Multi-disciplinary optimization of underwater vehicles based on a dynamic proxy model - Shaojun Sun; Weilin Luo (Brodogradnja)
This paper presents a method for optimizing the multidisciplinary shape design of underwater vehicles using a dynamic proxy model. The method employs a collaborative optimization approach that considers various disciplines, including rapidity, maneuverability, energy consumption, and structural strength of the underwater vehicle. The K and T indices are effectively utilized to represent the maneuverability performance of underwater vehicles. The hydrodynamics of underwater vehicles are analyzed using the Computational Fluid Dynamics (CFD) numerical simulation method. To reduce the computational burden in the optimization loop, this paper proposes a dynamic proxy model that combines the trust region with the adaptive minimum confidence Lowest Credible Bound (LCB) and the Synthetic Minority Over-Sampling Technique (SMOTE) algorithm. Additionally, an adaptive balance constant is introduced into the proxy model. The collaborative optimization framework employs a combined optimization algorithm based on the genetic algorithm and Nonlinear Programming by Quadratic Lagrangian Programming (NLPQLP) algorithm. The results of applying this optimization strategy to the SUBOFF model demonstrate its effectiveness in optimizing the resistance, mass, maneuverability, structural strength, and energy consumption of the underwater vehicle.