Surrogate-Based Airfoil Design with Multi-Level Optimization and Adjoint Sensitivity
Yonatan Afework Tesfahunegn, Slawomir Marcin Koziel, Leifur Leifsson · 53rd AIAA Aerospace Sciences Meeting · 2015
Robust and computationally efficient airfoil shape optimization algorithm is presented. Our technique enhances a recently introduced multi-level optimization (MLO) algorithm with adjoint sensitivity. Adjoint-enhanced MLO exploits a set of computational fluid dynamics (CFD) models of increasing discretization density that are sequentially optimized with the optimal design of the “coarser” model being the initial design for the “finer” one. Transition between the models of different fidelities is governed by suitably selected termination criteria, more relaxed at the initial stages, and stricter towards the end of the optimization process. Exploitation of variable-fidelity models allows for taking larger steps in the design space at a lower CPU cost, leading to an improved efficiency when compared to gradient-based direct optimization of the high-fidelity model with adjoints as demonstrated by several test cases of transonic airfoils. In particular, the results show that up to a 43% reduction in the optimization cost can be achieved with MLO when compared with the direct approach.