Estimating shear strength parameters of a fine-grained alluvial soil using resedimented samples and multivariate regression

Abstract The number of studies concerning the shear strength of resedimented alluvial soils is extremely limited compared to the studies conducted on fine-grained marine sediments, since alluvial soils are generally tested in remolded or reconstituted state especially in the studies investigating their liquefaction potential. In this study, estimation models were developed to predict cohesion ( c ) and internal friction angle (ϕ) parameters of a fine-grained alluvial soil using resedimented samples. A total of 60 undisturbed soil samples were obtained from Bafra district of Samsun province (Türkiye) by core drilling. A cone penetration test with pore water pressure measurement (CPTu) was also carried out alongside each borehole to determine the over-consolidation ratios of the samples. Physical-index property determinations and triaxial tests were conducted on the undisturbed samples. 20 sample sets were created with known physical, index, and strength characteristics. The samples are classified as CH, CL, MH, and ML according to the Unified Soil Classification System, with liquid and plastic limits ranging from 31.6–75% and 19.3 to 33.6% respectively. The c and ϕ values of the samples varied from 4.1 to 46.1 kPa and 26 to 35º respectively. The samples were then resedimented in the laboratory under conditions reflecting their original in-situ properties, and triaxial tests were repeated. The c and ϕ values of the resedimented samples ranged from 5.3 to 24.5 kPa and 28 to 32º respectively. The results indicate that the c values of the resedimented samples are generally lower than those of the undisturbed samples, whereas upper and lower bounds for ϕ values are similar. Multivariate regression analyses (MVR) were utilized to develop estimation models for predicting c and ϕ using strength and physical properties of 20 soil samples as independent variables. Three estimation models with R 2 values varying between 0.723 and 0.797 were proposed for c and ϕ which are statistically significant for p ≤ 0.05. Using artificial neural networks (ANN), the estimation models developed by MVR were replicated to validate the models. ANN yielded very similar results to the MVR, where the R 2 values for the correlations between c and ϕ values predicted by both methods varied from 0.852 to 0.955. The results indicate that c and ϕ values of undisturbed samples can be estimated with acceptable accuracy by determining basic physical and index properties of the disturbed samples and shear strength parameters of the resedimented samples. This approach, which enables the reuse of disturbed soil samples, can be used when undisturbed soil samples cannot be obtained from the field due to economic, logistical, or other reasons. Further research on the shear strength parameters of resedimented alluvial soils is needed to validate the estimation models developed in this study and enhance their applicability to a wider range of alluvial soils.