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PREDICTION OF THE BREAKING STRESS OF CLAYEY SOILS FROM TCHI DEPRESSION TO BENIN.
Publication year - 2020
Publication title -
international journal of engineering, sciences and research technology
Language(s) - English
Resource type - Journals
ISSN - 2277-9655
DOI - 10.29121/ijesrt.v9.i9.2020.14
Subject(s) - consolidation (business) , breakage , geotechnical engineering , shrinkage , soil water , oedometer test , plasticity , stress (linguistics) , swelling , environmental science , materials science , geology , soil science , composite material , linguistics , philosophy , accounting , business
The phenomena of shrinkage and swelling of clay soils depending on the water content are manifested by disorders affecting mainly individual houses, often not very rigid and superficially founded. The superficial foundations of infrastructures built on swelling soils are subjected to several stresses due to shrinkage and swelling phenomena. These stresses are the cause of damage to the frames in the form of cracks, or even lead to the partial or total breakage of the structure when it is built without special precautions. In order to control these induced stresses and to safeguard these infrastructures, it is necessary to control the breaking stress so that the dimensioned foundations do not cause the structure to break. The objective of this study is to develop a model to estimate the breaking stress thanks to the physical parameters of these soils. To achieve this, we performed several physical and mechanical tests on swelling soil samples taken from the study area, the results of which we used to use the established non-linear least squares method of swelling pressure prediction models. The models were based on test results from 24 soil samples. The tests were carried out in accordance with the French NF standards. This study has shown that the shear strength of a soil is a function of several physical parameters, mainly: pre-consolidation stress and plasticity index. We obtained the model qu=(2.9-1.181.IP). σ'p allowing us to predict the shear strength for the study area. This model is obtained with a regression coefficient precision r2 = 98.50%.

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