上海交通大学学报

上海交通大学学报

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基于改进遗传算法的海上浮式生产储油轮码头抗台系泊缆系统参数优化方法（网络首发）

  

  1. 1.上海交通大学海洋工程国家重点实验室；2.中远海运重工有限公司；3.中国船舶及海洋工程设计研究院
  • 基金资助:
    山东省重点研发计划项目(2021SFGC0701)，国家重点研发计划（2022YFB2602800）

The Parameter Optimization Method for FPSO Docking Mooring Lines Under Typhoon Conditions Based on Improved Genetic Algorithms

  1. （1. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China；2. COSCO Shipping Heavy Industry Co., Ltd., Shanghai 200135, China；3. Marine Design and Research Institute of China, Shanghai 200011, China）

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摘要： 海上浮式生产储油轮（FPSO）是海洋石油开发的关键装备，其在台风等恶劣环境条件下进行码头系泊时，由于主尺度较大，且将同时受到风浪流联合作用，因此对码头系泊系统承载能力要求较高；此外，系泊缆错综布置，缆绳数量近60根，采用比选方法来寻找所有系泊缆绳的最优参数组合方案，计算工作量巨大，几乎不可行。因此，本文综合考虑了多浪向风浪流载荷作用下，发展了一种基于改进遗传算法的FPSO码头抗台系泊缆系统参数迭代优化方法，以缆绳长度作为变量参数，不同缆绳长度组合作为遗传迭代中的个体，通过校核每个组合在典型工况下的缆绳载荷，评估该组合的适应度并进行迭代优化，最终得到了优化后的系泊缆系统参数。对优化前后系泊方案校核结果进行比对，发现优化后的缆绳长度参数整体呈现较长缆绳张紧、较短缆绳放松的趋势，提高了原来承载较少的缆绳的利用率；在对FPSO运动幅度影响不大的前提下使所有工况下出现的缆绳最大载荷降低了12.2%，并在其他参数不变的条件下仅通过调整缆绳张紧程度使优化后的方案通过了安全规范校核；该优化方法研究工作可在有限码头资源条件前提下尽可能提升系泊系统安全性，并为码头系泊带缆工作提供一定参考。

关键词: 码头系泊, 缆绳载荷, 遗传算法, 参数优化, 时域方法

Abstract: Floating Production Storage and Offloading (FPSO) units are critical equipment in offshore oil development. When mooring at a dock in harsh environmental conditions such as typhoons, their large main dimensions and simultaneous exposure to combined wind, wave, and current forces impose high demands on the load-bearing capacity of the mooring system. Additionally, the mooring lines are arranged in a complex manner, with nearly 60 lines, making it almost infeasible to use a comparative method to find the optimal parameter combination for all mooring lines due to the extensive computational workload. Therefore, this paper comprehensively considers the multi-directional wind, wave, and current loads and develops an iterative optimization method for FPSO typhoon-resistant mooring line system parameters based on an improved genetic algorithm. The method takes line lengths as variable parameters, and different combinations of line lengths as individuals in the genetic iteration. By checking each combination's line load under typical conditions to assess the fitness of the combination, the optimization is iteratively carried out, ultimately resulting in an optimized mooring line system. The comparison of the mooring scheme results before and after optimization reveals that the optimized mooring line length parameters show a trend of tightening longer lines and relaxing shorter lines, thus improving the utilization of lines that previously had lower loads. The optimized mooring scheme reduces the maximum mooring line load under all conditions by 12.2% without significantly affecting the amplitude of FPSO movements. By merely adjusting the tension levels of the mooring lines, the optimized scheme meets safety standard checks without altering other parameters. This optimization method can enhance the safety of mooring systems within the constraints of limited dock resources and provide a reference for docking mooring operations.

Key words: Docking mooring, mooring lines force, genetic algorithms, parameter optimization, time domain calculation

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