Fracture properties of dolomite and prediction of fracture toughness based on BP-ANN.

ABSTRACT: In this study, based on the digital image correlation technique, three-point bending tests were conducted on dolomite semi-circular bending (SCB) specimens, and the fracture properties of the SCB specimens, including crack opening displacement, apparent fracture toughness (K_If) calculated using the initial crack length and true fracture toughness (K_Ic) calculated using the effective crack length, were investigated first. Then, two datasets were constructed, incorporating specimen size parameters (such as radius, span, and initial crack length), tensile strength and fracture toughness. Considering the impact of specimen size, three backpropagation artificial neural network (BP-ANN) models were developed, two for predicting K_If and one for K_Ic resp

SUBMITTER: Guo Y 

PROVIDER: S-EPMC11830789 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature