FAILURE PREDICTION OF FIBER-REINFORCED MATERIALS WITH NEURAL NETWORKS

被引：10

作者：

LABOSSIERE, P ^{[1
]}

TURKKAN, N ^{[1
]}

机构：

[1] UNIV MONCTON,ECOLE GENIE,MONCTON E1A 3E9,NB,CANADA

来源：

JOURNAL OF REINFORCED PLASTICS AND COMPOSITES | 1993年 / 12卷 / 12期

关键词：

D O I：

10.1177/073168449301201202

中图分类号：

TB33 [复合材料];

学科分类号：

摘要：

Neural networks can be used to predict failure of anisotropic materials under any loading condition, provided that sufficient experimental data were initially available for the system to ''learn'' the rules. An example failure envelope for a typical fibre-reinforced material is obtained using this method.

引用

页码：1270 / 1280

页数：11

共 9 条

[1]

BrainMaker, 1989, BRAINMAKER

[2] ON THE DETERMINATION OF THE STRENGTH PARAMETERS IN THE TENSOR POLYNOMIAL FAILURE CRITERION [J].