New Approach for the Optimisation of a Ducted Propeller Under Uncertainty

Ducted propellers are promising candidates for electrical aircrafts where the propulsion efficiency must be highly optimised. The aerodynamic performance and efficiency of ducted propellers can be obtained through models and experiments of various fidelity, ranging from cheap analytic formulas to expensive Computational Fluid Dynamics simulations. The ducted propeller design problem also involves several uncertainties arising from environmental conditions or manufacturing imperfections. To alleviate the computational burden of the uncertainty-based design optimisation of ducted propellers, we propose a new approach that combines multi-fidelity information fusion and dimensionality reduction by using different surrogate models for the design and probabilistic spaces. The method is validated on a simplified propeller model.