Evolution Mechanism of Volume Parameters and Gradation Optimization Method for Asphalt Mixtures Based on Dual-Domain...

Area of Science:

• Pavement Engineering
• Materials Science
• Fractal Geometry

Background:

• Asphalt mixture design traditionally relies on empirical methods.
• Understanding the internal architecture's impact on performance is crucial.
• Bridging descriptive geometry and mechanistic design requires advanced analytical tools.

Purpose of the Study:

• To establish a dual-domain fractal framework for analyzing asphalt mixture internal architecture.
• To quantitatively assess the sensitivity of volumetric indicators (VV, VMA, VFA) to fractal parameters (Dc, Df, k).
• To propose a robust design methodology for optimizing asphalt mixture performance.

Main Methods:

• Grey Relational Analysis (GRA) was employed to determine sensitivity rankings.
• Fractal dimensions of coarse (Dc) and fine (Df) aggregates were utilized.
• Comparative analysis between optimized gradation (OG) and conventional gradations was performed.

Main Results:

• Fine aggregate fractal dimension (Df) and coarse-to-fine ratio (k) significantly influence macro-volumetric parameters.
• Mesoscopic void fractal dimension (DV) remained structurally unchanged, indicating gradation's primary role in void volume.
• Sensitivity hierarchy: Compaction > Dc > Pb > (k, Df). Dc regulates VMA; Pb governs VFA.

Conclusions:

• A "Robust Design" methodology emphasizing Dc for mineral framework stabilization is proposed.
• Optimized gradations (OG) yield superior volumetric stability and mechanical performance.
• This research transforms asphalt mixture design into a precision-engineered methodology for enhanced pavement durability.