A coupled-adjoint method for high-fidelity aero-structural optimization

Abstract : A new integrated aero-structural design method for aerospace vehicles is presented. The approach combines an aero-structural analysis solver, a coupled aero-structural adjoint solver, a geometry engine, and an efficient gradient-based optimization algorithm. The aero-structural solver ensures accurate solutions by using high-fidelity models for the aerodynamics, structures, and coupling procedure. The coupled aero-structural adjoint solver is used to calculate the sensitivities of aerodynamic and structural cost functions with respect to both aerodynamic shape and structural variables. The aero-structural adjoint sensitivities are compared with those given by the complex-step derivative approximation and finite differences. The proposed method is shown to be both accurate and efficient, exhibiting a significant cost advantage when the gradient of a small number of functions with respect to a large number of design variables is needed. The optimization of a supersonic business jet configuration demonstrates the usefulness and importance of computing aero-structural sensitivities using the coupled-adjoint method.

[1]  J. N. Lyness Numerical algorithms based on the theory of complex variable , 1967, ACM National Conference.

[2]  Bengt Fornberg,et al.  Numerical Differentiation of Analytic Functions , 1981, TOMS.

[3]  Philip E. Gill,et al.  Practical optimization , 1981 .

[4]  A. Jameson,et al.  Numerical solution of the Euler equations by finite volume methods using Runge Kutta time stepping schemes , 1981 .

[5]  F. W. J. Olver,et al.  ERROR ANALYSIS OF COMPLEX ARITHMETIC , 1983 .

[6]  Antony Jameson,et al.  Aerodynamic design via control theory , 1988, J. Sci. Comput..

[7]  Jaroslaw Sobieszczanskisobieski,et al.  On the sensitivity of complex, internally coupled systems , 1988 .

[8]  J. E. Horwedel GRESS Version 2. 0 user's manual , 1991 .

[9]  J. Sobieszczanski-Sobieski,et al.  A technique for locating function roots and for satisfying equality constraints in optimization , 1992 .

[10]  C. Bischof,et al.  ADIFOR exception handling , 1992 .

[11]  Andreas Griewank,et al.  ADIFOR - Generating Derivative Codes form Fortran Programs , 1992, Sci. Program..

[12]  C. Bischof,et al.  Derivative convergence for iterative equation solvers , 1993 .

[13]  Kumar Bhatia,et al.  AEROELASTIC CHALLENGES FOR A HIGH SPEED CIVIL TRANSPORT , 1993 .

[14]  Thomas Beck,et al.  The if-problem in automatic differentiation , 1994 .

[15]  Thomas Beck Automatic differentiation of iterative processes , 1994 .

[16]  John E. Dennis,et al.  Problem Formulation for Multidisciplinary Optimization , 1994, SIAM J. Optim..

[17]  Sean Wakayama,et al.  Lifting surface design using multidisciplinary optimization , 1995 .

[18]  C. Q. Liu,et al.  Sensitivity analysis of discrete structural systems , 1995 .

[19]  Ilan Kroo,et al.  Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment , 1995 .

[20]  Andreas Griewank,et al.  Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++ , 1996, TOMS.

[21]  R. Giering Tangent linear and adjoint model compiler users manual , 1996 .

[22]  T Haftka Raphael,et al.  Multidisciplinary aerospace design optimization: survey of recent developments , 1996 .

[23]  A. Jameson,et al.  Aerodynamic Shape Optimization of Complex Aircraft Configurations via an Adjoint Formulation , 1996 .

[24]  Antony Jameson,et al.  Re-engineering the design process through computation , 1997 .

[25]  Natalia Alexandrov,et al.  Multidisciplinary design optimization : state of the art , 1997 .

[26]  John C. Vassberg,et al.  An Efficient Multiblock Method for Aerodynamic Analysis and Design on Distributed Memory Systems , 1997 .

[27]  S. Brown,et al.  Displacement extrapolations for CFD+CSM aeroelastic analysis , 1997 .

[28]  R. Haftka,et al.  Multidisciplinary aerospace design optimization: survey of recent developments , 1997 .

[29]  Christian H. Bischof,et al.  ADIC: an extensible automatic differentiation tool for ANSI‐C , 1997, Softw. Pract. Exp..

[30]  George Trapp,et al.  Using Complex Variables to Estimate Derivatives of Real Functions , 1998, SIAM Rev..

[31]  L Walsh Joanne,et al.  Optimization Issues With Complex Rotorcraft Comprehensive Analysis , 1998 .

[32]  K. I. M. McKinnon,et al.  Convergence of the Nelder-Mead Simplex Method to a Nonstationary Point , 1998, SIAM J. Optim..

[33]  A. Jameson,et al.  Optimum Aerodynamic Design Using the Navier–Stokes Equations , 1997 .

[34]  M. J. Rimlinger,et al.  Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers , 1997 .

[35]  Wu K. Chauncey,et al.  Sensitivity of Lumped Constraints Using the Adjoint Method , 1999 .

[36]  Joaquim R. R. A. Martins,et al.  A coupled aero-structural optimization method for complete aircraft configurations , 1999 .

[37]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[38]  Joaquim R. R. A. Martins,et al.  AN AUTOMATED METHOD FOR SENSITIVITY ANALYSIS USING COMPLEX VARIABLES , 2000 .

[39]  Charbel Farhat,et al.  Optimization of aeroelastic systems using coupled analytical sensitivities , 2000 .

[40]  Jaroslaw Sobieszczanski-Sobieski,et al.  Bilevel Integrated System Synthesis with Response Surfaces , 2000 .

[41]  Anthony A. Giunta,et al.  A NOVEL SENSITIVITY ANALYSIS METHOD FOR HIGH FIDELITY MULTIDISCIPLINARY OPTIMIZATION OF AERO-STRUCTURAL SYSTEMS , 2000 .

[42]  Angel-Victor DeMiguel,et al.  An analysis of collaborative optimization methods , 2000 .

[43]  W. K. Anderson,et al.  Sensitivity Analysis for Navier-Stokes Equations on Unstructured Meshes Using Complex Variables , 2001 .

[44]  Kazuhiro Nakahashi,et al.  Navier-Stokes optimization of supersonic wings with four design objectives using evolutionary algorithm , 2001 .

[45]  Joaquim R. R. A. Martins,et al.  THE CONNECTION BETWEEN THE COMPLEX-STEP DERIVATIVE APPROXIMATION AND ALGORITHMIC DIFFERENTIATION , 2001 .

[46]  C. Farhat,et al.  Coupled Analytical Sensitivity Analysis and Optimization of Three-Dimensional Nonlinear Aeroelastic Systems , 2001 .

[47]  Juan J. Alonso,et al.  Development and Validation of a Massively Parallel Flow Solver for Turbomachinery Flows , 2001 .

[48]  J. Alonso,et al.  Aero-Structural Wing Design Optimization Using High-Fidelity Sensitivity Analysis , 2001 .

[49]  Kazuhiro Nakahashi,et al.  Navier-Stokes Optimization of Supersonic Wings with Four Objectives Using Evolutionary Algorithm , 2002 .

[50]  J. Alonso,et al.  Complete Configuration Aero-Structural Optimization Using a Coupled Sensitivity Analysis Method , 2002 .

[51]  Joaquim R. R. A. Martins,et al.  High-Fidelity Aerostructural Design Optimization of a Supersonic Business Jet , 2002 .

[52]  Ilan Kroo,et al.  Natural Laminar Flow for Quiet and Efficient Supersonic Aircraft , 2002 .

[53]  Michael A. Saunders,et al.  USER’S GUIDE FOR SNOPT 5.3: A FORTRAN PACKAGE FOR LARGE-SCALE NONLINEAR PROGRAMMING , 2002 .

[54]  Shigeru Obayashi,et al.  Self-organizing map of Pareto solutions obtained from multiobjective supersonic wing design , 2002 .