基于代理模型的自升式海洋平台桩靴的结构优化研究
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中国海洋大学

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中央高校基本科研业务费(202165009, 202113031);山东省自然科学基金(ZR2021ME014)


Research on Structure Optimization of jack-up offshore platform spudcan based on surrogate models
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Ocean University of China

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the Fundamental Research Funds for the Central Universities(202165009, 202113031);natural Science Foundation of Shandong Province(ZR2021ME014)

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    摘要:

    自升式海洋平台桩靴作为平台的重要组成部分存在结构庞大笨重,应力分布不均等问题。针对自升式海洋平台JU2000E桩靴,应用ANSYS建立有限元模型,依据ABS规范对其预压载工况和风暴自存工况下进行强度分析与校核,采用桩靴各结构板厚作为优化设计变量,通过最优拉丁超立方抽样选取样本点,结合径向基(RBF)神经网络算法,建立设计变量和各响应的代理模型,并基于第二代非劣解遗传算法(NSGA-Ⅱ)对桩靴进行多目标优化。对优化后桩靴进行仿真验证,桩靴重量减轻,应力减小且分布更均匀。

    Abstract:

    As an important part of the jack-up offshore platform spudcan have the problems of bulky structure and unequal stress distribution.?Aiming at JU2000E spudcan of jack-up offshore platform, finite element model is established by ANSYS?software. According to the ABS specification, the strength analysis and verification are carried out under the conditions of pre-ballast and storm self-storage. The thickness of each structure plate of spudcan is used as the optimal design variable, and the sample points are selected by optimal Latin hypercube sampling. Combined with the radial basis (RBF) neural network algorithm, the surrogate models of design variables and each response were established, and the multi-objective optimization of spudcan was carried out based on the second generation Non-inferior solution genetic algorithm (NSGA-Ⅱ).?The simulation results show that the weight of the optimized spudcan is reduced, the stress is reduced and the distribution is more uniform.

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  • 收稿日期:2022-11-03
  • 最后修改日期:2022-11-29
  • 录用日期:2022-12-01
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