Abstract

Propeller design is a comprehensive task in finding the best trade-off between competing objectives and constraints. It requires a multi-disciplinary evaluation of the propeller performance based on various input parameters. Thus optimisation algorithm applied to this type of problem require consideration of the problem to solve. The purpose of this paper is hence the improvement of commonly used population-based algorithms (NSGA-II and PSO) towards the application of marine propeller design. The extension to three algorithms are outlined utilising meta models, adapted constraints and modified constraints handling. The proposed algorithms are applied on a real-life marine propeller example. Results of 13 optimisations are compared in terms of optimisation convergence, constraints compliance and Pareto optimality and show advantageous performance of the developed cavitation constraints and the meta-model extended NSGA-II.

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