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

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openAccess

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Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2022-04-03

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Language

en

Pages

17

Series

Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

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.

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Keywords

clay, compressibility, compression index, database, empirical correlations, transformation models

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Citation

Löfman, M & Korkiala-Tanttu, L 2022, ' Transformation models for the compressibility properties of Finnish clays using a multivariate database ', Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, vol. 16, no. 2, pp. 330-346 . https://doi.org/10.1080/17499518.2020.1864410