Neural network based prediction on mechanical and wear properties of short fibers reinforced polyamide composites
Neural network based prediction on mechanical and wear properties of short fibers reinforced polyamide composites
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DOI：
10.1016/j.matdes.2007.02.008
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发表时间：
2008-01-01
影响因子：
8.4
通讯作者：
Schlarb, Alois K.
中科院分区：
文献类型：
--
作者：
Jiang, Zhenyu;Gyurova, Lada;Schlarb, Alois K.
应用人工神经网络技术对短纤维增强尼龙(PA)复合材料的力学性能和磨损性能进行了预测。使用两个实验数据库来训练神经网络：一个由101个尼龙4.6复合材料的独立微动磨损试验组成，另一个来自一家商业公司，包括93对尼龙6.6复合材料的独立Izod冲击、拉伸和弯曲试验。预测的性能曲线作为短纤维含量或测试条件的函数，证明了优化后的神经网络对建模关注的显着能力。(C)2007爱思唯尔有限公司。保留所有权利。
The artificial neural network technique was applied to predict the mechanical and wear properties of short fiber reinforced polyamide (PA) composites. Two experimental databases were used to train the neural network: one consisted of 101 independent fretting wear tests of PA 4.6 composites; the other one was from a commercial company and included 93 pairs of independent Izod impact, tension and bending tests of PA 6.6 composites. The predicted property profiles as a function of short fiber content or testing conditions proved a remarkable capability of well-optimized neural networks for modeling concern. (C) 2007 Elsevier Ltd. All rights reserved.