Prediction of Strength Properties of Soils Using the Dynamic Cone Penetrometer Index

ABSTRACT Strength of the subgrade plays a vital role in the design and construction of pavements. Traditional subgrade strength evaluation techniques consume more time and are labor-intensive. This study uses dynamic cone penetrometer index (DCPI) and other soil properties to predict the strength of subgrade soils including unconfined compressive strength (UCS) and California bearing ratio (CBR). In this study, silty sands from three local sites are considered for evaluation and various tests including compaction, UCS, CBR, and dynamic cone penetrometer tests, are conducted. To study the effect of density and water content, soil specimens were prepared at different relative density (Rc) levels, such as the dry side of optimum, at optimum, and the wet side of optimum. Soil at maximum dry unit weight and optimum moisture content attains higher strength, demonstrating that the DCPI of soil is inversely correlated with UCS and CBR. The correlations proposed in previous studies are used to predict the UCS and CBR based on DCPI to check their suitability for local soils, and the results indicate that a few models are not suitable for the local soils and are attributed to the regional variations. Further, new correlations are proposed to predict UCS and CBR using DCPI alone and DCPI combined with dry unit weight and water content. The proposed correlations demonstrate a good correlation with an R2 value of 0.987 and acceptable average absolute errors, which prove their accuracy and feasibility for practical usage in local silty soils. Sensitivity analysis indicates that DCPI is the main influential factor in strength prediction, followed by dry unit weight and water content. Overall, the study recommends proposed the predictive models for more reliable strength prediction of local silty sands.