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机构地区:[1]海洋工程国家重点实验室,上海交通大学,上海200240
出 处:《中国海洋平台》2013年第2期45-52,共8页China offshore Platform
基 金:国家自然科学基金资助项目资助(51009093);国家自然科学重点基金项目资助(项目编号:50739004)
摘 要:针对深水复合材料立管外压、拉伸承裁设计要求,采用了近似模型技术进行多目标优化设计。随着海洋资源开发向深海迈进,深水极限裁荷使得现有钢制立管技术难以满足设计要求。由于复合材料具有高比强度,设计性强、抗腐蚀性能好等优点,应用于深水前景较好。立管接头静水外压和轴向拉伸承裁力是立管环向和轴向的关键力学性能,因此对于上述目标进行铺角的优化是一个多目标优化问题。提出多目标优化设计方法,使用非支配排序遗传算法搜索帕累托(Pareto)前沿。通过优化改善了立管的力学性能并给出便于设计人员参考的优化铺角,在保证精度的情况下提高优化效率。A methodology based on approximation model is presented for the multi-objective optimization design of deepwater composite risers. Nowadays, the offshore oil production industry is gradually moving into deeper waters. Since the weight of a riser increases with water depth, traditional steel riser systems are heavy and require expensive tensioning and buoyancy systems. Composite materials offer many attractive properties such as the excellent strength to weight rations, design flexibility and high corrosion resistance. In the performance -based design of riser, the axial tensile capacity relates the axial strengths while buckling load under external pressure relates the hoop rigidities. The ply orientations optimization of composite riser joints gives rise to a multi-objective optimization problem. Non-dominated Sorting Genetic Algorithm is employed to obtain the Pareto solution set. The results indicate the optimization strategy with approximation is valid and both objectives have great improvements, among which the designer can make a choice.
关 键 词:复合材料立管 力学性能 多目标优化 近似模型 非支配排序遗传算法
分 类 号:TB332[一般工业技术—材料科学与工程]
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