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Intelligent Engineering Systems through Artificial Neural Networks, Volume 20

Cihan H. Dagli
Cihan H. Dagli
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Accurate predictions of contaminant transport in porous media are vital to assist in minimizing impairment of water resources. Fractal analysis of transport parameters may assist in quantifying soil heterogeneity at a variety of scales which will help in identifying possible water quality impairments and remedial procedures. The objective of this study was to evaluate whether computed tomography (CT)-measured solute transport parameters are fractal, and if so, determine the fractal dimension and lacunarity of pore-water velocity and dispersivity parameters. 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. CT-measured pore-water velocity and dispersivity were found to be fractal. Fractal dimensions of pore-water velocity ranged from 2.16 to 2.43 and for dispersivity from 2.38 to 2.66. Results indicated that both fractal dimension and lacunarity are required to discriminate spatial distributions of the solute transport parameters among samples. If fractal dimensions are the same for different fractal sets, lacunarity analysis may reveal different spatial patterns or fractal structures for such fractal sets.

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