Fishery Modernization ›› 2025, Vol. 52 ›› Issue (2): 9-.

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Analysis on the damage mechanism of single point mooring ship-type net cage

  

  1. (1 National Engineering Research Center For Marine Aquaculture, Zhejiang Ocean University, Zhoushan 316022,Zhejiang, China;
    2  School of Marine Engineering Equipment, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China) 

  • Online:2025-04-20 Published:2025-05-27

单点锚泊式船型网箱受灾破坏机理分析

  1. (1 浙江海洋大学国家海洋设施养殖工程技术研究中心,浙江 舟山 316022;
    2浙江海洋大学海洋工程装备学院,浙江 舟山 316022)
  • 通讯作者: 陈洪洲(1986—),男,教授,硕士生导师,研究方向:海岸工程水动力学。E-mail:379988848@163.com
  • 作者简介:桂福坤(1976—),男,教授,博士生导师,研究方向:水产设施养殖工程。E-mail:gui2237@163.com     

  • 基金资助:
    浙江省“尖兵”“领雁”科技计划项目(2023C02029);国家自然科学基金项目(42376205);舟山市“揭榜挂帅”科技攻关计划项目(2022C01003)

Abstract: This study aims to scientifically assess the disaster risks of ship net-type cages in wave environments, address the challenges in disaster prevention and control under extreme wave conditions, and promote the development of the offshore aquaculture industry. Numerical simulations were conducted using the AQWA hydrodynamic module in ANSYS to simulate the dynamic processes of ship-type net cages under various structural and wave conditions. After obtaining the data, a neural network algorithm was employed to construct the nonlinear relationship between disaster factors and structural damage, while the grey relational analysis method was used to identify the dominant disaster-causing factors. The results show that the structural motion responses and dynamic loads calculated by the numerical model closely match the test results, with an error of no more than 10%. The established neural network model accurately predicts the dynamic disaster situations, with a prediction error of no more than 5% and a root mean square error of no more than 0.52. It was determined that wave height is the dominant factor for mooring line breakage, and the floating frame length and wave height are the dominant factors for floating frame cracking. The research demonstrates that the neural network model can effectively predict the disaster damage for ship-type net cages and provides significant support for mooring line selection and floating frame safety assessment.


Key words: ship-type net cage, neural networks, disaster warning, primary disaster-causing factor, deep sea aquaculture

摘要: 为科学评估船型网箱在波浪环境中的灾害风险,解决其在极端风浪下灾害预防与控制难题,推动深远海养殖产业发展,本研究采用数值模拟方法,利用 ANSYS 中的 AQWA 水动力模块,对船型网箱在不同结构工况和波浪工况下的动力过程进行模拟,获取数据后用神经网络算法构建受灾因素与结构损伤的非线性关系,并以灰色关联度方法识别主控致灾因子。结果显示,数值模型计算的结构运动响应和动力荷载与试验基本一致,误差不超过10%;所建神经网络模型预报动力灾害情况准确,预测误差不超过5%,均方根误差不超过0.52;确定波高是锚绳断裂主控因子,浮架长度和波高是浮架开裂主控因子。研究表明,该神经网络模型可有效预测船型网箱的受灾破坏,同时为锚绳选型和浮架安全评估提供重要依据。


关键词: 船型网箱, 神经网络, 灾害预警, 主控致灾因子, 深远海养殖