Fatigue Characterisation of WMA and Modelling Using Artificial Neural Networks

Abstract

This study presents an investigation into the fatigue performance of WMA and the effect of mixing temperature on fatigue cracking of WMA tested in a dynamic shear rheometerm (DSR). WMA (organic and chemical technologies) was manufactured at 125 C (for modified soft binder, 100/150) and 135 C and 145 C (for modified hard binder, 40-60), while the control hot mix asphalt (HMA) was mixed at 145 C for modified soft binder and 155 C for modified hard binder. Despite the fact that WMA modified with hard binder was successfully manufactured at a temperature 20 C lower than the traditional HMA and the aggregate was completely coated, its fatigue life was lower than the traditional HMA. However, when WMA modified with hard binder was manufactured at a temperature only 10 C lower than the traditional HMA, its fatigue resistance significantly increased. In addition, successful reduction in the production temperature of up to 20 C as achieved for WMA modified with soft binder. In other words, the WMA production temperature should be identified based on the grade of the bitumen in order to produce an asphalt mixture which has a better performance than the traditional HMA. After taking the production temperatures into account, in all scenarios, Rediset WMX increased the fatigue life by approximately 32% while Rediset LQ doubled the fatigue life of the asphalt mixture and Sasobit increased the fatigue life by approximately 90%. Furthermore, an Artificial Neural Network (ANN) was used to model and predict the fatigue performance of WMA.