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Updated: Feb 14, 2026

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Published on: May 31, 2022
Evolution Mechanism of Volume Parameters and Gradation Optimization Method for Asphalt Mixtures Based on Dual-Domain
Bangyan Hu1,2,3, Zhendong Qian1,3, Fei Zhang2,4
1Intelligent Transportation System Research Center, Southeast University, Nanjing 211189, China.
Abstract:
The primary objective of this study is to bridge the gap between descriptive geometry and mechanistic design by establishing a dual-domain fractal framework to analyze the internal architecture of asphalt mixtures. This research quantitatively assesses the sensitivity of volumetric indicators-namely air voids (VV), voids in mineral aggregate (VMA), and voids filled with asphalt (VFA)-by employing the coarse aggregate fractal dimension (Dc), the fine aggregate fractal dimension (Df), and the coarse-to-fine ratio (k) through Grey Relational Analysis (GRA). The findings demonstrate that whereas Df and k substantially influence macro-volumetric parameters, the mesoscopic void fractal dimension (DV) remains structurally unchanged, indicating that gradation predominantly dictates void volume rather than geometric intricacy. Sensitivity rankings create a prevailing hierarchy: Process Control (Compaction) > Skeleton Regulation (Dc) > Phase Filling (Pb) > Gradation Adjustment (k, Df). Dc is recognized as the principal regulator of VMA, while binder content (Pb) governs VFA. A "Robust Design" methodology is suggested, emphasizing Dc to stabilize the mineral framework and reduce sensitivity to construction variations. A comparative investigation reveals that the optimized gradation (OG) achieves a more stable volumetric condition and enhanced mechanical performance relative to conventional empirical gradations. Specifically, the OG group demonstrated a substantial 112% enhancement in dynamic stability (2617 times/mm compared to 1230 times/mm) and a 75% increase in average film thickness (AFT), while ensuring consistent moisture and low-temperature resistance. In conclusion, this study transforms asphalt mixture design from empirical trial-and-error to a precision-engineered methodology, providing a robust instrument for optimizing the long-term durability of pavements in extreme cold and arid environments.
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