复合材料科学与工程 ›› 2015, Vol. 0 ›› Issue (8): 41-46.

• 基础研究 • 上一篇    下一篇

玻璃纤维/树脂基复合材料性能参数的确定及影响因素研究

舒明杰, 祖磊*, 王继辉, 李书欣   

  1. 武汉理工大学材料科学与工程学院,武汉 430070
  • 收稿日期:2015-03-16 出版日期:2015-08-28 发布日期:2021-09-14
  • 通讯作者: 祖磊(1983-),男,博士,教授,主要从事复合材料方面的研究,zulei@whut.edu.cn。
  • 作者简介:舒明杰(1990-),男,硕士研究生,主要从事复合材料方面的研究。
  • 基金资助:
    国家自然科学基金(11302168);湖北省自然科学基金(2014CFB140);中央高校基本科研业务费专项资金资助项目(143101001)

DETERMINATION OF STRUCTURAL PARAMETERS OF GLASS FIBER RESIN COMPOSITES AND THEIR INFLUENCIAL FACTORS

SHU Ming-jie, ZU Lei*, WANG Ji-hui, LI Shu-xin   

  1. School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
  • Received:2015-03-16 Online:2015-08-28 Published:2021-09-14

摘要: 与传统金属材料不同,玻璃纤维/树脂基复合材料的结构性能参数离散度较大,直接选用结构测试的平均值作为计算参数的可靠度不高。因此,复合材料结构特性研究在设计中的应用越来越重要,设计时必须使用经统计处理后的强度性能。本文概述了复合材料A/B基准值的计算方法,比较了两种方法计算复合材料A/B基准值的精确度;分析了玻璃纤维/树脂基复合材料结构性能参数的影响因素。结果表明,随着样本容量的增大,复合材料A/B基准值的准确度越高,采用正态分布比采用Weibull分布更容易获得较高的B基准值。样本离散性越大,B基准值保持率越小。

关键词: 复合材料, 玻璃纤维, A/B基准值, 正态分布, 离散系数

Abstract: Compared to traditionally-used metal materials, the structural parameters of glass fiber reinforced polymer (GFRP) composites have a large variation. The design parameters taken from the average values obtained from the structural test are thus not reliable. Therefore, investigations on mechanical properties of GFRP composites became increasingly important in their structural design. The strength values treated using statistical data should be used for design. The goal of this paper was to give a brief overview of the two methods for calculating A/B-basis values of GFRP composites, and to compare the accuracy of the two methods. The influential factors which affect the structural parameters of GFRP composites were also elaborated. The results show that the accuracy of the A/B-basis values improves with increasing the sample size; the use of the normal distribution leads to higher B-basis values than the use of the Weibull distribution. In addition, the conservation rate of the B-basis values reduces as the coefficient of variation of the samples becomes larger.

Key words: composite materials, glass fiber, A/B-basis, normal distribution, coefficient of variation

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