Decision support for selecting optimal method of recycling waste tire rubber into wax-based warm mix asphalt based on fuzzy comprehensive evaluation

Abstract

Recycling crumb rubber (CR) derived from waste vehicle tire as asphalt modifier is an effective waste management approach with both engineering and environmental merits. However, the high viscous asphalt rubber (AR) brings higher energy consumption and hazardous construction emission. Wax-based warm mix asphalt (WMA) additive has proven to be able to alleviate these concerns. Application of WMA additives enriches the methods of recycling CR into asphalt. Preliminary investigations documented the effects of CR recycling methods on the service performance of warm crumb rubber modified asphalt mixture (WCRMA). Therefore, making a decision on the optimal recycling method considering the overall service performance is necessary. Nevertheless, there are limited studies focusing on the recycling method assessment and decision-making approach. To fill this gap, WCRMAs with different crumb rubber recycling methods were prepared and tested in laboratory. The effect of the recycling method on the overall service performance of WCRMAs was characterized. A fuzzy comprehensive evaluation (FCE) method was employed to quantify the performance grade of asphalt mixtures according to fuzzy logic. The weight matrix of all the service properties was developed based on the Analytic Hierarchy Process (AHP) under the considering of the circumstance of southern China. The experimental work revealed the significant influence of the recycling method on the service performance of WCRMAs. By means of the FCE method, this study suggested that for southern China with hot and humid climate, the optimal method of recycling CR into wax-based WCRMA is mixing AR and Sasobit first followed by incorporating them into aggregate. In rainy regions, asphalt mixture produced by directly mixing AR, Sasobit, and aggregate at 160 °C may perform better because it showed the best moisture damage resistance and good overall performance.