Parameter estimation in multiaxial fatigue short crack growth model using hierarchical Bayesian linear regression.

Multiaxial fatigue failure is the most common problem in engineering structures. It is worth noting that short crack growth accounts for most of the fatigue life. Hence, it is necessary to study the short crack growth models for multiaxial fatigue life assessment. The primary focus of this study is to develop a hierarchical Bayesian linear regression method to estimate parameters in multiaxial fatigue crack growth model. The Bayesian method is used to estimate the intercept and slope of the regression equation for each loading path and ensemble test datasets. The method of this work was demonstrated on three multiaxial fatigue crack growth datasets. The main results obtained in this paper were that the parameters of the multiaxial fatigue crack growth model changed significantly with different loading paths, and the parameters of the model depended on the multiaxial loading path. Highlights: An equivalent strain‐based intensity factor ΔKESA was proposed.Hierarchical Bayesian linear regression is developed for parameter estimation.Hierarchical Bayesian model considers the differences of each loading paths.The parameters of the fatigue crack growth model depend on the loading path. [ABSTRACT FROM AUTHOR]