A parallel multidisciplinary optimization design is proposed for the lines design of an underwater vehicle. Resistance and energy consumption are concerned about in obtaining the optimized lines. Collaborative optimization strategy is adopted to construct the optimization framework. The simulated annealing algorithm in combination of the modified method of feasible directions are taken as the optimization algorithms. CFD based simulation is conducted to analyze the resistance of the underwater vehicle. To improve the optimization efficiency, a surrogate model is incorporated into the optimization framework to approximate the CFD calculation. Unlike the conventional static surrogate models used in the design of underwater vehicles, a dynamic surrogate based on trust region and lower confidence bound is proposed. An adaptive balance parameter is taken in the lower confidence bound approach to guarantee the tradeoff between the exploitation and exploration ability of the dynamic surrogate model. Optimal Latin hypercube algorithm is employed as the method of design of experiments. Radial basis function is employed to construct the surrogate model. SUBOFF model is used to demonstrate the proposed optimization scheme. Lines of the underwater vehicle are determined and optimization results of the resistance and energy consumption show the effectiveness of optimization scheme.

针对水下航行器的流水线设计，提出了一种并行的多学科优化设计方案。在获得优化线路时，需要考虑电阻和能耗。采用协同优化策略构建优化框架。结合可行方向的改进方法，将模拟退火算法作为优化算法。进行了基于CFD的仿真，以分析水下航行器的阻力。为了提高优化效率，将替代模型合并到优化框架中以近似CFD计算。与水下航行器设计中使用的常规静态替代模型不同，提出了一种基于信任区域和较低置信度边界的动态替代模型。在下置信界方法中采用自适应平衡参数，以确保动态代理模型的开发能力与探索能力之间的权衡。最优的拉丁超立方体算法被用作实验设计的方法。采用径向基函数构造替代模型。SUBOFF模型用于演示所提出的优化方案。确定了水下航行器的线路，阻力和能耗的优化结果表明了该优化方案的有效性。采用径向基函数构造替代模型。SUBOFF模型用于演示所提出的优化方案。确定了水下航行器的线路，阻力和能耗的优化结果表明了该优化方案的有效性。采用径向基函数构造替代模型。SUBOFF模型用于演示所提出的优化方案。确定了水下航行器的线路，阻力和能耗的优化结果表明了该优化方案的有效性。