Autonomous underwater vehicles hull shape resistance prediction and multi-objective optimization using CFD

The development of Autonomous Underwater Vehicles (AUVs) has become a priority for numerous countries. Achieving low drag and high efficiency in these vehicles is essential for enhancing their endurance. To effectively reduce energy consumption and improve navigation durability, a parametric Myring shape model was established, and the Computational Fluid Dynamics (CFD) method was employed to predict flight resistance at cruising speed. The accuracy and reliability of the CFD method were subsequently verified. A surrogate model was then constructed to optimize hydrodynamic performance, with optimal space filling applied for sample sampling to generate a nonparametric regression response surface. This surface was optimized using a multi-objective optimization algorithm, resulting in a 9.5% reduction in drag while maintaining sufficient volume, given constant overall length and diameter.