Abst'/> Multi-objective optimization of Tension Leg Platform using evolutionary algorithm based on surrogate model
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Multi-objective optimization of Tension Leg Platform using evolutionary algorithm based on surrogate model

机译：基于代理模型的进化算法对张力腿平台的多目标优化

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摘要

AbstractAn Innovative Tension Leg Platform (TLP) Optimization Program, called ITOP, has been developed to solve the multi-objective optimization problem for TLP. We first examine the hydrodynamic behavior of a base TLP for wave headings between0∘and45∘. The numerical results show that the maximum heave and surge motion responses occur in0∘wave heading in long-crest waves. It is found that the dynamic tension of No. 8 tendon is larger than the other tendons and reaches its maximum in45∘wave heading. It can be attributed to the fact that heave and pitch motions are almost out of phase for wave periods between 10 and 15 s. Because the maximum wave elevation occurs near the northeast column and the vertical motion is very small, the minimum airgap occurs there. Moreover, a surrogate model based on radial basis function (RBF) has been built and adopted to estimate the hydrodynamic performance of TLP. A multi-objective evolutionary algorithm, Non-dominated Sorting Genetic Algorithm II (NSGAII), is employed to find the Pareto-optimal solutions. By comprehensive and systematic computations and analyses, it is revealed that the maximum dynamic tension shows positive correlation with pontoon height and width, but negative correlation with hull draft, column spacing, and column diameter. The most efficient modification strategy for design is proposed to reduce the maximum dynamic tendon tension. According to the strategy, the column spacing, draft, and column diameter should be increased in sequence. By applying this strategy, the maximum dynamic tendon tensions can be reduced while the total weight of the platform is minimized as much as possible.Highlights•A surrogate model based on radial basis function is built and adopted to estimate the hydrodynamic performance of TLP.•The optimization results are verified by direct numerical simulations to ensure the accuracy of the surrogate model.•The Non-dominated Sorting Genetic Algorithm II (NSGAII) is performed for the multi-objective optimization of TLP.•The most efficient modification strategy for design is proposed.
机译： 摘要 已开发出一种名为ITOP的创新张力腿平台（TLP）优化程序，以解决TLP的多目标优化问题。首先，我们针对 0 ∘ 和 45 ∘ 。数值结果表明，最大的升沉和喘振运动响应发生在 0 ∘ 长波中的波浪前进方向。发现8号肌腱的动态张力大于其他肌腱，并在 45 < mml：mo>∘ 波航向。这可以归因于以下事实：在10到15秒之间的波浪周期中，升沉和俯仰运动几乎异相。因为最大的波高发生在东北柱附近，并且垂直运动非常小，所以最小的气隙在那发生。此外，已经建立了基于径向基函数（RBF）的替代模型，并采用该模型来估算TLP的水动力性能。采用多目标进化算法非支配排序遗传算法II（NSGAII）来找到帕累托最优解。通过综合和系统的计算和分析，发现最大动态张力与浮船的高度和宽度呈正相关，而与船体吃水，柱距和柱径呈负相关。提出了最有效的设计修改策略，以减小最大动态肌腱张力。根据该策略，应依次增加列间距，吃水深度和列直径。通过应用此策略，可以最大程度地减小动态肌腱的张力，同时尽可能减小平台的总重量。 < ce：abstract xmlns：ce =“ http://www.elsevier.com/xml/common/dtd” xmlns =“ http://www.elsevier.com/xml/ja/dtd” class =“ author-highlights” xml：lang =“ zh-CN” id =“ abs0015” view =“ all”> 突出显示 • 建立了基于径向基函数的替代模型，并采用该模型来估算TLP的水动力性能。 • 验证了优化结果通过直接数值模拟以确保替代模型的准确性。 • 针对多目标对象执行非主导排序遗传算法II（NSGAII） TLP的客观优化。 • 提出了最有效的设计修改策略。

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  • 来源
    《Ocean Engineering》 |2018年第15期|612-631|共20页
  • 作者

    Xinshu Zhang; Xingyu Song; Wenzhen Qiu; Zhiming Yuan; Yunxiang You; Naiming Deng;

  • 作者单位

    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE);

    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE);

    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE);

    Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde;

    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE);

    State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University,Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE);

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  • 正文语种 eng
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  • 关键词

    Multi-objective optimization; TLP; Airgap; Tendon tension; Radial basis function;

    机译：多目标优化;TLP;气隙;Tendon张力;径向基函数;

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