Evaluating strength characteristics of unsaturated sand soils using dynamic cone resistance Available to Purchase

The long-term performance of asphalt pavements is influenced by the quality of the supporting subgrade, with subgrade required to prevent premature asphalt pavement failures. Quality control (QC) in the conventional subgrade compaction process has usually been limited to attempting to determine spot density and moisture content readings using a nuclear density gauge (NDG). Based on its ability to verify both the level and conformity of compaction, the use of a dynamic cone penetrometer (DCP) would be an extremely valuable method for better construction inspection, while layer thickness could be determined by comparing the changing slope of the depth versus the profile of accumulated blows. DCP would offer low-cost field testing and save time as well as giving a more accurate continuous profile of the pavement layers. Manual driving would also no longer be necessary due to the DCP’s function, and as DCP could quickly locate weak spots, this would offer significant advantages over other in-situ pavement measurement systems. The main goal of this study was thus to create an alternative testing protocol using a dynamic cone penetrometer (DCP) to compute the CBR achieved in the field as a means of evaluating the in-situ strength of unbound pavement layers. DCP data was used to determine the strength of compaction under the influence of different numbers of passes, while in the lab, a sand replacement test (SRM) was used to determine dry density. Two testing methods were then used in three subgrade soil locations: a dynamic test method that incorporated the DCP device to evaluate the strength of unbound pavement layers by computing the CBR achieved in the field, and a static test method with similar aims. The DCP data and SRM results from these locations were then examined to see if there was a link between DD values and DCP parameters. Based on DCP measurement techniques such as CBR and DCPI, statistical analyses were then performed to predict the CBR of subgrade soils. Nonlinear regression analyses for data from subgrade soils produced the most effective correlations with the coefficient of determination, being equal to 89.61. DCP measurements can thus be used to evaluate the strength of unbound pavement layers based on this research.