FLNG低温软管内衬波纹管多目标优化设计

低温柔性管道是海上浮式液化天然气生产储卸装置系统中输送液化天然气的核心装备之一。U型波纹管作为低温柔性管道最内层结构，直接影响低温管道的安全性。本文选取波径和环板长度作为独立结构设计参数进行结构分析，解决了在传统的U型波纹管灵敏度分析中，波高会随波距的改变而改变的耦合计算问题。构建了径向基函数神经网络代理模型，采用遗传算法对U型波纹管结构开展了多目标优化，获得以拉伸刚度最大和弯曲刚度最小为优化目标时的帕累托最优解集，为U型波纹管在实际工程应用中提供有益的设计参考。

MULTI-OBJECTIVE OPTIMIZATION DESIGN OF U-SHAPED BELLOWS OF FLNG CRYOGENIC FLEXIBLE HOSE

Cryogenic flexible hose is one of the core equipment for transporting liquefied natural gas in the floating liquefied natural gas (FLNG) system. As the inner layer of LNG cryogenic flexible hose, U-shaped bellow directly affects the mechanical properties of the LNG cryogenic flexible hose. In this paper, the wave diameter and ring plate length are selected as independent structural design parameters for structural analysis, which solves the coupling calculation problem that the wave height changes with the change of wave distance in the traditional U-shaped bellows sensitivity analysis. The radial basis function neural network surrogate model is constructed, and the genetic algorithm is used to carry out the multi-objective optimization of the U-shaped bellows structure. The Pareto optimal solution set with the maximum tensile stiffness and the minimum bending stiffness as the optimization objectives is obtained, which provides a useful reference for the design of U-shaped bellows in practical engineering applications.