大连理工大学主页平台管理系统蹇锡高含二氮杂萘酮联苯结构聚芳酯的合成及性能中文主页

论文成果

Artificial neural networks in prediction of mechanical behavior of high performance plastic composites: 点击次数：; 发布时间： 2019-03-11; 发布时间：2019-03-11; 论文类型：会议论文; 发表时间：2011-11-04; 收录刊物：Scopus、CPCI-S、EI; 卷号：501; 页面范围：27-+; 关键字：artificial neural network; composites; ANN; 摘要：Using a feed-forward artificial neural network (ANN), the tensile strength of a series of poly(phthalazinone ether sulfone ketone)(PPESK) blended with different contents of polyetheretherketone(PEEK), polysulfone(PSF), polyphenylene sulide (PPS) and reinforced with various amounts of whisker(TK) composites has been predicted based on a measured database. Compared with the experimental results, the maximum error obtained is not more than 0.8%. It is concluded that the predicted data are well acceptable. A well-trained ANN is expected to be very helpful mathematical tool in the structure-property analysis of polymer composites. Finally, using ANN modeling data and experimental data, the tensile strength properties related to whisker weight percent were established.

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教授博士生导师硕士生导师

性别：男

毕业院校：大连工学院

学位：硕士

所在单位：化工学院

学科：高分子材料. 高分子化学与物理. 膜科学与技术

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