scholarly journals Determination of undrained shear strength using fall-cone device

2018 ◽  
Author(s):  
Luka Pušić ◽  
Danijela Jurić Kaćunić
Keyword(s):  
Shear Strength ◽  
Undrained Shear Strength ◽  
Undrained Shear

Determination of the consistency limits of soils by the fall cone test

1986 ◽  
Vol 23 (2) ◽  
pp. 241-246 ◽  
Author(s):  
Y. Wasti ◽  
M. H. Bezirci
Keyword(s):  
Shear Strength ◽  
Key Words ◽  
Water Content ◽  
Strength Criterion ◽  
Undrained Shear Strength ◽  
Wide Range ◽  
Undrained Strength ◽  
Content Range ◽  
Undrained Shear

The liquid and plastic limits for a variety of natural and artificial soils covering a wide range of plasticity, as determined by the Casagrande method and the fall cone test and based on a strength criterion, were compared. To check the validity of the strength criterion, the undrained shear strength of these soils has been determined with a laboratory vane over the water content range between these limits. A limited comparison of the undrained strength values obtained from the vane test and fall cone test is also given. Key words: Atterberg limits, consistency, fall cone, laboratory vane, shear strength.

scholarly journals The use of dilatometer test for the determination of undrained shear strength in organic soils

2008 ◽  
Vol 40 (1) ◽  
pp. 97-105
Author(s):  
Simon Rabarijoely
Keyword(s):  
Shear Strength ◽  
Undrained Shear Strength ◽  
Organic Soils ◽  
Engineering Practice ◽  
Empirical Correlations ◽  
Empirical Formulas ◽  
Geotechnical Design ◽  
Design Calculations ◽  
Undrained Shear

The use of dilatometer test for the determination of undrained shear strength in organic soils The use of dilatometer test for the determination of undrained shear strength in organic soils. In engineering practice the empirical correlations or charts are often use to determine soil properties for design calculations. The DMT tests results are analysed on the basis of the empirical formulas proposed by Marchetti (1980). In this paper the new chart to determine the τfu of organic mud was proposed. The chart presents the relationships between dilatometer readings (p0 - u0), (p1 - u0), σ'v0 and τfu. The chart will be helpful in geotechnical design of embankments constructed on organic subsoil.

scholarly journals CPT-Based Probabilistic Characterization of Undrained Shear Strength of Clay

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Mi Tian ◽  
Xiaotao Sheng
Keyword(s):  
Shear Strength ◽  
Correlation Function ◽  
Random Field ◽  
Site Investigation ◽  
Undrained Shear Strength ◽  
Bayesian Approaches ◽  
Probabilistic Characterization ◽  
Undrained Shear

Applying random field theory involves two important issues: the statistical homogeneity (or stationarity) and determination of random field parameters and correlation function. However, the profiles of soil properties are typically assumed to be statistically homogeneous or stationary without rigorous statistical verification. It is also a challenging task to simultaneously determine random field parameters and the correlation function due to a limited amount of direct test data and various uncertainties (e.g., transformation uncertainties) arising during site investigation. This paper presents Bayesian approaches for probabilistic characterization of undrained shear strength using cone penetration test (CPT) data and prior information. Homogeneous soil units are first identified using CPT data and subsequently assessed for weak stationarity by the modified Bartlett test to reject the null hypothesis of stationarity. Then, Bayesian approaches are developed to determine the random field parameters and simultaneously select the most probable correlation function among a pool of candidate correlation functions within the identified statistically homogeneous layers. The proposed approaches are illustrated using CPT data at a clay site in Shanghai, China. It is shown that Bayesian approaches provide a rational tool for proper determination of random field model for probabilistic characterization of undrained shear strength with consideration of transformation uncertainty.

scholarly journals Correlation between Compaction Characteristics with undrained Shear Strength of Soils found in Burayu Town

2021 ◽  
Author(s):  
SOLOMON KORMU ◽  
Alemineh Sorsa
Keyword(s):  
Shear Strength ◽  
Linear Regression ◽  
Soil Compaction ◽  
Undrained Shear Strength ◽  
Coefficient Of Determination ◽  
Red Clay ◽  
Compaction Characteristics ◽  
Undisturbed Samples ◽  
Undrained Shear

Abstract The shear strength of the soil is an important factor to know the internal resistance of soil against external loads causing shearing forces. Shear strength parameters are mandatory for the analysis of load bearing capacity of the soil, the stability of Geotechnical structures and in analysing stress and strain characteristics of soils. The undrained shear strength is one type of shear strength parameter. This parameter is conducted by undisturbed samples. But due to handling, transportation, release of overburden pressure and poor laboratory conditions, it is difficult to obtain accurate undisturbed samples. So, prediction of undrained shear strength parameters (cu) for cohesive soil with the help of compaction characteristics provides a good alternative to minimize this problem. Therefore, this study was conducted to develop the correlation between undrained shear strength values with soil compaction characteristics specifically located in Burayu town. The study was carried out using thirty samples collected from the town. By using the test result regression based statistical analysis was carried out to develop the intended correlation. The parameters considered for this study are Atterberg's limits, Grain size analysis, Specific gravity, Compaction tests and unconfined compression test. The test procedures were based on AASHTO and ASTM laboratory test standards. These parameters are used to establish equations of correlations between undrained shear strength values with soil compaction. The soil type found in Burayu town was highly plastic red clay soil. Based on both single and multiple linear regression analysis relatively good correlation is obtained by combining undrained shear strength (qu ) with maximum dry density and optimum moisture content of red clay soil. From the correlation analysis the equations developed are qu = - 3105 + 1625 MDD + 40.9 OMC with coefficient of determination of R2 =0.828 for multiple linear regression and qu= - 1473 + 57.8 OMC and qu= - 4861 + 3910 MDD with coefficient of determination of R2=0.787 and R2 =0.601 for single linear regression respectively. Generally, the intended correlation obtained from the study area fulfil the basic requirement of regression.

Disturbance effects in pressuremeter tests in clay

2004 ◽  
Vol 41 (4) ◽  
pp. 738-759 ◽  
Author(s):  
Vincenzo Silvestri
Keyword(s):  
Shear Strength ◽  
Strain Curve ◽  
Undrained Shear Strength ◽  
Case Histories ◽  
Stress Strain ◽  
Test Analysis ◽  
Hardening Material ◽  
Expansion Test ◽  
Undrained Shear

This paper analyzes the effect of borehole disturbance, caused by installation of pressuremeter probes in clays, on the derived stress–strain curves. Both overpushing- and overcutting-induced disturbances are considered. It is shown that overpushing results in underestimation of the undrained shear resistance. In general, the degree of underestimation cannot be determined. As for overcutting, the derived stress–strain curves are characterized by high peak strengths. The degree of overestimation of the undrained shear strength may reach 100% for the case of a strain-hardening material. Determination of the strain that corresponds to the peak shear strength allows determination of the true stress–strain curve from the expansion test. Analysis of four well-documented case histories serves to illustrate the proposed approach.Key words: pressuremeter, borehole disturbance, clay, stress-strain curves, case histories, undrained shear strength.

SPT based determination of undrained shear strength: Regression models and machine learning

2019 ◽  
Vol 14 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Walid Khalid Mbarak ◽  
Esma Nur Cinicioglu ◽  
Ozer Cinicioglu
Keyword(s):  
Machine Learning ◽  
Shear Strength ◽  
Regression Models ◽  
Undrained Shear Strength ◽  
Undrained Shear
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