A PROBABILISTIC ANALYSIS OF THE DISTRIBUTION OF COLLAPSING SOIL IN TUCSON USING KRIGING METHOD

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" A PROBABILISTIC ANALYSIS OF THE DISTRIBUTION OF COLLAPSING SOIL IN TUCSON USING KRIGING METHOD "
M. M. Ali

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1112460
Doc. No	:	TLpq303548078
Main Entry	:	M. M. Ali
Title & Author	:	A PROBABILISTIC ANALYSIS OF THE DISTRIBUTION OF COLLAPSING SOIL IN TUCSON USING KRIGING METHOD\ M. M. Ali
College	:	The University of Arizona
Date	:	1987
student score	:	1987
Degree	:	Ph.D.
Page No	:	271
Abstract	:	An analytical investigation was carried to determine the nature and extent of the variability of selected collapse criteria and collapse-related soil parameters both areally and with depth within the city of Tucson. Collapse-related soil parameters of about 1000 sample points from over 400 borehole locations throughout the Tucson basin were collected from several consulting geotechnical engineering offices of the city. Statistical analysis on seven data sets corresponding to six different depth increments below the surface showed high dispersion tendencies expressed by the value of coefficient of variation (cov). The value of cov was found to increase linearly with depth for most criteria and parameters. All the collapse criteria and collapse-related soil parameters were found to follow the Gamma distribution function except insitu dry density (usd\gamma\sb{d}usd) and porosity (usdn\sb0usd) which were found to follow the Weibull distribution function. A polynomial regression model developed for the collapse parameter usdC\sb{p}usd showed that it varies with depth almost linearly. A stepwise regression analysis revealed that the collapse parameter usdC\sb{p}usd is strongly correlated with usd\gamma\sb{d}usd and insitu moisture content, usdw\sb0usd. Factor analysis validates this finding by producing two strong factors usd\gamma\sb{d}usd and insitu degree of saturation, usds\sb0usd, which described almost 80% of the variation encountered in the data. The application of geostatistical concepts was found to be feasible in analyzing the collapse criteria and collapse-related soil parameters. Almost all criteria and parameters were strongly dependent spatially. A spherical variogram model was found to be appropriate for them. The method of Ordinary Kriging provided an unbiased estimation of a parameter at an unsampled location with known estimation variance. The method of Indicator Kriging was used to develop contour plots for the various data sets that showed the probability that the value of a certain parameter is above or below a critical level. These contour plots can be used to identify the areas within the City of Tucson that contain soils having a low- medium- or high-collapse potential. The ability to predict the occurrence of such soils with a known degree of certitude is invaluable to planners, developers and geotechnical engineers.
Subject	:	Applied sciences
	:	Civil engineering