Macro- and Microscopic Fracture Behavior of Hydraulic Asphalt Concrete Across Varying Temperatures

Abstract

Temperature significantly affects the crack resistance of hydraulic asphalt concrete (HAC) in engineering applications. This study performed three-point bending fracture tests on HAC single-edge notches deep beams (SENDB) at testing temperatures (T) from 6 °C to 18 °C. HAC fracture behavior was comprehensively analyzed by integrating macroscopic fracture performance indicators with mesoscale parameters extracted via digital image correlation (DIC). The results indicate that at the T below 9 °C, cracks propagate more locally through coarse aggregates, with direct penetration occurring within the coarse aggregates. In contrast, when T exceeds 9 °C, the main crack predominantly propagates along the interface between coarse aggregates and asphalt mortar. With further increases in T, asphalt softening induces micro-displacement and slippage between aggregates, leading to the formation of secondary microcracks outside the primary fracture path. Regions characterized by closely spaced aggregates or interfaces aligned with the loading direction are more susceptible to serving as preferential paths for crack propagation. With an increasing T, the peak load (Pmax) gradually decreases while the peak displacement increases. Both the effective fracture toughness (KIC*) and fracture energy (Gf) exhibit a declining trend, whereas the critical crack tip opening displacement (CTOD), crack tip strain (Exx), and horizontal strain density (DE) progressively increase. Furthermore, predictive equations were formulated to correlate each parameter to T, and supplementary models were developed to predict Gf and KIC* based on DE. These correlations exhibit robust consistency, facilitating bidirectional prediction between macroscopic and mesoscale fracture parameters, and offering a robust framework for investigating the fracture behavior of HAC.

Keywords: hydraulic asphalt concrete, Fracture, Deep beam, temperature, Digital image correlation