Derivative free global optimisation of CFD simulations

This work reports on the use of numerical optimisation techniques to optimise objective functions calculated by Computational Fluid Dynamics (CFD) simulations. Two example applications are described, the first being the shape optimisation of a low speed wind tunnel contraction. A potential flow and viscous flow solver have been coupled to produce a robust computational tool, with the contraction shape defined by a two parameter B´ezier curve. The second application is a simplified test case with a known minimum calculated using a commercial CFD code. For the optimisation of complex CFD simulations, it is sometimes advantageous to use an efficient derivative free global optimisation algorithm because of potentially long simulation times, the objective function may contain multiple local minima and it is often difficult to evaluate analytical or numerical gradients. The Efficient Global Optimisation (EGO) algorithm sequentially samples results from an expensive calculation, does not require derivative information, uses an inexpensive surrogate to search for a global optimum, and is used in this current work. For both applications, the EGO algorithm is able to efficiently and robustly find a global optimum that satisfies any constraints.R.C. Morgans, C.J. Doolan and D. Stephen