Numerical modelling of the stress strain behaviour of Kuttanad clay.
DOI:
https://doi.org/10.7770/safer-V12N1-art2771Abstract
Soil has been used as a construction material since antiquity with both success and failure. As the earth material is widely available and relatively economical, it has been found very useful in the construction of foundations, subgrades, embankments and as backfill. The collapsibility of soil is mainly due to the decrease of shear strength and macro-deformation with the increase of moisture content. This can result in some serious problems, such as the differential settlement of the foundation, landslides, and slope instability, resulting in a series of damages of infrastructures and loss of human lives to some degree. Fine-grained soils are the most complicated engineering material. These clays are characterized by high compressibility, low shear strength and high percentage of organic matter, which are unfavourable from the geotechnical point of view.It is of great importance in civil engineering to make realistic predictions of the behaviour of soil under various conditions. Studying the effect of moisture content on the shear strength of cohesive soil during different confining pressure helps to find a relationship between them. Triaxial tests under unconsolidated undrained conditions are carried outat different moisture contents, each at four different confining pressures (50, 100, 150, and 200 kPa). The relation of stress and strain of soils is analysedusing thehyperbolicmathematicalmodel which can provide a brief idea about how soil will behave under different conditions.Mathematical equations were determined based on the hyperbolic mathematical modelto predict the stress-strain behaviour of Kuttanad soil.Comparison of measured and predicted stress –strain curves for an additional group of soil sample with 37.22 % moisture contentshows that the proposed moisture content-dependent hyperbolic model provides good prediction of stress-strain behaviour of cohesive Kuttanad soil. The accuracy of the developed model is tested by employing Coefficient of determination (R2).
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