Wing shape optimization for an air-launched underwater glider considering impact loads and gliding performance

The air-launched underwater glider has two typical scenarios that need to be specially considered in its design: the water impact stage after air-launched deployment and the gliding stage of the glider in the water. The wing shape of the underwater glider has a significant impact on the hydrodynamic performance in both scenarios. This study proposes a multi-objective optimization method for the wing shape optimization of air-launched gliders, comprehensively considering the gliding motion performance and impact load performance during water entry. An Artificial Neural Network (ANN) and Polynomial Response Surface (PRS) method were used to establish surrogate models for the gliding motion and impact load, respectively, and the accuracy of these surrogate models was verified. The sensitivities of the different design variables to the output parameters were analyzed. An optimized wing shape can improve the gliding range and reduce the impact load. Considering the uncertainties in the net buoyancy and energy consumption in practical applications, an interval optimization algorithm for wing shape optimization was proposed. The interval optimization results provided a more reasonable wing-shape design scheme.