首页|基于数字孪生的海上浮式发电平台连接器应力场预报方法

基于数字孪生的海上浮式发电平台连接器应力场预报方法

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[目的]对多模块海上浮式发电平台连接器开展安全性评估时,为弥补因传感器数量有限而无法实时监测全域结构应力场的问题,提出一种基于仿真数据库的海上浮式发电平台应力场快速预测的数字孪生方法.[方法]通过将连接器的三维物理模型降阶为一维数字模型,在数字空间内对连接器的应力场数据进行插值推演,从而实现结构应力场的全域快速预报及可视化展示.[结果]结果表明,仿真模型与试验结果的吻合度较高,最大绝对误差为 8.61%;对于不同加载角度下的数据插值推演,当加载角度插值步长为 10°时,应力平均绝对误差为 1.98%;对于不同载荷下的数据插值推演,当载荷插值步长为 10 t时,应力平均绝对误差为 1.28%,实现了连接器应力场分布的快速预报与可视化展示.[结论]基于数字孪生技术所构建的连接器数字化模型可为海上浮式发电平台结构强度的快速动态感知及科学预测提供参考.
Digital twin based stress field prediction method for offshore floating power generation platform connectors
[Objectives]When assessing the safety of the connectors of a multi-module offshore floating power generation platform,in order to compensate for the inability to carry out the real-time monitoring of the structural stress field across the whole domain due to a limited numbers of sensor,a digital twin method based on a simulation database is proposed that can rapidly predict the platform's stress field.[Methods]By downgrading the three-dimensional physical model of the connectors to a one-dimensional digital model,the stress field data is interpolated and deduced in digital space,thereby achieving the rapid prediction of the struc-tural stress field across the whole domain and its visual display.[Results]The results show that the simula-tion model is in good agreement with the test results,with a maximum absolute error of 8.61%;for the inter-polation of data under different loading angles,when the interpolation step of the loading angle is 10°,the aver-age absolute error of stress is 1.98%;and for the interpolation of data under different loads,when the interpola-tion step of the load is 10 t,the average absolute error of stress is 1.28%,achieving the rapid prediction and visualization of the connectors'stress field distribution.[Conclusions]The digital twin-based model of connectors can provide useful references for the rapid dynamic perception and scientific prediction of the structural strength of offshore floating power generation platforms.

offshore floating power generation platformconnectorrapid predictiondigital twinreduced order model

曹宇、甘霖、张涛

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上海海洋大学 工程学院,上海 201306

大连理工大学 工业装备结构分析国家重点实验室,辽宁 大连 116024

中国船舶科学研究中心,江苏 无锡 214082

海上浮式发电平台 连接器 快速预测 数字孪生 降阶模型

大连理工大学工业装备结构分析国家重点实验室开放基金高性能船舶技术教育部重点实验室开放基金

GZ22113GXNC21112703

2024

中国舰船研究
中国舰船研究设计中心

中国舰船研究

CSTPCD北大核心
影响因子:0.496
ISSN:1673-3185
年,卷(期):2024.19(4)
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