人发增强聚酯复合材料拉伸强度的数学模型及优化

Q3 Engineering International Journal of Computational Materials Science and Surface Engineering Pub Date : 2019-08-14 DOI:10.1504/IJCMSSE.2019.10017418

P. Rao, C. Kiran, K. E. Prasad

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引用次数: 0

摘要

聚合物基复合材料是用人发短纤维制成的，其体积分数从重量的5%到25%不等，纤维长度从10毫米到50毫米不等。通过实验了解了复合材料的抗拉强度。采用双因素五层历史数据模型(DOE)。在本研究中，利用响应面法(RSM)从实验结果中建立数学模型，以获得复合材料的最佳抗拉强度条件。采用方差分析(ANOVA)检验回归模型的相关系数，以检验数学模型的充分性。

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Mathematical Model and optimization for Tensile strength of Human Hair Reinforced Polyester Composites

Polymeric-based composites were prepared using chopped fibres of human hair in different volume fractions varying from 5% to 25% by weight and in different fibre lengths ranging from 10 mm to 50 mm. Experiments are conducted to know the tensile strength of the composites. Two-factor - five-level historical data model (DOE) is chosen. In the present study, a mathematical model was developed from the experimental results using response surface methodology (RSM) so as to obtain the optimum tensile strength condition for the composite. The correlation coefficient of the regression model was tested by analysis of variance (ANOVA) to check the adequacy of the mathematical model.

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来源期刊

International Journal of Computational Materials Science and Surface Engineering Engineering-Engineering (all)

CiteScore

1.20

自引率

0.00%

发文量

期刊介绍： IJCMSSE is a refereed international journal that aims to provide a blend of theoretical and applied study of computational materials science and surface engineering. The scope of IJCMSSE original scientific papers that describe computer methods of modelling, simulation, and prediction for designing materials and structures at all length scales. The Editors-in-Chief of IJCMSSE encourage the submission of fundamental and interdisciplinary contributions on materials science and engineering, surface engineering and computational methods of modelling, simulation, and prediction. Papers published in IJCMSSE involve the solution of current problems, in which it is necessary to apply computational materials science and surface engineering methods for solving relevant engineering problems.