基于稀疏网格模型和NSGA-II算法的中型游艇结构轻量化研究

Research on Structural Lightweight Design of Medium-sized Yachts Based on the Sparse Grid Model and NSGA-II algorithm

为了提高某中型游艇结构的优化效率,本文针对船体结构进行优化,提出了一种将稀疏网格模型与NSGA-II算法结合的优化方法,进行轻量化研究.根据船体结构有限元分析结果,选择合适的优化参数,然后利用稀疏网格自适应局部细化过程,生成响应面模型,能在保证样本点数较少情况下满足精度要求,结合NSGA-II算法对其进行优化求解,得到的优化结果误差小,求解速度快,收敛性好,其强度满足设计要求,仿真结果与原有设计参数比,优化后船体总质量减轻了15.6%,有效实现了轻量化设计目标.

In order to improve the optimization efficiency of the structure of a medium-sized yacht and optimize the hull structure, an optimization method combining the sparse grid model with the NSGA-II algorithm for lightweight research is proposed,the appropriate optimization parameters are selected, and then the response surface model is generated by using the adaptive local refinement process of the sparse grid. The model can meet the accuracy requirements under the conditions of ensuring that the number of sample points is small. Combined with the NSGA-II algorithm, the optimized method can achieve a smaller error rate, fast solution speed, good convergence, and the strength can meet the design requirements. The simulation results show the total mass of the hull after optimization is reduced by 15.6%, effectively achieving the lightweight design goal.