4.7 Article

Predicting the nonlinear response and progressive failure of composite laminates

期刊

COMPOSITES SCIENCE AND TECHNOLOGY
卷 64, 期 3-4, 页码 329-342

出版社

ELSEVIER SCI LTD
DOI: 10.1016/S0266-3538(03)00217-3

关键词

composite laminate

向作者/读者索取更多资源

A comprehensive comparison of laminate failure models was established to assess the state-of-the-art in laminate modeling technologies on an international level (known as the Worldwide Failure Olympics Exercise) [1]. This paper represents one contribution (Part A) to the Exercise, where predictions for laminate response and failure behavior of various laminates under a broad range of loading conditions are made. A method for predicting the nonlinear stress/strain response and failure behavior of composite laminates is described. Predictions are based on an incremental formulation of a well-established three-dimensional laminated media analysis [2] coupled with a progressive-ply failure methodology. Nonlinear lamina constitutive relations for the composites are represented using the Ramberg-Osgood equation [3]. Piece-wise linear increments in laminate stress and strain are calculated and superimposed to formulate the overall effective nonlinear response. Individual ply stresses and strains are monitored to calculate instantaneous ply stiffnesses for the incremental solution and to establish ply failure levels. The progressive-ply failure approach allows for stress unloading in a ply and discrimination of the various potential modes of failure. Laminate response and failure predictions for 14 different cases are presented. The cases include prediction of the effective nonlinear stress-vs.-strain responses of laminates, as well as, initial and final ply failure envelope predictions under multi-axial loading. Comparison of predictions with actual experimental data will be made in a companion paper to be published in Part B of the Exercise. Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据