Machine learning RBF-based surrogate models for uncertainty quantification of age and time-dependent fracture mechanics

This paper proposes a machine learning strategy using radial basis function (RBF) as surrogate models for uncertainty quantification of age and time-dependent fracture mechanics problems. The RBF surrogate models are trained to replace the time-consuming evaluations of the mapping integral of the time-dependent energy release rate. The probabilistic problem considers input random variables of geometry, loading, and material parameters for a...