Effects of Biological Adhesion on the Hydrodynamic Characteristics of Different Panel Net Materials: A BP Neural Network Approach

文献类型： 外文期刊

第一作者： Liu, Yongli

作者： Liu, Yongli;Liu, Wei;Wang, Lei;Min, Minghua;Li, Lei;Ma, Shuo;Wang, Liang

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关键词： panel net; biological adhesion; hydrodynamic characteristics; density

期刊名称：JOURNAL OF MARINE SCIENCE AND ENGINEERING （ 影响因子：2.8； 五年影响因子：2.8 ）

ISSN：

年卷期： 2024 年 12 卷 11 期

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收录情况： SCI

摘要： Biofouling is a serious problem in marine aquaculture facilities, exerting several negative effects on cage structures. In this study, different materials of nets were placed in the Fujian Sea area of China, and the main biological adhesion species were determined. The drag force of different materials of fouled nets was studied by a physical test in a flume tank. The drag force coefficient of a clean polyethylene terephthalate (PET) net was 0.53. The drag force coefficients of ultrahigh-molecular-weight polyethylene (UHMWPE) and polyethylene (PE) nets were 161.2% and 133.5% higher, respectively, compared with those of PET nets. Crustaceans, mollusks, and algae were the main organisms that adhered to the nets. Compared with the clean nets, the drag force of PET, UHMWPE, and PE nets increased by 1.29-5.06 times, 1.11-2.85 times, and 0.55-2.46 times, respectively. Based on backpropagation (BP) neural network training, the relationship between biological characteristics (average adhesion thickness and density) and the drag force of three kinds of net materials was determined. The drag force of the biofouled net at various time points throughout the year can be predicted based on this model, which can guide the cleaning and maintenance of nets in cage structures.

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