Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/6136
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dc.contributor.authorSandamali, D.M.T.U.-
dc.contributor.authorD.M.T.U., K.H.S.M.-
dc.contributor.authorRanathunga, A. S.-
dc.date.accessioned2022-09-01T08:04:41Z-
dc.date.available2022-09-01T08:04:41Z-
dc.date.issued2022-
dc.identifier.isbn978-624-6150-05-1-
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/6136-
dc.description.abstractThe use of Calcium Carbide Residue (CCR) for soil stabilization results in changes of the properties of natural soil. In terms of compaction properties, the addition of CCR reduces the maximum dry density (MDD) of clayey soils while increasing the optimum moisture content (OMC). This paper describes a multivariate linear regression model and a multivariate polynomial regression model which can predict the MDD, and OMC of clayey soils stabilized with CCR, respectively. In both models, the compaction properties of the natural soil and the CCR mix proportion are used as independent variables and the developed models can be used to study any clayey soil which can be classified as CH or CL according to the unified soil classification system (USCS). From the statistical analysis, it is found that the models are capable of accurately predicting the compaction properties (i.e., MDD and OMC) of clayey soils stabilized with different CCR dosages with a prediction accuracy of ±5%. Therefore, the developed correlations can be effectively used as an indirect approach to estimate the improved compaction properties of soil in the process of soft ground improvement using CCR.en_US
dc.language.isoenen_US
dc.publisherUniversity of Jaffnaen_US
dc.subjectCalcium Carbide Residueen_US
dc.subjectCompactionen_US
dc.subjectClayey soilsen_US
dc.subjectRegression analysisen_US
dc.subjectMaximum dry densityen_US
dc.subjectOptimum moisture contenten_US
dc.titlePrediction of Compaction Properties of Clayey Soils Stabilized With Calcium Carbide Residueen_US
dc.typeArticleen_US
Appears in Collections:ICE 2022



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