Document Type : Original Article
Authors
1
Geotechnical Lab, Structural Department, Faculty of Engineering, Tanta University, Tanta, Egypt
2
Geology Department, Faculty of Science, Ain Shams University, Cairo, Egypt
Abstract
Establishment of any engineering structure on a compressible clay leads to settlement and/or failure through this clay. The amount of settlement is related mainly to the compressibility parameters while the failure to the undrained strength. The measuring of compressibility parameters and undrained strength are expensive, cumbersome, and time-consuming, therefore several attempts have been made in the past to predict these geotechnical parameters by using simple, cheap, and time-saving index properties of the soil as Atterberg limits, bulk density, moisture content, and initial void ratio as well as pocket penetrometer and laboratory torvane. In this study, the performance of applying empirical equations for the estimation of these critical geotechnical parameters was assessed by using the database consisting of 551 undisturbed clay soil samples. The regression analysis results depict statistically moderately to strong correlations of compression index and recompression index with bulk density, Atterberg limits, initial void ratio, and effective overburden pressure. The precompression stress, overconsolidation ratio, and undrained shear strength parameters have no remarkable correlations with the index properties except with the effective overburden pressure whereas they have moderately to strong correlations. The compressibility and strength parameters are depending on the same factors as in-situ effective stress, stress during geological history, diagenesis and cementation process, mineralogy, microstructure, and texture of clay, therefore there are meaningful relationships between these geotechnical parameters. This study suggested that, the developed empirical equations which derived from various linear and multi-variables regression models are reliable and capable to predict the geotechnical design parameters with high prediction performance.
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