Meso-crack evolution based constitutive model for concrete material under compression

Concrete is a heterogeneous material at the mesoscale, with components that significantly influence its macroscale behavior. In this study, a wings-crack based model which could reflect the influence of coarse aggregate and cement mortar on stress-strain relationship of concrete under compression was proposed. The wings-crack was assumed to be the form of a sliding main crack with two asymmetrically distributed type I wing cracks. The size of the main crack was considered to follow a random distribution based on the coarse aggregate sieve curve, while the propagation of wing cracks was controlled by the type I fracture toughness of the cement mortar. By incorporating the wings-crack model into an evolution square, crack interaction as concrete approached failure was considered by the difference between the evolution square size and the wing crack length. The influence of coarse aggregate gradation, coarse aggregate content, and water-to-cement ratio on the stress-strain relationship was successfully reproduced through an appropriate parameter determination method, and good agreement with experimental results were achieved. Additionally, the crack evolution process was also studied by the active wings-crack number, the velocity of main crack slip, and the speed of wing crack propagation extracted from the model. Comparisons with acoustic emission (short for AE) data revealed similar trends between the model and experimental observations.

Automated summary

A wings-crack based model was proposed to simulate the stress-strain relationship of concrete under compression by considering the influence of coarse aggregate and cement mortar. The model successfully reproduced the effects of coarse aggregate gradation, content, and water-to-cement ratio on the stress-strain relationship, and showed good agreement with experimental results. The crack evolution process was also studied, and similar trends were observed compared to experimental observations.