Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

[1]  J. Lions Optimal Control of Systems Governed by Partial Differential Equations , 1971 .

[2]  R. M. Hicks,et al.  An assessment of airfoil design by numerical optimization , 1974 .

[3]  R. M. Hicks,et al.  Wing Design by Numerical Optimization , 1977 .

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

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

[6]  O. Pironneau Optimal Shape Design for Elliptic Systems , 1983 .

[7]  A. Jameson Solution of the Euler equations for two dimensional transonic flow by a multigrid method , 1983 .

[8]  Michael A. Saunders,et al.  User''s guide for NPSOL (Ver-sion 4.0): A FORTRAN package for nonlinear programming , 1984 .

[9]  Joe F. Thompson,et al.  Numerical grid generation , 1985 .

[10]  Joe F. Thompson,et al.  Numerical grid generation: Foundations and applications , 1985 .

[11]  P. Gill,et al.  Some theoretical properties of an augmented lagrangian merit function , 1986 .

[12]  Antony Jameson,et al.  Multigrid algorithms for compressible flow calculations , 1986 .

[13]  P. Gill,et al.  Fortran package for nonlinear programming. User's Guide for NPSOL (Version 4. 0) , 1986 .

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

[15]  V. Korivi,et al.  Sensitivity analysis, approximate analysis, and design optimization for internal and external viscous flows , 1991 .

[16]  Oktay Baysal,et al.  Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics , 1991 .

[17]  C. P. van Dam,et al.  Subsonic and Transonic Low-Reynolds-Number Airfoils with Reduced Pitching Moments , 1992 .

[18]  R. M. Hicks,et al.  Practical design optimization of wing/body configurations using the Euler equations , 1992 .

[19]  M. D. Salas,et al.  Aerodynamic design and optimization in one shot , 1992 .

[20]  Michael B. Bieterman,et al.  Practical Design and Optimization in Computational Fluid Dynamics , 1993 .

[21]  Donald V. Steward,et al.  Re-engineering the design process , 1993, [1993] Proceedings Second Workshop on Enabling Technologies@m_Infrastructure for Collaborative Enterprises.

[22]  Oktay Baysal,et al.  Airfoil Shape Optimization Using Sensitivity Analysis on Viscous Flow Equations , 1993 .

[23]  A. Jameson,et al.  Control theory based airfoil design for potential flow and a finite volume discretization , 1994 .

[24]  G. Kuruvila,et al.  Airfoil Optimization by the One-Shot Method , 1994 .

[25]  P. A. Newman,et al.  Sensitivity derivatives for three dimensional supersonic Euler code using incremental iterative strategy , 1994 .

[26]  P. A. Newman,et al.  Aerodynamic optimization studies using a 3-D supersonic Euler code with efficient calculation of sensitivity derivatives , 1994 .

[27]  A. Jameson Optimum aerodynamic design via boundary control , 1994 .

[28]  Antony Jameson,et al.  Control theory based airfoil design using the Euler equations , 1994 .

[29]  Oktay Baysal,et al.  Three-dimensional aerodynamic shape optimization of wings using sensitivity analysis , 1994 .

[30]  A. Jameson,et al.  Aerodynamic shape optimization of wing and wing-body configurations using control theory , 1995 .

[31]  Antony Jameson,et al.  Supersonic wing and wing-body shape optimization using an adjoint formulation , 1995 .

[32]  A. Jameson Optimum aerodynamic design using CFD and control theory , 1995 .

[33]  A. Jameson,et al.  A comparison of design variables for control theory based airfoil optimization , 1995 .

[34]  Ramesh Agarwal,et al.  Airfoil design via control theory using full potential and Euler equations , 1996 .

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

[36]  Juan J. Alonso,et al.  Automatic aerodynamic optimization on distributed memory architectures , 1996 .

[37]  Vijay Modi,et al.  Design of minimum drag bodies in incompressible laminar flow , 1996 .

[38]  Neal Pfeiffer,et al.  Business jet wing design using aerodynamic shape optimization , 1996 .

[39]  Juan J. Alonso,et al.  Aerodynamic Shape Optimization of Supersonic Aircraft Configurations via an Adjoint Formulation on Parallel Computers , 1996 .

[40]  W. K. Anderson,et al.  Aerodynamic design optimization on unstructured grids with a continuous adjoint formulation , 1997 .

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

[42]  Akira Oyama,et al.  Transonic Wing Optimization Using Genetic Algorithm , 1997 .

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

[44]  O. Baysal,et al.  Three-Dimensional Viscous ADI Algorithm and Strategies for Shape Optimization , 1997 .

[45]  J. Peraire,et al.  Aerodynamic optimization of unstructured meshes with viscous effects , 1997 .

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

[47]  Antony Jameson,et al.  Optimum aerodynamic design using the Navier-Stokes equations , 1997 .

[48]  Antony Jameson Re-Engineering the Design Process Through Computation , 1999 .

[49]  Juan J. Alonso,et al.  Aerodynamic shape optimization of supersonic aircraft configurations via an adjoint formulation on distributed memory parallel computers , 1996 .

[50]  Kazuhiro Nakahashi,et al.  Inverse design optimization of transonic wings based on multi-objective genetic algorithms , 1999 .

[51]  Jaroslav Mackerle,et al.  Parallel finite element and boundary element analysis: theory and applications - a bibliography (1997-1999) , 2000 .

[52]  Michael B. Giles,et al.  Adjoint Recovery of Superconvergent Functionals from PDE Approximations , 2000, SIAM Rev..

[53]  Kazuhiro Nakahashi,et al.  Flap-Deflection Optimization for Transonic Cruise Performance Improvement of Supersonic Transport Wing , 2001 .