Enhancing Granular Surface Material Performance Using California Bearing Ratio and Repeated Load Triaxial Tests

Granular-surfaced roads are prone to significant wear and damage due to heavy agricultural traffic and freeze-thaw cycles, which tend to increase maintenance costs and safety risks. While previous studies have explored the role of particle size distribution in influencing properties like resilient modulus (MR) and California Bearing Ratio (CBR) of surfacing aggregates, limited research has focused on quantifying the effects of gradation on the mechanical performance of such roads. The present study addresses this gap by analyzing laboratory tests, including soaked CBR, MR, and plastic strain (εp), combined with statistical analysis to assess the impact of gradation variations. The gradation of the tested materials was parametrized using a two-parameter sigmoidal model to enable optimization based on values of soaked CBR, MR, and plastic strain. Two specimen sets were analyzed: one with six mixtures of virgin quarry aggregates and another with six mixtures of virgin aggregates blended with existing roadway surface materials. The findings show that incorporating existing surface materials into the virgin materials enhances the strength and stiffness while significantly influencing the optimum gradation parameters. This research presents an approach involving gradation analysis, experimental testing, and statistical modeling to identify the optimal gradation. By adopting this systematic process, engineers and practitioners can develop cost-effective solutions for constructing and rehabilitating granular-surfaced roads, ultimately enhancing their durability and performance while reducing long-term maintenance demands.