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The Scientific World Journal
Volume 2015 (2015), Article ID 414262, 6 pages
http://dx.doi.org/10.1155/2015/414262
Research Article

Evaluation of Multiple-Scale 3D Characterization for Coal Physical Structure with DCM Method and Synchrotron X-Ray CT

1Institute of Theoretical Physics and Department of Physics, Shanxi University, Taiyuan, Shanxi 030006, China
2CSIRO, Private Bag Box 33, Clayton, VIC 3169, Australia
3State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, Shanxi 030001, China
4College of Physics & Electronics Engineering, Shanxi University, Taiyuan, Shanxi 030006, China
5Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China

Received 24 June 2014; Accepted 14 July 2014

Academic Editor: Wenjun Jiang

Copyright © 2015 Haipeng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.