Selection method of gradation index in hydraulic asphalt concrete considering skeleton effect

Abstract

Currently, the aggregate gradation design method for hydraulic asphalt concrete (HAC) fails to fully consider the primary-secondary contributions and skeleton effects of coarse and fine aggregates in the asphalt mixture matrix, presenting certain limitations. To address this, this study proposes a gradation index selection method based on the Ding Purong formula, aiming to optimize aggregate gradation design by considering skeleton effects to enhance asphalt concrete performance. Through vertical vibration compaction method, this approach measures skeleton strength (CBR value) and compactness indicators (volume change rate, compacted density, void ratio) of aggregates with different gradation index; And perform statistical analysis on the experimental data, comprehensively evaluating and identifying the optimal aggregate skeleton (gradation index n) that simultaneously possesses both strength and density. Under consistent filler concentration and asphalt-aggregate ratio, performance comparisons of asphalt concrete specimens prepared with different skeleton-effect aggregates verified the method's practicality. Results demonstrate: Aggregates with different gradation index show significant skeleton effect differences, with n = 0.37 exhibiting maximum CBR value (156.2 %) combined with minimum void ratio and maximum density; Specimens based on this optimal skeleton achieved peak splitting strength (3.34 MPa) and low porosity (1.74 %). This research provides new theoretical support and technical methodology for HAC gradation design, offering significant engineering application value.