forces ( 𝑋 , 𝑌 , 𝑍 ) ▪ Dimensional body - axis aero - propulsive moments ( 𝐿 , 𝑀 , 𝑁 ) Aero - Propulsive • Nonlinear response surface equations (RSEs) developed at each ത 𝑞 Model ▪ Model structure determination: stepwise regression ▪ Parameter estimation: ordinary least - squares regression 𝑋 , 𝑌 , 𝑍 , 𝐿 , 𝑀 , 𝑁 • Continuous transition model formed by interpolating between RSEs 1. Simmons, B. M., and Murphy, P. C., “Aero - Propulsive Modeling for Tilt - Wing, Distributed Propulsion Aircraft Using Wind Tunnel Data,” Journal of Aircraft , Vol. 59, No. 5, 2022, pp. 1162 – 1178.
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Sample Local Modeling Results
• 𝑍 RSE at ത 𝑞 = 2.75 psf compared to axial and center wind - tunnel data points • RSE predictions show good agreement with measured data • Data are within the 95% prediction interval (PI) • Similar results observed for other response variables and ത 𝑞 settings • Sample residual diagnostics plots are shown in the paper Model and wind - tunnel data comparison for explanatory variable sweeps ( ഥ 𝒒 = 2.75 psf).
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Sample Global Modeling Results
𝟐 Coefficient of determination, 𝑹 , for each local model.
Modeling/validation normalized root - mean - square error (NRMSE) for each local model.
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Concluding Remarks
• eVTOL aircraft present new aero - propulsive modeling challenges • DOE/RSM techniques enable accurate characterization of complex aircraft • Multiple advances in efficient eVTOL aircraft wind - tunnel testing ▪ Gravitational tare experiment design and modeling approach ▪ Experimental transition trim envelope determination strategy ▪ Powered - airframe testing conducted using the nested 𝐼 - optimal design • Final aero - propulsive models have good predictive capability • Techniques can be applied for many current and future eVTOL vehicles • Active research is further refining eVTOL vehicle modeling techniques • RAVEN project – strong emphasis on public release of data/technology Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 17
Look Ahead: NASA Langley FDRF
• Flight Dynamics Research Facility (FDRF) • Scheduled to open in January 2025 • Replacing, combining, and expanding capabilities of the: ▪ 20 - Foot Vertical Spin Tunnel (VST) ▪ 12 - Foot Low - Speed Tunnel (LST) FDRF construction progress (Dec. 19, 2023) 20 - Foot VST 12 - Foot LST Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 18 Questions/Discussion – Thank you for attending.
Acknowledgments • Funding: NASA Aeronautics Research Mission Directorate (ARMD) Transformational Tools and Technologies (TTT) Project • Wind - tunnel test support: Wes O’Neal, Clinton Duncan, Rick Thorpe, Earl Harris, Lee Pollard, Sue Grafton • RAVEN - SWFT vehicle support: Greg Howland, Matt Gray, Neil Coffey, Steve Geuther, Dave North • RAVEN project support: Kasey Ackerman, Jake Cook, Steve Riddick, Siena Whiteside, Jason Welstead, Nat Blaesser • Gravitational tare modeling integration and validation support: Stephen Farrell and Wes O’Neal Related eVTOL Aircraft Modeling and RAVEN - SWFT References 1. Simmons, B. M. and Murphy, P. C., “Aero - Propulsive Modeling for Tilt - Wing, Distributed Propulsion Aircraft Using Wind Tunnel Data,” Journal of Aircraft , Vol. 59, No. 5, 2022, pp. 1162 – 1178.
2. Simmons, B. M., Geuther, S. C., and Ahuja, V., “Validation of a Mid - Fidelity Approach for Aircraft Stability and Control Characterization,” AIAA AVIATION Forum , AIAA Paper 2023 - 4076, June 2023.
3. Simmons, B. M., “Evaluation of Response Surface Experiment Designs for Distributed Propulsion Aircraft Aero - Propulsive Modeling,” AIAA SciTech Forum , AIAA Paper 2023 - 2251, Jan. 2023.
4. Simmons, B. M., “Efficient Variable - Pitch Propeller Aerodynamic Model Development for Vectored - Thrust eVTOL Aircraft,” AIAA AVIATION Forum , AIAA Paper 2022 - 3817, June 2022.
5. Busan, R. C., Murphy, P. C., Hatke , D. B., and Simmons, B. M., “Wind Tunnel Testing Techniques for a Tandem Tilt - Wing, Distributed Electric Propulsion VTOL Aircraft,” AIAA SciTech Forum , AIAA Paper 2021 - 1189, Jan. 2021.
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Backup Slides
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RAVEN - SWFT Modeling and Controls
Flight Testing Validation RAVEN - SWFT RAVEN SWFT Wind - Tunnel Testing Flight Dynamics Model Flight Control Validation System Computational Predictions Development Research Advancement and Toolchain Validation Enabled by RAVEN - SWFT 1000 - lb RAVEN Industry Simmons and Busan, NASA Langley AIAA SciTech 2024 Forum 21
Gravitational Tare Model Validation
RSE = Response Surface Equation PI = Prediction Interval
Gravitational tare voltage data and model predictions for an
ഥ
isolated - airframe angle - of - attack sweep data at 𝒒 = 3.5 psf.
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Powered - Airframe Experiment Design
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Powered - Airframe Experiment Design
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Powered - Airframe Experiment Design
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Powered - Airframe Modeling Results
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Powered - Airframe Modeling Results
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