Surrogate-based bilevel shape optimization for blended-wing–body underwater gliders

Abstract

For blended-wing–body underwater gliders (BWBUGs), a high-performance shape design necessitates not only a higher lift-to-drag ratio (LDR), but also additional carrying space. However, regardless of how the parameters alter with the fixed layout, some potential optimal solutions may be lost. It is feasible to achieve the genuine global optimum when the parameter space of the layout is liberated. On the other hand, the shape and layout parameters have different physical properties. The complexity of optimization can be reduced if these can be organized according to their properties. Therefore, a surrogate-based bilevel shape optimization (SBSO) method is presented, in which surrogate models are updated iteratively until the optimum is found. The upper level aims at maximizing the LDR, while the lower level aims to maximize the volume. SBSO is tested on 12 benchmark cases, several existing algorithms and shape optimization of a BWBUG, and all show excellent performance.