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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:水利工程系
学科:港口、海岸及近海工程. 船舶与海洋结构物设计制造
办公地点:大连理工大学 海岸和近海工程国家重点实验室 海洋工程研究所A区402室
联系方式:ypzhao@dlut.edu.cn
电子邮箱:ypzhao@dlut.edu.cn
An efficient artificial neural network model to predict the structural failure of high-density polyethylene offshore net cages in typhoon waves
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论文类型:期刊论文
发表时间:2020-01-15
发表刊物:OCEAN ENGINEERING
收录刊物:EI、SCIE
卷号:196
ISSN号:0029-8018
关键字:Prediction model; Structural failure; Offshore net cage; Artificial neural network; Field survey
摘要:Offshore net cages are aquaculture facilities that can provide satisfactory volumes of stocked fish. The safety of these structures is of great importance to aquaculture companies. Typhoons are considered to be the main cause of damage to offshore net cages. In this study, an artificial neural network (ANN) model was developed to predict the structural failure of high-density polyethylene offshore net cages in typhoon waves. A case study was conducted where the ANN model was used to predict the structural failure of the offshore net cages around Nanji Island, Wenzhou, China, during Typhoon Maria. Field survey was performed to study the hydrodynamics of the offshore net cages in different wave conditions and the results were used as the training data for the ANN model. By classifying the structural failure, the damage levels of offshore net cages can be predicted and used with wave forecasting before typhoon landing. Field survey was carried out immediately after the typhoon. The prediction and field survey results showed that the proposed ANN model can accurately predict the damage levels of offshore net cages under the influence of typhoon waves.