Correlations for undrained shear strength of Finnish soft clays

Abstract

The study focuses on the derivation of transformation models for undrained shear strength (su) of Finnish soft sensitive clays. Specific correlation equations for su of Finnish clays are presented in this work for the first time. Field and laboratory measurements from 24 test sites in Finland are exploited for this purpose and a multivariate database is constructed. The multivariate data consist of su from the field vane test, preconsolidation stress, vertical effective stress, liquid limit, plastic limit, natural water content, and sensitivity. The main objective is to evaluate the interdependence of su, consolidation stresses, and index parameters and provide a consistent framework for practical use. The new correlations are established through regression analyses. The constructed framework is further validated by another independent multivariate database of clays from Sweden and Norway as well as by empirical equations for Swedish and Norwegian clays. Existing correlations are evaluated for Finnish and Scandinavian clays. Finally, bias and uncertainties of the new correlations are presented.

Reply to the discussion by Mesri and Wang on “Correlations for undrained shear strength of Finnish soft clays”

“…The m values for Finnish clays, denoted by the parameter ␤ in Table 9 in D'Ignazio et al (2016), are consistent with the values reported by Ladd et al (1977) for natural clays from different test types. Moreover, for Norwegian soft clays, Karlsrud and Hernandez-Martinez (2013) suggested that the coefficient m may well be material-dependent, based on laboratory tests on highquality specimens (retrieved by block sampling) taken at different depths and reconsolidated to their in situ effective stress before shearing.…”

“…As mentioned, our paper (D'Ignazio et al 2016) aimed to provide a probabilistic model to estimate s u / v of Finnish soft clays. The S and m values reported as ␣ and ␤ in Table 9 of D'Ignazio et al (2016) and the values in Table R1 are sample mean values derived from small sample sizes that are associated with statistical uncertainties. That means that a different sample may produce a different sample mean value.…”

“…(R1) to the data points, assuming the exponent m to be equal to 1. Our paper (D'Ignazio et al 2016) did not aim at studying the value of exponent m. We perform such a study in this reply using, however, regression analysis rather than manual fitting. We believe that a regression approach is to be preferred because the method seeks to maximize the coefficient of determination (r 2 ) by adjusting both S and m.…”

Discussion of “Correlations for undrained shear strength of Finnish soft clays”

“…In spite of an expected data scatter in Figs. D1 and D2, the soft clay data tabulated by D'Ignazio et al (2016) are consistent with conclusion 1. Part of the scatter in Figs.…”

A Bayesian Approach in the Evaluation of Unit Weight of Mineral and Organic Soils Based on Dilatometer Tests (DMT)

“…Statistical analysis has been applied on the measurement results obtained from the DMT field tests [40,41]. Additionally, p 0 and p 1 pressures were measured.…”