Determination of composite modulus of concrete containing reclaimed asphalt pavement using micromechanical modelling and soft computing techniques

Abstract

Portland cement concrete (PCC) containing reclaimed asphalt pavement (RAP) is an eco-friendly material, which is beneficial to the economy, society and environment. Before the material can be implemented in the field, a comprehensive evaluation of the effect of the RAP addition on PCC is of great necessity. Modulus of elasticity (MOE), an important measure of concrete material stiffness, dictates the stress and strain in concrete structures. This paper aims to propose a modeling approach to determining the MOE of PCC containing RAP aggregates as a virgin coarse aggregate replacement. Analytical models for individual and composite phases of RAP-PCC were presented and compared. Soft computing techniques including artificial intelligence (AI) algorithms were applied. The study shows that the calibrated model could successfully predict the MOE of RAP-PCC at different curing ages and RAP replacement levels. The proposed approach can serve as a rapid but accurate tool for the determination of the MOE with any RAP replacement levels using limited experimental data.