1. Failure probability of offshore high-density polyethylene net cages under typhoon waves.
- Author
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Shi, Xian-Wu, Zhao, Yun-Peng, Bi, Chun-Wei, Liu, Qiang, Fan, Zhong-Qi, Zhou, Shui-Hua, and Jia, Ning
- Subjects
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SEAFOOD , *HIGH density polyethylene , *MONTE Carlo method , *TYPHOONS , *FINITE element method , *PROBABILITY theory - Abstract
With the growth of global population, the demand for seafood has been increasing. Aquaculture as a sustainable industry provides a new direction to satisfy the rising demand for seafood. However, typhoons, a common disaster in coastal areas, can cause massive waves that can threaten the safety of aquaculture facilities. Therefore, studying the facilities' failure probability under typhoon waves with different return periods is crucial. The example of offshore high-density polyethylene net cages in the seas near Guishan Island, Zhuhai, China, was examined in this study. The wave conditions for different return periods for these seas were predicted using the SWAN+ADCIRC model and the local wave statistics for the last 30 years. Based on the prediction results, the hydrodynamic loads and stresses of the primary cage structure (floating collar, nets, and mooring lines) in typhoon waves at different return periods were calculated using the lumped-mass and finite element methods. Meanwhile, the failure probability of the cage components was analyzed based on the Monte Carlo method. According to the failure probability and cost of different components, the suitable size of the each of the cage components in the representative seas was studied. This study affords a reference for the design of the cage and improve the aquaculture insurance. • Relation between typhoon waves and failure probability of HDPE net cage components. • SWAN+ADICRC model combined with local hydrographic data to predict typhoon waves. • Lumped-mass and finite element methods for hydrodynamic loads on components. • Quantitative response relationship established using Monte Carlo method. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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