AERODYNAMICS and AEROELASTICITY METHODOLOGIES for FUTURE CONCEPTS in VERTICAL LIFT Marilyn J

AERODYNAMICS AND AEROELASTICITY METHODOLOGIES FOR FUTURE CONCEPTS IN VERTICAL LIFT Marilyn J. Smith, PhD Professor Director, Vertical Lift Research Center Georgia Institute of Technology Atlanta, GA US

Oct 15, 2019 Aerodynamics Tools and Methods in Aircraft Design The Evolution of Modern Vertical Lift Design

Tail Rotor

Main Rotor

Empennage

Fuselage

https://www.lockheedmartin.com/en-us/products/sikorsky-black-hawk- helicopter.html Aeromechanics of a Traditional Helicopter

Rotor Fuselage Interactions Dynamic Stall • Vibration V∞ • Loads • Performance

Rotor-Wake Interactions

W • Vibration • Noise FXC • Loads • Performance

Tail-rotor Transonic Flow Interactions With: • Empennage • Main Rotor M > 1 • Main-Rotor Wake Fuselage Flow • Loads M < 1 Performance, Handling- • Drag • Noise Qualities • Component Loads • Performance The Evolution of Modern Vertical Lift Design

Proprotors Multiple Rotors

RecirculationMain Rotor Effects Conversion

Empennage

Fuselage

By FOX 52 - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=35908368 Vertical Lift in the 21st Century

Low Reynolds Numbers Coaxial/Corotating Rotors Unmanned Vehicles/Drones FLRAA and FARA

Shrouded/Ducted Rotors Jaunt Air Mobility Bell Flight

Distributed Electric Propulsion

Urban Air Mobility Aeromechanics Prediction Requirements • Vehicle performance • Blade loads • Airframe & drive train loads • Vibration (rotor and fuselage) UH-60F Hover • Aeroelastic stability • Flight dynamics

• Handling qualities TRAM proprotor • Noise

UH-60A forward flight Figures courtesy of US Army Aerodynamic Tools for 21st Century VL

Conceptual and Preliminary Design - NDARC - GTABB/COMPASS

Detailed Design and Engineering Analysis - Comprehensive Codes: CAMRAD, RCAS, HOST - Panel-Based Methods - Dual Solver Hybrid Methods - Adjoint Design: FUNtoFEM

Physics and High Fidelity Analysis - Helios, FUN3D, OVERFLOW - FLOWer, ELSA, TAU - Academic Codes: Liverpool/Glasgow, UMD 21st Century Aerodynamic Prediction Goals

Johnson et al., “Requirements for Next Generation Comprehensive Analysis of Rotorcraft,” AHS Specialist's Conference on Aeromechanics, San Francisco, CA, January 23-25, 2008. What Capabilities are Needed?

Multiple Core/Processor Capabilities Active Flow Control Ability to model or include the effects of New Technology New Designs

Multiple Rotors/Propellers Active Surfaces/Dampers What Capabilities are Needed? Slung Loads Multiple Core/Processor Capabilities Ability to model or include the effects of New Technology New Designs Robotic Landing Gear Incorporate the effects of Environment Urban and Nap of the Earth Near-ground Operations Large Gusts in Urban Canyons In-Flight Operations

Gust Responses: Urban Canyon Typical What Capabilities are Needed? Reduce the scope of wind tunnel testing during design and flight testing for certification

• Digital Threads • Uncertainty Quantification • Removal of User-generated Errors Quantitative Data Analysis Techniques CIFER • Developed for system identification (USRA) • Computes difference between frequency response of two datasets J= 10 40 1000

• Coherence: Linearity between response of two data sets, illuminates missed harmonics. Coh < 0.6 → missed harmonic • Cost Function: Scalar measure of difference between response of two data sets

J < 100 → Very little difference J < 50 → Virtually identical

.0 20 5 5 ) = - ! ! 21 − 2 + ! ∠21 − ∠2 & " $ 3 ( 3 ./ where !", !$, %&' !( are weighting factors for coherence, magnitude, and phase, respectively

J= 10 40 1000

Cho et al. "System Identification and Controller Optimization of a Coaxial Quadrotor UAV in Hover," AIAA, 2019 Smith et al., “Towards Certification of CFD as Numerical Experiments for Rotorcraft Applications,” Aeronautical Journal, 122(1247), 104-130. AerodynamicAerodynamics forTools Designfor Designand Modelingand & ModelingSimulation & Simulation NASA Design and Analysis of Rotorcraft (NDARC) Capabilities for: Off-design mission analysis Flight performance Vehicle sizing

Flexibility for non-conventional vehicles through Optimization with NDARC • Synthesis of component modules • Propulsion system options (electric, turbojet, turbofan, reaction drives, fuel cells, etc.) • Surrogate models for trade-space analysis

• Silva et al, “Multidisciplinary Conceptual Design for Reduced-Emission Rotorcraft,” AHS Specialists Conf., San Francisco, California, USA, January 16-18, 2018. • Johnson, “NDARC: A Tool for Synthesis and Assessment of Future Vertical Lift Vehicles,” Vertiflite, Nov- Dec, 2014, pg. 26-27. Prior slide figure from this work. A New Approach for Design and M&S : GTABB and COMPASS • Development of physics-based reduced order models for aerodynamic and bluff bodies • Extensible to new configurations: Not an interpolation • New features: Shadowing orientation effects GUI Rotor and engine effects Multiple body types • Validated with CFD, wind tunnel, and flight test • Adopted/in adoption by US Army, US Navy, Drone Racing League, academia • Slung loads • Control law and autonomous algorithm design • Virtual reality-based training (M&S)

• Prosser, D. and Smith, M. J., “Physics-Based Aerodynamic Simulation Models Suitable for Dynamic Behavior of Complex Bluff Body Configurations,” American Helicopter Society 71st Annual Forum, May, 2015. See also JAHS. • Koukpaizan et al. “Rapid Vehicle Aerodynamic Modeling for Use in Early Design,” in Proceedings of the AHS Aeromechanics Design for Transformative Vertical Flight Conference, San Francisco, CA, January 16–19, 2018 GT Aerodynamics of Bluff Bodies (GTABB)

External Control Module

17 Unsteady Aerodynamics in Real Time

• Unsteady phase lag

• Large vortex shedding No vortex fluctuations shedding • Three-dimensional effects (finite bodies)

With Captures Onset vortex of Instability shedding

US Army Blackhawk Flight Test Validation COMPlex Aerodynamic Shape Simulation (COMPASS)

• Use canonical shapes with corrections to estimate the characteristics of complex shapes. • Add corrections for shadowing (feature blockage) and shear layers

COMPASS quadrotor representation (without rotors) Nondimensional Aerodynamic Characteristics Figures from Prosser and Smith (2016)

Predict the Cp distribution about the body

Integrate to get force and moment coefficients Nondimensional Aerodynamic Characteristics

Prosser, D. and Smith, M. J., “Aerodynamics of Finite Bluff Bodies,” Journal of Fluid Mechanics, Vol. 799, No. 6, pp. 1–16, 2016, Quasi-Steady Predictions

Drag Coefficient Lift Coefficient

Typical Control Law Design: • Flat plate wetted area used for forces • Moments are neglected Vehicle Performance

30 Flat Plate 25 Unsteady FP 20

10 FP FP 5

0 (Deg) Range (Km) Flight Time (Min) trim Flat plate aerodynamics overpredicts performance by ~10% and underpredicts rotor trim by ~15% Split-S Trajectory predicted by GTABB

Height Above Ground (m) Flight Test Validation

Real Flight Vehicle

Simulated Flight Vehicle

https://www.youtube.com/watch?v=UNoGxq8pQGE, Courtesy Drone Racing League Hybrid CFD Analyses CFD + Free Wake Model

• Data is exchanged between the CFD and free wake code at fixed intervals • CFD near-body solver calculates the Wake Vortex Filaments sectional loads along the blades as the solution advances • The vortex filaments which model the wake are updated based on the sectional loads • The outer boundary conditions of the CFD domain are updated from the wake- induced flow field to reflect the influence of the wake Outer Boundary CFD Hybrid CFD Methods

• Promise of CFD-level accuracy without the costs, up to 90% savings in some cases • Many approaches through the decades, but with limitations: • Single blade • No fuselage (except DLR) • Very mixed results with significant errors in pitching moment, structural bending, and hub forces • Some have known numerical formulation errors • Many are “academic” codes without formal version control Past (US) engineering experience not positive to adoption in work flow CDI-GT Hybrid CFD Approach

• CFD/CFD-CSD provide highest accuracy at highest cost • Hybrid CFD methods mitigate costs by 50%-90% while maintaining accuracy • Increase CFD-based applications to earlier design and additional analysis

• Carefree: Couple CFD solvers with commercial wake solvers • Flexible: Takes advantage of near-body capabilities • Physics: Multiple level of physics • Cost-effective: Can use same meshes • Expanded Capabilities: Multiple components, full Cost Accuracy vehicles Non-contiguous Methodology • Remove the inertial background grids • Allow boundary motion and arbitrary boundary shapes • Velocity at all unblanked outer boundaries determined by the free wake code

Blade Vortex Interaction

Conglomeration of vortex filaments modeling the tip vortex

Illustration of tip vortex passing between domains

Contiguous vs non-continguous S-76 Hover

• Mtip = 0.65, trimmed to CT/σ=0.09 • 3.9M nodes per blade (15.4M total) • O-grid topology Noncontiguous Meshes

Hover is complex computation with significant wake interactions

Helios Predictions with OVERFLOW as near-body solver (Full CFD, 448M nodes) Mark Potsdam, Rohit Jain (Army ADD) S-76 Integrated Loads Figure of Merit

Exp. uncertainty ~0.6 counts Helios ~ 1 count OF-Charm ~ 2 counts OF-alone >2 counts

Comparable or better to all US and International participants

Torque coefficient vs. Thrust coefficient Figure of Merit

Non-contiguous wake Lateral Wake predictions (lines) comparable to those in Contiguous CFD domain (symbols) Vertical Wake Computational cost

Simulation Number of grid Core-hours Cost ratio nodes (millions) OVERFLOW-Helios (Jain 2015) 448 122,880 57.5 OVERFLOW (Narducci 2015) 63.4 28,080 13.14 OVERFLOW-CHARM with 28 14,400 6.74 background grids OVERFLOW-CHARM non-contiguous 15.4 2,140 1 grids (5 revs)

The full grid non-contiguous simulations cost about 7.6% of the number of core-hours as the stand-alone engineering OVERFLOW simulations

Jacobson, K. and Smith, M. J., “Performance and Physics of a S-76 Rotor in Hover With Non-Contiguous Hybrid Methodologies,” AIAA SciTech, AIAA-2016-0302, San Diego, CA, January, 2016 Evaluation in Forward Flight

• Baseline mesh was provided by Boeing-PHL • Represents a typical near-body mid-size mesh • 3.7M point mesh on each of four blades • 32.9 M background Cartesian mesh (orig) • Menter kw-SST turbulence model with full viscosity in the near-body region and Euler terms in the off-body region • Sensitivity to mesh sizes, coupling updates, turbulence model • Aeroelastic coupling • Examination of different rotor blade structural properties on same rotor (experimental set-up) • Evaluation of fuselage and wind tunnel floor effects

NFAC Tunnel Test • Wilbur et al., “Complex Vehicle Design and Analysis with Hybrid Methodologies,” AHS Aeromechanics Conference, San Francisco, CA, January 16–19, 2018. Coming soon: Journal of Aircraft • Min, B.-Y. et al., “Toward Improved UH-60A Blade Structural Loads Correlation,” AHS 74th Annual Forum, Phoenix, AZ, May 14-17, 2018 Dual-Solver Vortex Interactions Correlation with Industry CFD-alone

Normalized, means removed

r/R=.92

r/R=0.4

• Not a correlation with experiment – correlation with “best industry mesh/practices” • Reduction in background mesh by 40% nodes – no difference in loads • Convergence occurs at 75% of full CFD convergence requirements • None of the poor correlations with structural, hub or pitching moments as observed with other hybrid approaches Full CFD Analysis Full CFD Analyses Rotorcraft simulation and adjoint-based derivative evaluation framework (Graeme Kennedy at Georgia Tech) FUNtoFEM: Adjoint-enabled aeroelastic analysis Forward path Adjoint path FUNtoFEM FUN3D

Load transfer Surface integration Load adjoint Flow solver FEM/TACS Time-accurate Aeroelastic Rotorcraft SimulationDispl. transfer Displ. adjoint Mesh warping I On-going work to verify against HART-II case

I General interface for aeroelastic load and displacement transfer between FUN3D and a ﬁnite-element code

I Ecient hand-coded partial derivatives terms and transpose Jacobian-vector products that enable adjoint-based derivative Comparison of naturalevaluation frequencies with DYMORE • FUNtoFEM: A general interface for aeroelastic simulation and I Fan plot forI HART-IIDi↵ typeerent model transfer schemes enabledadjoint through-based an abstract gradient interface evaluation 16 TACS ﬂap TACS lag TACS torsion 15 layer: MELD and RBF (for surface-to-surface transfer), beam-speciﬁc 14 •23 / 29Enables use of either loosely or tightly coupled simulation 13 transfer 12 11 • Separation of time integration schemes for CSD/CFD 10 I Di↵erent bodies can be assigned di↵erent transfer schemes

ref 9

/ 8

• Different bodies can employ their own load/displacement 7 3/29 6 5 transfer methods 4 3 2 1 • Efficient hand-coded derivative terms enable efficient

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 /ref computation of coupled Jacobian-vector products

25 / 29 Helios Overview

Steady forward flight Wake resolution

• Rotary-wing product of CREATE™-AV − Jointly developed by CREATE and Army ADD

• Multi-mesh/Multi-solver Interactional aerodynamics

Unsteady maneuver - Strand, unstructured, structured curvilinear - Cartesian high-order with AMR - Automated domain interpolation

• Interfaces to rotorcraft comprehensive Sikorsky X2™ analysis codes for CSD and trim Elastic bending • Scalable execution on HPC systems

• 100+ active user licenses - DoD organizations (Army, Navy) - Various US rotorcraft companies - Various academic institutions US Army Helios Development

• Helios integrates simulation codes from CREATE, Army, and outside organizations • Software integrated through an extensible Python infrastructure

H-47 tandem simulation AH-64 Apache UH-60 main/tail simulation JMR “Defiant” JMR “Valor” CH47 – Block II Courtesy Boeing Courtesy Boeing Courtesy U.S.Army AED Sikorsky/Boeing Bell Helicopter Boeing/AED/ADD

Maneuver/ Automated 3D Strand slvr Strands Structures Propellers/ Multi-rotor DES Wake Rotor- Dual Propulsers AMR Fuselage V9 solver V8 V7 V4 V5 V6 V3 V2 MELODI mStrand COVIZ CSI KCFD V1 CAMRADII SAMCart PARAVIEW

Capability FUN3D OVERFLOW SIF, PUNDIT, SAMARC, Developed under CREATE NSU3D, RCAS, SAMRAI Third-party packages Annual 2010 2011 2012 2013 2014 2015 2016 2017 2018 releases Apache INSTALLED ROTOR PERFORMANCE

• High-fidelity, time-accurate rotor and fuselage combinations • Boeing Mesa

AH-64 E Apache, Hover:

Narducci & Tadghighi, Boeing AIAA-2016-0564 UH-60A Rotor Modeling & Validation

§ Blade tip vortex (B) § Trim tab vortex (T) Blade 2 § Twist/planform vortex (V) § Wake sheet (W) Blade 1 CFD

B2 B3 V2? V3 B4

B1? T4i W4 V4 T3i B1 T1o W1 Blade 3 T1i Blade 4

PIV

NASA/Army UH-60A NFAC test

Helios wake velocities, vortex locations and strength predictions are within experimental errors Sikorsky X-2™ TD

Main rotor unsteady lift 1 rev

Unsteady fuselage lift

1 rev

Reed, Egolf, “Coaxial Rotor Wake and Prop Induction Impact on a rd Horizontal Tail using Helios”, AIAA-2015-0554, 53 AIAA Amplitude Normalized Unsteady propeller thrust Aerospace Sciences Meeting, AIAA SciTech Forum, Jan 2015 Helios models the interactional 6 revs aerodynamics between lift-offset coaxial compound rotors, fuselage, and propulsor configuration 82 kts Validation with Bell XV-15 Tiltrotor

Fountain Reingestion flow

Wake impingement

Reingestion

Download/Thrust (%) !"/$ Wing Fuselage Nacelle Total

CFD 0.1195 10.31 5.41 1.07 16.79 Flight test 0.1271 – 0.1296 - - - 13.42 – 14.50 (Arrington et al.) Download Validation with JVX

Felker et al, ‘87

OVERFLOW

Config 1 FUN3D- OVERFLOW FUN3D

mStrand

Config 2 mStrand

mStrand JVX DOWNLOAD ANALYSIS

Rotor Thrust CT Wing/Flap Download CZ

Test 0.0075 Low thrust 0.000813 0.00754 0.000852 FUN3D/OFLOW 0.00741 q = 6o 0.000846 mStrand 0.0133 0.00134 0.0138 High thrust 0.00132 0.0136 q = 12o 0.00135

0.0000 0.0025 0.0050 0.0075 0.0100 0.0125 0.0150 0.0175 0.0200 0.00000 0.00025 0.00050 0.00075 0.00100 0.00125 0.00150 0.00175 0.00200

Download - CT/CZ

10.8% 11.3% 11.4% 10.1% 9.6% 10.2%

0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

mStrand FUN3D-OVERFLOW Manuever: UH-60A UTAAS Pull-Up

• 40 revs, 9 sec (real-time) • Flight path angle 3 deg at start to 35 deg at end UH-60A UTTAS Maneuver 2 Section Pitching Moment Cm M 86.5 % R UH-60A UTTAS Maneuver : Pushrod loads

Pushrod load

Helios demonstrates big improvement over RCAS for pushrod load prediction Joint CFD-Experimental Validation!

• Full-scale UH-60A rotor in Air Force 40- by 80-foot Wind Tunnel under NASA/Army Airloads Wind Tunnel Test Program (2010) • Extensive database of performance, hub loads, air loads, structural loads, wake PIV, blade deformation, RBOS on highly instrumented rotor for validating analytical tools • PIV phase • Wake measurements at 90 deg azimuth over 50% of outer blade • Vortex characteristics extracted: circulation, size, position

PIV camera ports laser launch port PIV ROI

mirror port

smoke airflow generators NASA/Army UH-60A NFAC test Future Research Directions

• Continuous improvement in speed and efficiency on multi-core processors for all levels of aerodynamic prediction tools • Integration of reduced-order modeling that is physics-based for earlier design of maneuvering and operational effects • Advanced design capabilities for rapid, highly-accurate design • Using high-fidelity methods, exploration of physics to understand complex interactional phenomena and shortcomings of current algorithms • Improved prediction of acoustics (interior and exterior) from unsteady aerodynamics • Jointly designed experimental datasets with sufficient information for CFD validation! • International collaboration to solve complex problems

Multi-rotor trim

3D Structures Acknowledgements • This effort was partially sponsored by the U.S. Government under • U.S. Army/Navy/NASA Vertical Lift Research Center of Excellence under the direction of Mahendra Bhagwat of AFDD, Agreement No. W911W6-11-2-0010. • Other Transaction number W15QKN-10-9-0003 between Vertical Lift Consortium, Inc. and the Government • Navy STTR contract N68335-09-C-0335 with guidance from technical monitors Jennifer Abras and Mark Silva • US DOE STTR DESC0004403 • The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. • The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government. • The authors would like to thank • Andy Wissink and Roger Strawn of CCDC Aviation Command for the Helios figures and slides • Glen Whitehouse and Dan Wachspress of Continuum Dynamics, Inc. • Rohit Jain and Mark Potsdam for their insights and figures • Ted Meadowcroft of Boeing-Philadelphia for the UH-60A computational mesh and input decks • All slides that require approval have been previously approved for prior presentations. Questions?