A Coupled Aero−Structural Optimization Method for Complete...
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Stanford University Stanford University A Coupled Aero-Structural Optimization Method for Complete Aircraft Configurations AIAA 37th Aerospace Sciences Meeting & Exhibit Reno, NV January 11th, 1999 James J. Reuther MCAT Institute Juan J. Alonso and Joaquim R. R. A. Martins Stanford University Stephen C. Smith NASA Ames Research Center
Transcript of A Coupled Aero−Structural Optimization Method for Complete...
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A Coupled Aero−Structural OptimizationMethod for Complete Aircraft Configurations
AIAA 37th Aerospace Sciences Meeting & ExhibitReno, NV
January 11th, 1999
James J. ReutherMCAT Institute
Juan J. Alonso and Joaquim R. R. A. MartinsStanford University
Stephen C. SmithNASA Ames Research Center
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OBJECTIVESOBJECTIVES
❑ Develop a high−fidelity environment for aero−structural analysis and design of complex aircraft configurations.
❑ Create a full aircraft geometry outer mold line (OML) database for the exchange of information between disciplines.
❑ Couple a Reynolds Averaged Navier−Stokes (RANS) flow solver with linear finite element CSM solvers for aero−structural analysis and design.
❑ Establish a basic framework for future use in coupled sensitivity analysis.
❑ Demonstrate aeroelastic analysis and simplified aero−structural design problems.
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OUTLINEOUTLINE
❑ Introduction and Motivation
❑ CSM Models: wind−tunnel model and aircraft wing structures
❑ Aero−Structural Coupling: consistency and conservativeness
❑ Sensitivity Analysis: aerodynamics, structures, coupled
❑ Results: analysis and design cases
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rsity ❑ Dr. James J. Reuther, MCAT Institute, NASA Ames Research Center
❑ Joaquim R. R. A. Martins, Stanford University
❑ Dr. Stephen C. Smith, NASA Ames Research Center
RESEARCH TEAMRESEARCH TEAM
❑ Prof. Juan J. Alonso, Stanford University
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❑ Use of high−fidelity discipline models in the Multi−Disciplinary Optimization (MDO) arena
❑ Advanced aerodynamic shape optimization methods have facilitated great improvements, but they require artificial constraints
❑ Iterative application of single−discipline design methods can miss the true optimum of a coupled system
❑ Single−discipline optmization methods may produce infeasible designs
MOTIVATIONMOTIVATION
❑ Ability to account for trade−offs between various disciplines is the key to generate improved designs
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❑ Aeroelastic wing design
❑ Interaction between aerodynamics and structures
❑ Induced drag vs. structural performance
❑ Compressibility drag vs. structural performance
❑ Variety of off−design constraints (loads, pitch−up, etc.)
DEMONSTRATION PROBLEMDEMONSTRATION PROBLEM
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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HIGH−FIDELITY AERODYNAMICSHIGH−FIDELITY AERODYNAMICS
❑ FLO107−MB: parallel multiblock RANS flow solver
❑ 5−stage Runge−Kutta algorithm
❑ Multigrid
❑ MPI parallel implementation
❑ Residual averaging
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SAMPLE BUSINESS JETSAMPLE BUSINESS JET
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SAMPLE COMMERCIAL JETSAMPLE COMMERCIAL JET
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SAMPLE SUPERSONIC AIRCRAFTSAMPLE SUPERSONIC AIRCRAFT
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MULTIBLOCK SOLVER: TFLO98MULTIBLOCK SOLVER: TFLO98TYPICAL COMPRESSOR STAGETYPICAL COMPRESSOR STAGE
❑ Rotor 37 Compressor Stage❑ 36 Blades❑ 288 Blocks❑ 27,000,000 cells
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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WIND TUNNEL MODELSWIND TUNNEL MODELS❑ Aeroelastic analysis of complete configurations
❑ Comparison with experimental data
❑ 8−node isoparmetric elements
❑ Cholesky factorization
❑ 2−point Gauss quadrature
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❑ Triangular plates and truss elements
❑ Skins modeled with plates
❑ Spars and ribs modeled with plates and trusses
❑ Simplified but realistic and accurate
WING STRUCTURE MODELWING STRUCTURE MODEL
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❑ States the exact form of the functions and arguments provided by the programmer.
❑ Designed for ease of interchangeability of different structural solvers.
❍ CSM_Init(...) memory allocation and initialization of model
STRUCTURAL MODEL APISTRUCTURAL MODEL API
❍ CSM_Solve(...) returns structural deflections
❑ Will establish couplings for NASTRAN, ANSYS.
❍ CSM_Stresses(...) returns element stresses
❍ CSM_GetPoint(...) returns CSM surface information
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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❑ Intent is to maintain accuracy of disciplines.
❑ Accomplished via Aerosurf database.
❑ Aero−structural coupling used here is both consistent and conservative.
−Consistent: resultant forces and moments are preserved. −Conservative: total work/energy is preserved.
AERO−STRUCTURAL COUPLINGAERO−STRUCTURAL COUPLING
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TRANSFER EQUATIONSTRANSFER EQUATIONS
❑ Transfer of CSM nodal displacements to AeroSurf database.
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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OML DATABASEOML DATABASE
❑ Un−intersected set of aircraft components❑ Parametric patches from intersection of surfaces
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OML DATABASE
❑ Parametric location of CFD mesh points is identified by a triad (n, u, v), where n is the patch number.
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PRE−PROCESSING STEPSPRE−PROCESSING STEPS
❑ Aerosurf point "association" procedure
❑ "Association" with parametric location within a given element on the surface of the CSM model
❑ Computation of basis functions values
❑ Calculation of weights, [η]
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❑ In a preprocessing step, all points on Aerosurf are "associated" with a "donor" cell and location inside that cell in CFD mesh.
❑ During the calculation process, the current pressure distribution is transferred directly to the Aerosurf database.
❑ Using appropriate weights a conservative and consistent load vector is created and passed to the CSM solver.
❑ CSM_Solve is called to obtain structural displacements.
CFD PRESSURE TRANSFERCFD PRESSURE TRANSFER
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❑ Result of CSM_Solve is the vector of displacements at the CSM nodes.
❑ Using the CSM model displacement basis functions and pre−computed [η] matrix, new locations of Aerosurf points are found.
❑ Aerosurf database is used to deform the CFD mesh on the solid boundaries.
❑ Warp−MB is used to perturb the interior of the CFD mesh.
DISPLACEMENT TRANSFERDISPLACEMENT TRANSFER
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INGREDIENTS OF THE FRAMEWORKINGREDIENTS OF THE FRAMEWORK
❑ High−fidelity modeling in the component disciplines:
− Euler and Navier−Stokes equations for aerodynamics.− Detailed Finite Element Model for structures.
❑ High−fidelity coupling between participating disciplines:
− Consistency: force and moment resultant preserved.− Conservativeness: total work/energy preserved.
❑ OML geometry database for information exchanges (shape, pressure distributions, displacements).
❑ Sensitivity analysis.
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AERODYNAMIC SENSITIVITIESAERODYNAMIC SENSITIVITIES
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COUPLED SENSITIVITIESCOUPLED SENSITIVITIES
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❑ Navier−Stokes aeroelastic analysis of complete configuration wind tunnel models
− Rigid model− Flexible model
❑ Aerodynamic shape optimization of a flight wing−alone geometry
− Aerodynamics only− With aeroelastic deformation
RESULTSRESULTS
❑ ✳❉❍❐●❉❆❉❅❄ aero−structural shape optimization
−Wing−alone−Complete configuration
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CONCLUSIONSCONCLUSIONS
❑ High−fidelity modeling in aerodynamics and structures
❑ Centralized OML geometry database as reference for different disciplines
❑ Force and work preserving coupling algorithm
❑ Framework for computation of coupled sensitivities
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KEY ENABLING TECHNOLOGIESKEY ENABLING TECHNOLOGIES
❑ Development of adjoint−based, gradient calculation techniques for systems governed by partial differential equations.
❑ Portable, scalable, parallel implementations for efficient computing platforms such as the SGI Origin2000.
❑ Advances in automatic multiblock mesh generation techniques.
❑ Recent development of direct interfaces to CAD geometry kernels.
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❑ SPMD (Single Program Multiple Data) layout.
❑ MPI (Message Passing Interface) Library for message passing.
❑ Using block boundaries in the multiblock domain, natural parallelization is achieved.
❑ Domain decomposition strategy.
❑ MPI is used to update the "halo" quantities at every stage of the time−stepping.
❑ Computational cost of optimization is negligible compared to flow and adjoint solutions.
PARALLEL IMPLEMENTATIONPARALLEL IMPLEMENTATION
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LOAD BALANCING AND COMMUNICATIONLOAD BALANCING AND COMMUNICATION
❑ Needed communication:
−Multiblock decomposition, multigrid acceleration.
−CFD stencil.
−Multistage time−stepping:✔ Convective fluxes at all stages and levels.✔ 1st order dissipation on odd stages at all levels.✔ 3rd order dissipation only on fine mesh at odd stages.
1st Level Halo 2nd Level Halo
Convective Stencil Dissipative Stencil
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LOAD BALANCING AND COMMUNICATIONLOAD BALANCING AND COMMUNICATION
❑ Load balancing and communication:
−CPU time:
✔ Balance the number of computational cells in each processor.
−Bandwidth:✔ Place adjacent blocks on same processor.
−Latency:✔ Gather all communication between an two processors into a single message regardless of the number of blocks in each processor.
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PARALLEL PERFORMANCEPARALLEL PERFORMANCE
240 Blocks
4,157,440 Cells
Maximum Speedup 28.0 / 32.0
Maximum Possible29.5 / 32.0
Load Balance Effects
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CONCLUSIONSCONCLUSIONS
❑ Feasible and Efficient Parallel Environment Developed and Demonstratedfor the Inviscid Design of Complete Aircraft Configurations
❑ Portable, Scalable Parallel Implementations Necessary for Continuityand Fast Turnaround
❑ Final Objective is to Make Use of These Techniques During thePreliminary Design Stage
❑ Performance of Computing Platform is Essential for Accomplishing Task
❑ Origin2000 Has Delivered Expected Performance for These Calculations
❑ Navier−Stokes Based Methods are Needed and Currently in Development
