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Adhesively bonded joints composed of pultruded adherends: Considerations at the upper tail of the material strength statistical distribution

机译:拉挤被粘物组成的胶粘接头:材料强度统计分布上尾的注意事项

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摘要

The Weibull distribution, used to describe the scaling of strength of materials, has been verified on a wide range of materials and geometries; however, the quality of the fitting tended to be less good towards the upper tail. Based on a previously developed probabilistic strength prediction method for adhesively bonded joints composed of pultruded glass fiber-reinforced polymer (CFRP) adherends, where it was verified that a two-parameter Weibull probabilistic distribution was not able to model accurately the upper tail of a material strength distribution, different improved probabilistic distributions were compared to enhance the quality of strength predictions. The following probabilistic distributions were examined: a two-parameter Weibull (as a reference), m-fold Weibull, a Grafted Distribution, a Birnbaum-Saunders Distribution and a Generalized Lambda Distribution. The Generalized Lambda Distribution turned out to be the best analytical approximation for the strength data, providing a good fit to the experimental data, and leading to more accurate joint strength predictions than the original two-parameter Weibull distribution. It was found that a proper modeling of the upper tail leads to a noticeable increase of the quality of the predictions.
机译:威布尔分布用于描述材料强度的缩放比例,已在各种材料和几何形状上得到了验证。但是,配件的质量趋于朝上尾巴变差。基于先前开发的拉挤玻璃纤维增​​强聚合物(CFRP)被粘物组成的胶接接头的概率强度预测方法,在此方法中,验证了两参数Weibull概率分布无法准确地建模材料的上尾部强度分布,比较了不同的改进概率分布,以提高强度预测的质量。检查了以下概率分布:两参数Weibull(作为参考),m倍Weibull,嫁接分布,Birnbaum-Saunders分布和广义Lambda分布。事实证明,广义Lambda分布是强度数据的最佳分析近似值,与实验数据非常吻合,与原始的两参数Weibull分布相比,可以得出更准确的接头强度预测。发现上尾部的正确建模导致预测质量的显着提高。

著录项

  • 来源
    《Probabilistic engineering mechanics》 |2009年第3期|358-366|共9页
  • 作者单位

    Composite Construction Labaratory CCLab, Ecole Polytechnique Federate de Lausanne EFFL, BP 2225, Station 16, CH-1015 Lausanne, Switzerland;

    Composite Construction Labaratory CCLab, Ecole Polytechnique Federate de Lausanne EFFL, BP 2225, Station 16, CH-1015 Lausanne, Switzerland;

    IACS, Chair of Modeling and Scientific Computing, Eco!e Polytechnique Federate de Lausanne, CH-1015 Lausanne, Switzerland;

    CEA SACLAY - ENSMP, DEN-DANS/DMN/SRMA/LC2M, Bat, 455, 91191 Gif-sur-Yvette Cedex, France;

    Civil Engineering and Architecture Department, Instituto Superior Tecnko, Technical University of Lisbon, Av. Rovisco Pais 1049-001 Lisboa, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    A. Adhesive joints; B. Modeling; B. Strengtn; C. Failure criterion; C. Probabilistic methods;

    机译:A.胶接点;B.建模;B.加强;C.失效标准;C.概率方法;

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