Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization

Abstract

Purpose

Strategies for accelerated multi-objective optimization of aerodynamic surfaces are investigated, including the possibility of exploiting surrogate modeling techniques for computational fluid dynamic (CFD)-driven design speedup of such surfaces. The purpose of this paper is to reduce the overall optimization time.

Design/methodology/approach

An algorithmic framework is described that is composed of: a search space reduction, fast surrogate models constructed using variable-fidelity CFD models and co-Kriging, and Pareto front refinement. Numerical case studies are provided demonstrating the feasibility of solving real-world problems involving multi-objective optimization of transonic airfoil shapes and accurate CFD simulation models of such surfaces.

Findings

It is possible, through appropriate combination of surrogate modeling techniques and variable-fidelity models, to identify a set of alternative designs representing the best possible trade-offs between conflicting design objectives in a realistic time frame corresponding to a few dozen of high-fidelity CFD simulations of the respective surfaces.

Originality/value

The proposed aerodynamic design optimization algorithmic framework is novel and holistic. It proved useful for fast design of aerodynamic surfaces using high-fidelity simulation data in moderately sized search space, which is extremely challenging when using conventional methods due to the excessive computational cost.

Citation

Koziel, S., Tesfahunegn, Y. and Leifsson, L. (2016), "Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization", Engineering Computations, Vol. 33 No. 8, pp. 2320-2338. https://doi.org/10.1108/EC-09-2015-0277