A failure-dependence related stochastic crack growth modeling approach of competing cracking mode

Competing crack-induced fatigue fracture has been a typical failure mode especially in the very high cycle fatigue regime. However, the stochastic crack growth modeling related to failure-dependence has not been fully investigated. Here, a failure-dependence related stochastic crack growth modeling approach for competing cracking mode is proposed to address this issue. Firstly, copulas are used to model the dependent competing relationships among multiple fatigue fracture modes. The reliability analysis of multiple fatigue fracture modes is conducted from a copula perspective. Besides, the fatigue crack growth is modeled based on a nonlinear Wiener process, with unit-to-unit variability addressed by introducing random effects. Marginal reliability expressions are derived based on the Wiener process. Furthermore, a two-stage Bayesian inference method based on Hamiltonian Monte Carlo sampling is proposed to estimate model parameters. A Monte Carlo simulation study is conducted to validate the accuracy and robustness of the proposed inference method. Finally, the effectiveness of the proposed approach is proven through a real case study. It turns out that the ignorance of the competing relationships among multiple cracking modes leads to an underestimation of overall reliability. The accuracy of the model can be further improved with random effects considered.