An Intelligent System for Crack Growth Prediction with the $R$-ratio Effect

In this paper, crack growth behaviour under different R-ratios is studied and a new ANN-based intelligent system for analysing crack growth behaviour with respect to R-ratio effects is developed. Considering the limitations of the Paris law in practical application, the inherent non-linear relationships between the Paris constants and the R-ratio are approximated by two ANN models, respectively. Following training with a small experimental dataset, the proposed ANN models have the capability of estimating the unknown Paris constants for a new certain R-ratio. The simulation results with the experimental datasets of Al2024-T351 confirm that both the developed system and the algorithms are efficient and applicable.

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