This training will introduce traditional and cutting-edge aerodynamic shape optimisation methods suitable for rotary wing applications. The training will cover definitions and classification of optimisation problems. We will introduce shape parameterisation methods suitable for aerofoils and rotary wings. We will then introduce common and novel optimisation algorithms based on gradients, surrogates, stochastics, metaheuristic principles etc. We will cover how to extract gradient and sensitivity information from computational fluid dynamics or any aerodynamic solvers via adjoint formulations and automatic differentiation, and how to construct high-performance surrogate models leveraging machine learning. Last but not least, we will present practical aerodynamic shape design optimisation cases for aerofoils, propellers, and helicopter rotors.
