Use of a machine learning-based framework to approximate the input features of an intrinsic cohesive zone model of recycled asphalt mixes tested at low temperatures University of Antwerp
Although the cohesive zone model (CZM) provides numerous advancements in simulating the crack initiation and evolution in asphalt mixes, its efficiency and applicability are still challenging. This is because asphalt mixes are principally assumed to be homogeneous in CZM modeling despite intrinsic heterogeneity. Therefore, it is essential to calibrate the CZM model, by adjusting the input factors, aiming at alleviating this inconsistency between ...