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论文类型： 期刊论文

发表时间： 2017-10-01

发表刊物： JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME

收录刊物： Scopus、SCIE、EI

卷号： 139

期号： 5

ISSN号： 0892-7219

摘要： Recently, the flexible cryogenic hose has been preferred as an alternative to exploit offshore liquefied natural gas (LNG), in which helical corrugated steel pipe is the crucial component with C-shaped corrugation. Parametric finite element models of the LNG cryogenic helical corrugated pipe are established using a three-dimensional shell element in this paper. Considering the nonlinearity of cryogenic material and large geometric structural deformation, mechanical behaviors are simulated under axial tension, bending, and internal pressure loads. In addition, design parameters are determined to optimize the shape of flexible cryogenic hose structures through sectional dimension analysis, and sensitivity analysis is performed with changing geometric parameters. A multi-objective optimization to minimize stiffness and stress is formulated under operation conditions. Full factorial experiment and radial basis function (RBF) neural network are applied to establish the approximated model for structure analysis. The set of Pareto optimal solutions and value range of parameters are obtained through nondominated sorting genetic algorithm II (NSGA-II) under manufacturing and stiffness constraints, thereby providing a feasible optimal approach for the structural design of LNG cryogenic corrugated hose.