An efficient gradient-based algorithm for aerodynamic shape optimization is presented. The algorithm consists of several components, including a novel integrated geometry parameterization and mesh movement, a parallel Newton-Krylov flow solver, and an adjoint-based gradient evaluation. To integrate geometry parameterization and mesh movement, generalized B-spline volumes are used to parameterize both the surface and volume mesh. The volume mesh of B-spline control points mimics a coarse mesh; a linear elasticity mesh-movement algorithm is applied directly to this coarse mesh and the fine mesh is regenerated algebraically. Using this approach, mesh-movement time is reduced by two to three orders of magnitude relative to a node-based movement. The mesh-adjoint system also becomes smaller and is thus amenable to complex-step derivative approximations. When solving the flow-adjoint equations using restarted Krylov-subspace methods, a nested-subspace strategy is shown to be more robust than truncating the entire subspace. Optimization is accomplished using a sequential-quadratic-programming algorithm. The effectiveness of the complete algorithm is demonstrated using a lift-constrained induced-drag minimization that involves large changes in geometry.
Aerodynamic optimization algorithm with integrated geometry parameterization and mesh movement
Aerodynamischer Optimierungsalgorithmus mit integrierter Geometrie-Parametrisierung und Netzverschiebung
AIAA Journal ; 48 , 2 ; 400-413
2010
14 Seiten, 13 Bilder, 1 Tabelle, 79 Quellen
Aufsatz (Zeitschrift)
Englisch
British Library Conference Proceedings | 2015
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