水下航行器环肋复合材料耐压壳6σ优化设计

为了得到更可靠的水下航行器环肋复合材料耐压壳结构，考虑复合材料各向异性和加工不可控性对结构性能影响，将6σ设计理论引入环肋复合材料耐压壳优化设计中。应用蒙特卡洛抽样模拟方法对耐压壳结构进行可靠性分析，借助径向基函数神经网络近似模型技术，以σ水平为评价指标对环肋复合材料耐压壳结构进行考虑可靠性的优化设计。结果表明，虽然6σ优化相比确定性优化结果增加3.11 kg质量，但将耐压壳结构性能约束的σ水平提高到了8σ以上，可靠度达到100%，得到了兼顾结构质量和可靠性的最优方案。可见所提基于径向基函数神经网络近似模型技术的6σ设计与可靠性评估相结合优化方法，可以准确、高效、可靠地对水下航行器环肋复合材料耐压壳进行优化，合理解决随机因素变化导致结构可靠性不高的问题。

6σ Optimization Design of Ring-stiffened Composite Pressure Hull of Underwater Vehicle

In order to get a more reliable composite pressure hull structure of underwater vehicle, the effects of anisotropy and uncontrollable processing of composite materials on the structural performances should be taken into consideration. 6σ design is introduced into the optimization of ring-stiffened composite pressure hull. Monte Carlo sampling simulation is used for the reliability analysis of hull structure, and the reliability optimization design of pressure hull is conducted by taking sigma level as an evaluation index based on the radial basis function (RBF) neural network approximation model. The results show that, although the structural mass designed by 6σ optimization is 3.11 kg higher than that designed by deterministic optimization, the sigma levels of structural performance constraints are up to 8 and more, and the reliability reaches to 100%. Both structural mass and reliability are considered in the optimal design. The proposed optimization method of RBF approximation model-based 6σ design and reliability evaluation can be used for the accurate, efficient and reliable optimization of ring-stiffened composite pressure hull of underwater vehicle and solve the problem of low structural reliability due to variation of random factors.