Multi-fidelity Surrogate Assisted Design Optimisation of an Airfoil under Uncertainty using Far-Field Drag Approximation

Uncertainty-based optimisation techniques provide optimal airfoil de- signs that are less vulnerable to the presence of uncertainty in the operational conditions (i.e., Mach number, angle-of-attack, etc.) at which an airfoil is func- tioning. These uncertainty-based techniques typically require numerous function evaluations to accurately calculate the statistical measure of the quantity of inter- est. To render the computational burden down, the design optimisation of the air- foil is performed by a multi-fidelity surrogate-based technique. The high-fidelity aerodynamic performance is calculated with a compressible RANS solver using a fine grid. At the low-fidelity level a coarser grid is used. To obtain accurate drag predictions despite the lower grid resolution the so-called far-field drag approxi- mation is employed.