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Prediction of Compression Index of the Soil of Al-Nasiriya City Using Simple Linear Regression Model

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The engineering design and selection of appropriate sites for engineering projects require many physical and engineering tests; some of these tests are very expensive and take a long time consuming… Click to show full abstract

The engineering design and selection of appropriate sites for engineering projects require many physical and engineering tests; some of these tests are very expensive and take a long time consuming to complete. Compression index (Cc) is used to predict the compressibility of soil and estimate how much settlement which is occurred due to loads of different engineering structures. In this study, soil investigations reports were used for the city of Al-Nasiriya which were carried out by the national construction laboratories. Physical properties results showed that Al-Nasiriya city soil has a low to high compressibility and it is classified as inorganic clays of medium to high plasticity. The simple linear regression analysis was applied for estimating compression index indirectly through using some properties of soil indices such as atterberg limits. The correlation coefficient of the linear regression model indicated the presence of reasonable relationships between the compression index and the parameters proposed in this paper. The obtained results showed that the best model is capable of predicting the amount of compression index and with higher accuracy is based on liquidity limits in regression analyses. There is also a reasonable agreement between measured and predicted compression index values in addition to presence a small difference between calculated values using statistical properties for atterberg limits. The empirical equations obtained from simple linear regression model can be reliably used in engineering designs for study area with high confidence.

Keywords: compression index; compression; engineering; linear regression

Journal Title: Geotechnical and Geological Engineering
Year Published: 2020

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