Artificial Intelligence Techniques in Simulation of Viscoplasticity of Polymeric Composites

被引：7
|
作者：
Al-Haik, M. S. [1 ]
Hussaini, M. Y. [2 ]
Rogan, C. S. [3 ]
机构：
[1] Univ New Mexico, Dept Mech Engn, Albuquerque, NM 87131 USA
[2] Florida State Univ, Sch Computat Sci & Informat Technol, Tallahassee, FL 32306 USA
[3] Princeton Univ, Dept Phys, Princeton, NJ 08544 USA
来源：
POLYMER COMPOSITES | 2009年 / 30卷 / 11期
关键词：
D O I：
10.1002/pc.20745
中图分类号：
TB33 [复合材料];
学科分类号：
摘要：
The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress-viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm-based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 30:1701-1708, 2009. (c) 2008 Society of Plastics Engineers
引用
收藏
页码：1701 / 1708
页数：8
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