Abstract

In critical state soil mechanics, the critical state refers to the combination of effective stress and void ratio (e) at which a soil continues to shear with no change in effective stress, shear stress, and e. The phenomena can be visualized using the critical state line (CSL). The CSL represents the locus of e at critical state with effective mean stress (σ′mean). To define the CSL, the CSL slope (λ), termed “compressibility,” and CSL y-axis intercept at 1 kPa (Γ), termed “altitude,” are required. The CSL in e – σ′mean space provides a simple model of complex soil behavior that allows engineers to construct constitutive models using the state parameter (ψ), which is the mathematical difference between the in-situ e of the soil and the e of the soil at critical state. Currently, Γ can be obtained only through laboratory testing, while λ and ψ can be obtained via laboratory testing or correlation. This paper presents forthcoming correlations based on the ΔQ soil behavior index (which is obtained via the cone penetration test, CPT) to forecast Γ, λ, and ψ, and compares the ΔQ-based correlations’ performance to other CPT-based correlations as well as to data obtained from literature. To compare the correlations, the authors used data from a site investigation performed in Fraser River sand as part of the Canadian Liquefaction Experiment.

Abstract

In critical state soil mechanics, the critical state refers to the combination of effective stress and void ratio (e) at which a soil continues to shear with no change in effective stress, shear stress, and e. The phenomena can be visualized using the critical state line (CSL). The CSL represents the locus of e at critical state with effective mean stress (σ′mean). To define the CSL, the CSL slope (λ), termed “compressibility,” and CSL y-axis intercept at 1 kPa (Γ), termed “altitude,” are required. The CSL in e – σ′mean space provides a simple model of complex soil behavior that allows engineers to construct constitutive models using the state parameter (ψ), which is the mathematical difference between the in-situ e of the soil and the e of the soil at critical state. Currently, Γ can be obtained only through laboratory testing, while λ and ψ can be obtained via laboratory testing or correlation. This paper presents forthcoming correlations based on the ΔQ soil behavior index (which is obtained via the cone penetration test, CPT) to forecast Γ, λ, and ψ, and compares the ΔQ-based correlations’ performance to other CPT-based correlations as well as to data obtained from literature. To compare the correlations, the authors used data from a site investigation performed in Fraser River sand as part of the Canadian Liquefaction Experiment.

Abstract

The state parameter is the main variable employed for predicting the undrained behaviour of artificial soils such as tailings and hydraulic fills. Current practice involves using screening methods and CPTu data (e.g. Robertson (2010)) or cavity expansion based methods (e.g. Shuttle and Jefferies (2016)). However, these methods have drawbacks: they are based on empirical correlations for clean sands and do not consider the effect of partial drainage. This paper presents a site-specific procedure to determine the state parameter of tailings, inspired in the work by Monforte (2022). The procedure consists of: i) calibrating the CASM constitutive model using triaxial tests for different state parameters; ii) determining the plausible range of hydraulic conductivity based on dissipation tests; and iii) conducting numerical simulations of CPTu tests using the Pocket G-PFEM tool for different combinations of state parameters and hydraulic conductivities. By comparing the results of the simulations with the real CPTu data, a site-specific relationship between the state parameter and the CPTu measurements can be established. To validate the procedure, the method is applied to a real tailings deposit and contrasted against routine screening methods. In the particular case studied in this paper, the method predicts more contractive behaviour than the screening methods. While the method is still in an early stage of development, it looks very promising because it allows for using the raw CPTu data to calibrate a constitutive model, without resourcing to any kind of correlations or empirical transformation models.

Abstract

Cone penetration tests (CPTs) can provide quantitative information about the mechanical state of sandy soils. In the current state of the art, the soil state is derived from the cone resistance, which is estimated from the cavity expansion solution and a calibrated scaling equation. Recently, Martinelli and Pisano (2022) showed that MPM simulations of CPTs provide accurate values of the cone resistance in sandy soils when using the critical state NorSand model. This paper adopts this framework to develop a predictive equation for cone resistance as a function of the NorSand parameters and the state parameter of the soil. This formula is straightforward to implement, and it can be adopted by researchers and practitioners to assess soil state in a soil deposits.