Fatigue strength analysis of stone mastic asphalt (SMA) mixtures using crack meander protocol

Fatigue failure is a common pavement distress other than rutting and permanent deformation. Cracks are typically found along the wheel path of asphalt pavements. Initially, hairline sized micro-cracks propagate and then join together to form macro-cracks. The micro-cracks usually develop as thin, small cracks. Meanwhile macro-cracks manifest as cracks that can be seen on the pavement surfaces in the mature phase of the pavement. Crack meander technique is a method to evaluate the fatigue strength of asphalt mixtures by mapping visual cracks on the surface of the diametral side of cylindrical sample. In this study, a 150 mm diameter sample of Stone Mastic Asphalt with 12.5 mm nominal maximum aggregate size (SMA 12.5) control sample, and two other mixture of SMA with 0.6 percent of Cellulose Oil Palm Fiber (COPF) and 6.0 percent Ethylene Vinyl Acetate (EVA) polymer respectively are tested under Indirect Tensile Fatigue Test (ITFT). The type of aggregate gradation, asphalt type and parameters used in the test are standardized when comparison of performance is made. During ITFT, the crack images on the sample surface are captured using a high-speed digital camera in a fixed distance from the sample for an interval of cyclic loading. Prior to fatigue evaluation, crack properties like crack length, crack area and crack density are measured by mapping of crack propagation using Measurement and Mapping of Crack Meander (MMCM) software. These three crack properties are plotted against fatigue cycle to exhibit the trend of development. The plotted graph is compared with the graph of tensile strain data against fatigue life obtained from real data in ITFT. The comparisons that between crack length analysis and strain data shows both have the same pattern of trendline. It is found that the Crack Meander technique has a high correlation to the real data of tensile strain. This study has shows that visual crack analysis on the sample surface is a reliable approach to evaluate fatigue strength.

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