Matric Suction-Based Mathematical Model in Predicting California Bearing Ratio Using Dynamic Cone Penetrometer Test

This study examined the limitations of the dynamic cone penetrometer test (DCPT) for predicting soil strength such as California bearing ratio (CBR) and proposed incorporating matric suction, a measure of water retention, to improve accuracy of the existing equation. The current dynamic cone penetration index (DCPI)-CBR equation can significantly deviate from actual CBR values, especially for loose materials. The results demonstrated that A-1-b soils with high water holding capacity had the highest CBR, while A-1-a with tightly packed particles exhibited the lowest. These findings informed the development of new equations for CBR prediction with a coefficient of determination ranging from 0.84 for A-1-a soil and 0.97 for A-1-b soils. The equations performed best with consistent particle size distribution and incorporating matric suction measurements from soil water characteristic curve (SWCC), highlighting the importance of these factors for accurate results. Overall, the study underlines the need to consider moisture content, matric suction, and particle size distribution alongside traditional dynamic cone penetrometer (DCP) methods for reliable CBR prediction in pavement design.