期刊
INTERNATIONAL JOURNAL OF FATIGUE
卷 28, 期 2, 页码 132-140出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijfatigue.2005.04.012
关键词
multiaxial fatigue; artificial neural network; random loading; critical plane method
A back-propagation neural network was applied to fatigue life prediction under multiaxial random loading. The proposed artificial neural network (ANN) model was demonstrated by predicting the multiaxial fatigue life and finding critical locations of an automotive sub-frame within reasonable time. While the conventional methods calculating multiaxial fatigue life with critical plane model require very long-time, this method outputs instantaneously result for a given set of input after the ANN model has been trained. The performance of the ANN model was evaluated by comparing outputs of the ANN with results of the conventional calculation method and acceptable in most fatigue design considerations. Particularly, this method gave good results in searching critical locations. (c) 2005 Elsevier Ltd. All rights reserved.
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。
推荐
暂无数据