Integrating non-destructive testing data to produce asphalt pavement critical strains

Knowledge of critical strains during the asphalt pavements’ life is an inherent process within pavement structural assessment. Highway agencies need this knowledge to effectively manage potential maintenance activities. Conventional practice includes mechanistic analysis of data collected in-situ. Contrariwise, developing models or algorithms for strain prediction bypasses the time-consuming processes of back-analysis and strain analysis and contributes towards a more efficient assessment. This research deals with adaptability issues of empirical equations suggested in the international literature for the estimation of tensile strains at the bottom of asphalt concrete (AC) layers. For this purpose, non-destructive testing data collected from a trial section of a heavy-duty highway is utilised. Moving forward with the research, new models are developed for AC strain estimation considering the effect of AC temperature on the developed strains. From a statistical view, the high R2 values indicate acceptable goodness of fit for the new equations. These results outline the feasibility of using the developed equations to ensure time and cost savings towards the acceleration of pavement evaluation processes. Besides, these results motivate future research to consider variable pavement structures, material and climatic conditions during model development, since the use of existing equations elsewhere may not be a rational approach.