The Presence and Influence of Fissures in the Boulder Clays of West Central Scotland

1975 ◽  
Vol 12 (1) ◽  
pp. 84-97 ◽  
Author(s):  
Alan McGown ◽  
Amr M. Radwan

The recent urban and rural developments in west central Scotland have involved the execution of much more widespread, and often deeper, excavations than previously undertaken in the boulder clays of the area. A number of failures in deep trenches and slope excavations have occurred, whose character appeared to be influenced by the presence of macrofabric features. A detailed field study has confirmed the presence of fissures and showed that they exhibit definite preferred orientation patterns. The influence of these fissure patterns on undrained shear strength and consolidation properties have been assessed using test specimens ranging from 76 to 254 mm diameter and correlations between observed laboratory anisotropic behavior and behavior in excavations have been suggested.

2017 ◽  
Vol 62 (2) ◽  
pp. 367-384
Author(s):  
Sebastian Olesiak

Abstract Soil strength parameters needed for the calculation of bearing capacity and stability are increasingly determined from field testing. This paper presents a method to determine the undrained shear strength cuWST of the soil, based on the Weight Sounding Test (WST). The innovative solution which allows for a significant reduction of equipment needed for geotechnical field investigation is presented. The proposed method is based on an additional measurement of the torque during testing. It then becomes possible to estimate the undrained shear strength, cuWST of the soil, using the correlation given in this paper. The research results presented in this paper were carried out on selected cohesive soils, Miocene clays from the Carpathian Foredeep.


2018 ◽  
Vol 8 (8) ◽  
pp. 1395 ◽  
Author(s):  
Zbigniew Lechowicz ◽  
Masaharu Fukue ◽  
Simon Rabarijoely ◽  
Maria Sulewska

The undrained shear strength of organic soils can be evaluated based on measurements obtained from the dilatometer test using single- and multi-factor empirical correlations presented in the literature. However, the empirical methods may sometimes show relatively high values of maximum relative error. Therefore, a method for evaluating the undrained shear strength of organic soils using artificial neural networks based on data obtained from a dilatometer test and organic soil properties is presented in this study. The presented neural network, with an architecture of 5-4-1, predicts the normalized undrained shear strength based on five independent variables: the normalized net value of a corrected first pressure reading (po − uo)/σ′v, the normalized net value of a corrected second pressure reading (p1 − uo)/σ′v, the organic content Iom, the void ratio e, and the stress history indictor (oc or nc). The neural model presented in this study provided a more reliable prediction of the undrained shear strength in comparison to the empirical methods, with a maximum relative error of ±10%.


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