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IJSTR >> Volume 3- Issue 5, May 2014 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Modelling The Mechanical, Thermo-Physical, And Filtration Properties Of Dried Clay-Sand Mixtures For Water Storage Vessel Using Regression Method

[Full Text]



Raimi Oluwole Abiodun, Oluwatoyin Edwin



KEY WORDS: Mathematical models, Dried clay-sand mixtures, Mechanical properties, Thermo-physical properties, Filtration properties, Water storage vessel, Regression method



ABSTRACT: The study estimated on some mathematical models to predict accurately the relationship between the compressive force, crushing strength, thermal conductivity, filtration rate and permeability of dried clay-sand mixtures within experimental limit. The dependent parameter is the investigated properties of the dried clay-sand mixtures while the sample of dried clay-sand mixtures is the independent parameters. The experimental data were modelled using simple linear regression method. The data were analysed with the aid of statistical software called Statistical Package for Social Science (SPSS), version 17. The findings show that the coefficient of determination (R2) of the formulated models is significantly high with respect to the adjusted R2 at 95% confidence interval. The F-value and t-statistic shows that the regression models and the investigated parameters are significant to the model. The estimated result from the models and the investigated experimental result were highly significant and explained a very high percentage effect of what was taking place in the samples of dried clay-sand mixtures. This result showed that the investigated properties parameters can be predicted accurately using the established relationship with the samples of dried clay-sand mixtures. It is also observed that the estimated result from the models having clay-sand mixture specimen with 0% weight of sand has the highest compressive force, crushing strength, least thermal conductivity, least filtration rate and least permeability, which will be the ideal specimen for making water storage vessels.



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