Uniaxial tension damage mechanics of steel fiber reinforced concrete using acoustic emission and machine learning crack mode classification

Abstract

This paper presents a new scalar plastic damage constitutive model in tension for steel fiber reinforced concrete. It considers the coupled mechanism of matrix bridging and fiber bridging using the Helmholtz free energy. A total of 27 steel fiber reinforced concrete specimens with three concrete matrix strengths and three fiber volume fractions were subjected to three-point bending tests. The acoustic emission monitoring method was utilized to detect the evolution of the released strain energy within the fracture process zone. A machine learning based framework was designed to classify the acoustic emission signals into tension-crack mode and shear-crack mode ones. The relationships between the fiber volume fraction and the plastic strain and between the characteristic length and crack opening displacement were identified. Furthermore, empirical expressions for the two damage variables dm and df corresponding to concrete matrix and steel fibers, respectively, were developed based on the detected results of the evolution of the released strain energy and the strain at the notch tip. The proposed model was validated by comparing it with the models of fib Model Code 2010 and RILEM TC 162-TDF. The results show that the proposed model can reliably predict the strength, post softening or hardening branch, unloading and stiffness degradation of steel fiber reinforced concrete in uniaxial tension.