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Intelligent Engineering Systems through Artificial Neural Networks, Volume 20

Cihan H. Dagli
Cihan H. Dagli
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The heterogeneous nature of porous media presents serious challenges in accurately predicting solute transport through earth materials. Spatial analysis techniques such as geostatistics provide a quantitative tool to evaluate soil pore heterogeneity at a variety of scales. The objective of this study was to determine the macropore-scale spatial variograms of CT-measured pore-water velocity and dispersivity in intact soil cores. CT-measured breakthrough curve experiments were conducted through eight intact soil cores removed from the surface horizon of a Sarpy loamy sand (Typic Udispamment). Breakthrough experiments with KI were conducted using a medical x-ray CT scanner. Based on the breakthrough curve for each pixel, solute pore-water velocity and dispersivity distributions were determined. The exponential variogram model provided the best fit for the variograms of CT-measured pore-water velocity and dispersivity for the cores. The range of autocorrelation for pore-water velocity was found to be 1.4 to 10 mm and dispersivity to be 0.85 to 3.5 mm. The dispersivity autocorrelation range was found to be approximately 65% of the pore-water velocity range. This study illustrates the ability to utilize spatial variograms for quantifying the autocorrelation of CT-measured transport properties, information which may be useful in transport models.

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