Abstract
The crack density and crack growth rate are important parameters, which are used to describe the fatigue damage and predict the fatigue life of a material. There are many researches on the quantitative description of the fatigue cracks density and the crack growth rate, and several models are proposed, but these models cannot be widely used. In this paper, the BP network is used to describe the evolution of the fatigue crack density and the crack growth rate. It can be seen that the proposed method is feasible. The proposed method does not need to determine the interface between the long and short crack, and overcome the shortcoming of traditional models in which physical background of the parameters are uncertain, so it is difficult to determine in engineering.
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References
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Liu, C., Wu, W., Sun, D. (2004). Neural Network Based Fatigue Cracks Evolution. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_132
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DOI: https://doi.org/10.1007/978-3-540-28648-6_132
Publisher Name: Springer, Berlin, Heidelberg
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