柔性立管限弯器高效设计方法
Efficient Design Method of Flexible Riser Bend Stiffeners
董磊磊 1王宦婷 1王莹莹2
作者信息
- 1. 大连理工大学 船舶工程学院,辽宁 大连 116024
- 2. 中国石油大学(北京) 安全与海洋工程学院,北京 102249
- 折叠
摘要
目的 考虑聚氨酯材料非线性的影响,建立一种简单高效的柔性立管限弯器设计方法.方法 首先确定限弯器的初始尺寸,在此基础上进行参数分析,并根据分析结果绘制设计图谱,然后通过插值获得最佳的设计尺寸.结果 针对深水与浅水2 种典型环境,分别采用本方法与基于遗传算法的优化设计方法进行限弯器设计,通过结果对比验证了方法的有效性.同时发现,深水环境条件设计出的限弯器相对短粗,而浅水条件设计出的限弯器则较为细长,且考虑材料非线性后,2 种环境下限弯器的设计尺寸均有所减小.结论 本文建立的限弯器设计方法具有广泛的适用性,且能够在确保得到理想设计方案的前提下,显著提高设计效率.与基于遗传算法的优化设计方法相比,采用线性材料和考虑材料非线性时的设计效率可分别提高约10 倍和 20 倍.
Abstract
The work aims to build a simple and efficient design method for flexible riser bend stiffeners considering the nonlinear material behavior of polyurethane.The initial dimensions of the bend stiffener were firstly determined,based on which parametric analyses were performed and the design chart was drawn according to the analysis results.The optimal dimensions of the bend stiffener were then obtained using an interpolation technique.A case study was carried out for two typical environ-mental conditions,i.e.deep-water and shallow-water applications,using this method and the optimization method based on the genetic algorithm.The comparison of results confirmed the effectiveness of this method.It was also found through the compari-son that the bend stiffener designed for the deep-water environmental condition was relatively short and thick,while that for the shallow-water condition was slenderer.The dimensions of the bend stiffeners for both conditions were smaller when material nonlinearity was taken into account.It is concluded that the developed method has a wide applicability and can significantly im-prove the efficiency while ensuring the optimal design.Compared with the optimization method based on the genetic algorithm,the design efficiency,when using the linear material and considering material nonlinearity,can be improved by approximately 10 times and 20 times,respectively.
关键词
限弯器/结构设计/优化/遗传算法/细长梁模型/非线性响应分析Key words
bend stiffener/structural design/optimization/genetic algorithm/slender beam model/non-linear behavior analysis引用本文复制引用
基金项目
国家重点研发计划项目(2022YFC2803701)
国家自然科学基金(52071054)
出版年
2024
NETL
NSTL
万方数据