Simulation study reveals enhanced low-temperature crack resistance in warm-mix steel slag asphalt mixtures, highlighting optimized force chain dynamics and delayed fracture propagation.
This study employs the discrete element method (DEM) in conjunction with acoustic emission (AE) experimental data to systematically investigate the low-temperature cracking evolution behaviour of asphalt mixtures incorporating steel slag aggregates and the warm-mix additive SDYK, along with their mesoscopic mechanisms. By simulating the low-temperature loading process of a semi-circular bend (SCB) using DEM, this study captures the characteristics of bond failure, force chain reorganisation, and microcrack propagation at the granular scale, enabling a correlation analysis between the macroscopic mechanical response and micro-damage evolution. The results indicate that steel slag aggregate, owing to its high strength and rough surface characteristics, significantly enhances the force chain load-bearing capacity and optimises load transfer pathways. While the warm-mix additive SDYK improves inter-particle adhesion and structural compactness, resulting in a more continuous and uniform force chain distribution. Together, they establish a force chain system characterised by ‘strong bearing capacity—stable transmission—uniform distribution’, effectively suppressing microcrack propagation and delaying the penetration of primary cracks. Coupled AE–DEM analysis reveals a strong correlation between the sudden increase in cumulative AE energy and the accelerated bonding failure phase in the DEM. Following the incorporation of steel slag and warm-mix additives, the aforementioned critical damage stages were significantly delayed, indicating effective suppression of rapid crack propagation. This study elucidates the mechanism enhancing the low-temperature crack resistance of warm-mix steel slag polymer-modified asphalt mixtures at the micromechanical level, providing theoretical foundations for crack resistance evaluation and material optimisation design based on test-numerical coupling.
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Xiaoyan et al. (2026) studied this question.
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