Prediction of fatigue crack growth using convolutional neural network (2nd Report, Prediction of crack propagation on different levels)

Prediction of fatigue crack growth using convolutional neural network (2nd Report, Prediction of crack propagation on different levels)

In this paper, the prediction of crack propagation with two cracks using machine learning is described. The analysis results of crack propagation by s-version FEM (s-FEM), which combines the automatic mesh generation technique, are used for generation of training and validation datasets. Plural crac...

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Bibliographic Details
Main Authors: Rekisei OZAWA, Takuya TOYOSHI, Ryuhei TAICHI, Yoshitaka WADA
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2023-07-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
fatigue crack growth
crack growth prediction
interaction effect
s-version fem
convolutional neural network
data augmentation
deep learning
Online Access:https://www.jstage.jst.go.jp/article/transjsme/89/924/89_23-00032/_pdf/-char/en

Internet

https://www.jstage.jst.go.jp/article/transjsme/89/924/89_23-00032/_pdf/-char/en

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