Stochastic reconstruction of snow microstructure from x-ray microtomography images

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Author
Yuan, Hongyan
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URI
http://hdl.handle.net/11122/5854
Abstract
The three-dimensional (3D) high-resolution digitized snow microstructure (pixel size 6 micron) was obtained by X-ray microtomography. The experimental result was verified by measuring the density of the snow sample. Statistical characteristics (porosity, local porosity, two-point correlation function) were extracted from cross-sectional images. The one-level-cut Gaussian random field model was used to stochastically reconstruct snow microstructure from X-ray microtomography images. Efficient computer programs were developed in MATLAB for the whole stochastic reconstruction procedure, including the numerical inversion of the correlation function and the generation of 3D large-scale Gaussian random fields by 3D inverse fast Fourier transform. The quality of the reconstruction was assessed by comparing the two-point correlation function and cross-sectional images.
Description
Thesis (M.S.) University of Alaska Fairbanks, 2007
Table of Contents
1. Introduction -- 2. Snow images by X-ray microtomography -- 2.1. Introduction of computed tomography -- 2.2. Acquisition and reconstruction -- 2.3. Binary images and 3D visualization -- 2.4. Statistical characteristics of the snow sample -- 3. Stochastic reconstruction of porous materials -- 3.1. Weak sense stationary gaussian random fields -- 3.2. The power spectral density function -- 3.3. The one-level-cut gaussian random field model -- 3.4. Generation of gaussian random fields -- 3.5. Stochastic reconstruction procedure -- 4. Reconstruction results -- 5. Conclusions -- References -- Appendices.
Date
2007-08
Type
Thesis
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