Scalable Parallel Approach for High-Fidelity Steady-State Aeroelastic Analysis and Derivative

In this paper we present several significant improvements to both coupled solution methods and sen-sitivity analysis techniques for high-fidelity aerostructural systems. We consider the analysis of full aircraft configurations using Euler CFD models with more than 80 million state variables and struc-tural finite-element models with more than 1 million degrees of freedom. A coupled Newton–Krylov solution method for the aerostructural system is presented that accelerates the convergence rate for highly flexible structures. A coupled adjoint technique is presented that can compute gradients with respect to thousands of design variables accurately and efficiently. The efficiency of the presented methods is assessed on a high performance parallel computing cluster for up to 544 processors. To demonstrate the effectiveness of the proposed approach and the developed framework, an aerostruc-tural model based on the Common Research Model is optimized with respect to hundreds of variables representing the wing outer mold line and the structural sizing. Two separate problems are solved: one where fuel burn is minimized, and another where the maximum takeoff weight is minimized. Multi-point optimizations with 5 cruise conditions and 2 maneuver conditions are performed with a 2 million cell CFD mesh and 300 000 DOF structural mesh. The optima for problems with 476 design variables are obtained within 36 hours of wall time on 435 processors. The resulting optimal aircraft are discussed and analyze the aerostructural tradeoffs for each objective. Convergence tolerance for aerostructural solution Convergence tolerance for aerostructural adjoint solution Nomenclature α Angle of attack AS Convergence tolerance for aerostructural solution A Convergence tolerance for aerodynamic solution S Convergence tolerance for structural solution A Aerodynamic residuals R All residual