Towards High-Fidelity Aerostructural Optimization using a coupled ADjoint Approach

The tools required to perform high-fidelity aerostructural optimization are developed. Given the highly coupled nature of the aerostructural problem, a multidisciplinary feasible (MDF) approach is used for the framework. This approach is facilitated by a lagged-coupled adjoint, implemented using the ADjoint technique to sensitivity analysis. The ADjoint technique allows for the generation of very accurate and efficient adjoint sensitivities. The lagged-coupled adjoint system, which is equivalent to using a block-Jacobi method on the full coupled adjoint system, is solved using a pair of linear solvers. The structural portion of the system is solved using FEAP’s linear solver, while the CFD portion of the system is solved using PETSc. To demonstrate the accuracy of the coupled ADjoint, the sensitivities computed using the lagged-coupled approach are verified against complex-step sensitivities.

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

[2]  Sobieszczanski Jaroslaw,et al.  Bi-Level Integrated System Synthesis (BLISS) , 1998 .

[3]  Georgi Kalitzin,et al.  Unsteady turbomachinery computations using massively parallel platforms , 2006 .

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

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

[6]  Joaquim R. R. A. Martins,et al.  The complex-step derivative approximation , 2003, TOMS.

[7]  J. Alonso,et al.  ADjoint: An Approach for the Rapid Development of Discrete Adjoint Solvers , 2006 .

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

[9]  J. L. Walsh,et al.  Efficient structural optimization for multiple load cases using adjoint sensitivities , 2001 .

[10]  Robert D. Braun,et al.  Collaborative optimization: an architecture for large-scale distributed design , 1996 .

[11]  Joaquim R. R. A. Martins,et al.  pyACDT: An Object-Oriented Framework for Aircraft Design Modelling and Multidisciplinary Optimization , 2008 .

[12]  J. Alonso,et al.  A methodology for the development of discrete adjoint solvers using automatic differentiation tools , 2007 .

[13]  J. Martins.  A coupled-adjoint method for high-fidelity aero-structural optimization , 2002 .

[14]  J. Alonso,et al.  A Coupled-Adjoint Sensitivity Analysis Method for High-Fidelity Aero-Structural Design , 2005 .

[15]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2005, SIAM Rev..

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

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

[18]  O. Pironneau.  On optimum design in fluid mechanics , 1974 .