Prediction of fatigue crack growth using convolutional neural network (1st Report, Prediction for a single crack with angle)

Prediction of fatigue crack growth using convolutional neural network (1st Report, Prediction for a single crack with angle)

This paper presents a method for predicting the crack growth shape and the number of cycles of a two-dimensional fatigue crack under cyclic loading using a convolutional neural network. All of data sets for train are generated by s-version FEM for fatigue crack propagation analysis. The crack propag...

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Bibliographic Details
Main Authors: Takuya TOYOSHI, Rekisei OZAWA, Ryuhei TAICHI, Yoshitaka WADA
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2022-10-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
fatigue crack growth
convolutional neural network
data augmentation
deep learning
crack growth prediction
s-version fem
Online Access:https://www.jstage.jst.go.jp/article/transjsme/88/915/88_22-00188/_pdf/-char/en

Internet

https://www.jstage.jst.go.jp/article/transjsme/88/915/88_22-00188/_pdf/-char/en

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