Transformation models for the compressibility properties of Finnish clays using a multivariate database

Abstract

The compression index obtained from an oedometer test is often used to estimate the settlements of clayey subsoil, but compressibility parameters are rarely available during the preliminary geotechnical design phase. Various empirical correlations linking compressibility to other properties such as water content have been proposed. However, as Scandinavian clays are soft and exhibit greater compressibility, the existing transformation models for compressibility can be biased when applied to Finnish clays. This paper compiles a partial multivariate database of Finnish clayey soils and demonstrates that the existing transformation models tend to underestimate the compressibility of Finnish clays. The new transformation models are constructed by means of a 2-degree polynomial regression applied to the natural logarithms of the soil properties. Finally, the transformation uncertainties are quantified via the standard deviation of errors and the coefficient of variation. The best predictors for the compressibility of Finnish clayey soils were found to be the void ratio and water content. When the void ratio was combined with a secondary predictor, such as the ratio between undrained shear strength and preconsolidation pressure or plastic limit, the transformation uncertainty decreased notably.

CatBoost–Bayesian Hybrid Model Adaptively Coupled with Modified Theoretical Equations for Estimating the Undrained Shear Strength of Clay

“…The data used in this study were derived from the FI-CLAY/14/856 dataset in the TC304 database, made up of laboratory test data of clay parameters in 33 regions in Finland [50,51]. In this study, 11 parameters of 202 Finnish clay samples were selected for research, including organic content (𝑂𝑟𝑔), clay content (𝐶𝐼), void ratio (𝑒), natural water content (𝑊), liquid limit (𝐿𝐿), plastic limit (𝑃𝐿), effective overburden pressure (𝜎 𝑣𝑖 ′ ), preconsolidation pressure (𝜎 𝑣0 ′ ), overconsolidation ratio (𝑂𝐶𝑅), compression index (𝐶 𝑐 ), sensitivity (𝑆 𝑡 ), and undrained shear strength (𝑆 𝑢 ); the statistical results of this data set are as follows (Table 1 [51], Figure 4).…”

“…The data used in this study were derived from the FI-CLAY/14/856 dataset in the TC304 database, made up of laboratory test data of clay parameters in 33 regions in Finland [50,51]. In this study, 11 parameters of 202 Finnish clay samples were selected for research, including organic content (𝑂𝑟𝑔), clay content (𝐶𝐼), void ratio (𝑒), natural water content (𝑊), liquid limit (𝐿𝐿), plastic limit (𝑃𝐿), effective overburden pressure (𝜎 𝑣𝑖 ′ ), preconsolidation pressure (𝜎 𝑣0 ′ ), overconsolidation ratio (𝑂𝐶𝑅), compression index (𝐶 𝑐 ), sensitivity (𝑆 𝑡 ), and undrained shear strength (𝑆 𝑢 ); the statistical results of this data set are as follows (Table 1 [51], Figure 4). Figure 5 shows the normal distribution and fitting effect of organic clay content (𝐶𝐼), void ratio (𝑒), natural water content (𝑊), liquid limit (𝐿𝐿 (𝑃𝐿), effective overburden pressure (𝜎 ), preconsolidation pressure (𝜎 ), o tion ratio (𝑂𝐶𝑅), compression index (𝐶 ), and undrained shear strength (𝑆 ysis of the abnormal value of clay undrained shear strength.…”