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基于灰色系统理论的有机涂层/钢的湿附着力数学模型及寿命预测研究

Studies on Mathematical Models of Wet Adhesion and Lifetime Prediction of Organic Coating/Steel by Grey System Theory.

作者信息

Meng Fandi, Liu Ying, Liu Li, Li Ying, Wang Fuhui

机构信息

Institute of Metal Research, Chinese Academy of Sciences, Wencui Road 62, Shenyang 110016, Liaoning, China.

Key Laboratory for Anisotropy and Texture of Materials (MoE), School of Materials Science and Engineering, Northeastern University, Wenhua Road 3-11, Shenyang 110819, Liaoning, China.

出版信息

Materials (Basel). 2017 Jun 28;10(7):715. doi: 10.3390/ma10070715.

DOI:10.3390/ma10070715
PMID:28773073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5551758/
Abstract

A rapid degradation of wet adhesion is the key factor controlling coating lifetime, for the organic coatings under marine hydrostatic pressure. The mathematical models of wet adhesion have been studied by Grey System Theory (GST). Grey models (GM) (1, 1) of epoxy varnish (EV) coating/steel and epoxy glass flake (EGF) coating/steel have been established, and a lifetime prediction formula has been proposed on the basis of these models. The precision assessments indicate that the established models are accurate, and the prediction formula is capable of making precise lifetime forecasting of the coatings.

摘要

对于处于海洋静水压力下的有机涂层而言,湿附着力的快速下降是控制涂层寿命的关键因素。已运用灰色系统理论(GST)对湿附着力的数学模型进行了研究。建立了环氧清漆(EV)涂层/钢和环氧玻璃鳞片(EGF)涂层/钢的灰色模型(GM)(1, 1),并在此基础上提出了寿命预测公式。精度评估表明所建立的模型准确无误,且该预测公式能够对涂层的寿命进行精确预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/9e0b1c185134/materials-10-00715-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/8513d18b1046/materials-10-00715-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/fa3ce5c661d7/materials-10-00715-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/458bfb3dbd5d/materials-10-00715-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/d3f289c43375/materials-10-00715-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/2c39b44b7bf5/materials-10-00715-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/dafd1a5fe5d4/materials-10-00715-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/8a910b90542c/materials-10-00715-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/0e38aa61a759/materials-10-00715-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/a227650f7cec/materials-10-00715-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/9e0b1c185134/materials-10-00715-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/8513d18b1046/materials-10-00715-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/fa3ce5c661d7/materials-10-00715-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/458bfb3dbd5d/materials-10-00715-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/d3f289c43375/materials-10-00715-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/2c39b44b7bf5/materials-10-00715-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/dafd1a5fe5d4/materials-10-00715-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/8a910b90542c/materials-10-00715-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/0e38aa61a759/materials-10-00715-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/a227650f7cec/materials-10-00715-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f4/5551758/9e0b1c185134/materials-10-00715-g010.jpg

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