Abstract

The self-righting deck can improve the survivability of the Unmanned Surface Vessel (USV) in the rough sea states. In order to realize the automatic optimal design of the self-righting deck of USV and improve the optimization efficiency, this paper proposes a design method of self-righting deck based on the combination of particle swarm optimization and sequential quadratic programming. The deck wind resistance and the average value of the righting arm at 90–100° angles of heel and 170–180°angles of heel are taken as the optimization objectives. The parametric modeling of the USV deck is carried out and the design variables are determined. The approximate model is constructed by Radial Basis Functions (RBF) to save the optimization time. The automatic optimization framework is established through ISIGHT intelligent optimization platform by integrating Maxsurf Modeler, Maxsurf Stability, and Excel. The shape optimization of self-righting deck for a 7 Dm USV is taken as an example to verify the effectiveness of the design method and optimization process. The proposed method provides a solution for the automatic optimal design of self-righting deck of different types of unmanned boats.

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