Stochastic optimisation of the flow around a linear cascade of blades

The past decades have seen remarkable progress in computing capabilities, allowing computational fluid dynamics (CFD) to become an ever more present tool in describing and predicting complex unsteady flows. However, robust optimisation and control of these flows on the basis of such high-fidelity simulations remains a big challenge. The main bottleneck arises from the large cost associated with performing each function evaluation (a full and potentially unsteady CFD calculation). As the first step, we study the performance of a stochastic optimisation algorithm using response surfaces (DYCORS) when applied to such cases. The performance of this method is then improved by adding local gradient information as well as the functional value in constructing the response surface. The effectiveness of the proposed algorithm is then studied by optimising the total pressure drop around a linear cascade of blades, by imposing a tangential velocity in the blade surface. A range of Reynolds numbers are considered and the performance of the method is compared to the original derivative free algorithm as well as a gradient-based alternative.