Characterization by X-ray computed tomography of the bedding planes influenceon excavation damaged zone of a plastic clay

2011 ◽  
pp. 245-248 ◽  
Author(s):  
S You ◽  
H Ji
Keyword(s):  
Computed Tomography ◽  
Plastic Clay ◽  
X Ray ◽  
Excavation Damaged Zone ◽  
Bedding Planes ◽  
Damaged Zone ◽  
X Ray Computed

scholarly journals X-Ray Computed Tomography Analysis of Sajau Coal, Berau Basin, Indonesia: 3D Imaging of Cleat and Microcleat Characteristics

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ahmad Helman Hamdani
Keyword(s):  
Computed Tomography ◽  
Coalbed Methane ◽  
High Density ◽  
Coal Seams ◽  
3D Images ◽  
X Ray ◽  
Bedding Planes ◽  
X Ray Computed ◽  
Basin Area ◽  
Tomography Analysis

The Pliocene Sajau coals of the Berau Basin area have a moderately to highly developed cleat system. Mostly the cleat fractures are well developed in both bright and dull bands, and these cleats are generally inclined or perpendicular to the bedding planes of the seam. The presence of cleat networks/fractures in coal seam is the important point in coalbed methane prospect. The 3D X-ray computed tomography (CT) technique was performed to identify cleats characteristics in the Sajau coal seams, such as the direction of coal cleats, geometry of cleat, and cleats mineralization. By CT scan imaging technique two different types of natural fractures observed in Sajau coals have been identified, that is, face cleats and butt cleats. This technique also identified the direction of face cleats and butt cleats as shown in the resulting 3D images. Based on the images, face cleats show a NNE-SSW direction while butt cleats have a NW-SE direction. The crosscutting relationship indicated that NNE-SSW cleats were formed earlier than NW-SE cleats. The procedure also identified the types of minerals that filled the cleats apertures. Based on their density, the minerals are categorized as follows: very high density minerals (pyrite), high density minerals (anastase), and low density minerals (kaolinite, calcite) were identified filling the cleats aperture.

X-Ray Computed Tomography of Ultralightweight Metals

1999 ◽  
Vol 11 (1) ◽  
pp. 199-211
Author(s):  
J. M. Winter ◽  
R. E. Green ◽  
A. M. Waters ◽  
W. H. Green
Keyword(s):  
Computed Tomography ◽  
X Ray ◽  
X Ray Computed

scholarly journals Nano- scale X-ray Computed Tomography: Morphological Analysis of Fuel Cell Electrodes

2013 ◽  
Vol 19 (S2) ◽  
pp. 630-631
Author(s):  
P. Mandal ◽  
W.K. Epting ◽  
S. Litster
Keyword(s):  
Computed Tomography ◽  
Fuel Cell ◽  
Morphological Analysis ◽  
Fuel Cell Electrodes ◽  
X Ray ◽  
Nano Scale ◽  
X Ray Computed

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

scholarly journals Ant Colony-Based Hyperparameter Optimisation in Total Variation Reconstruction in X-ray Computed Tomography

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 591
Author(s):  
Manasavee Lohvithee ◽  
Wenjuan Sun ◽  
Stephane Chretien ◽  
Manuchehr Soleimani
Keyword(s):  
Computed Tomography ◽  
Total Variation ◽  
Cross Validation ◽  
Ant Colony ◽  
Reference Image ◽  
X Ray ◽  
X Ray Computed ◽  
Hyperparameter Selection ◽  
The Cross ◽  
Optimal Set

In this paper, a computer-aided training method for hyperparameter selection of limited data X-ray computed tomography (XCT) reconstruction was proposed. The proposed method employed the ant colony optimisation (ACO) approach to assist in hyperparameter selection for the adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm, which is a total-variation (TV) based regularisation algorithm. During the implementation, there was a colony of artificial ants that swarm through the AwPCSD algorithm. Each ant chose a set of hyperparameters required for its iterative CT reconstruction and the correlation coefficient (CC) score was given for reconstructed images compared to the reference image. A colony of ants in one generation left a pheromone through its chosen path representing a choice of hyperparameters. Higher score means stronger pheromones/probabilities to attract more ants in the next generations. At the end of the implementation, the hyperparameter configuration with the highest score was chosen as an optimal set of hyperparameters. In the experimental results section, the reconstruction using hyperparameters from the proposed method was compared with results from three other cases: the conjugate gradient least square (CGLS), the AwPCSD algorithm using the set of arbitrary hyperparameters and the cross-validation method.The experiments showed that the results from the proposed method were superior to those of the CGLS algorithm and the AwPCSD algorithm using the set of arbitrary hyperparameters. Although the results of the ACO algorithm were slightly inferior to those of the cross-validation method as measured by the quantitative metrics, the ACO algorithm was over 10 times faster than cross—Validation. The optimal set of hyperparameters from the proposed method was also robust against an increase of noise in the data and can be applicable to different imaging samples with similar context. The ACO approach in the proposed method was able to identify optimal values of hyperparameters for a dataset and, as a result, produced a good quality reconstructed image from limited number of projection data. The proposed method in this work successfully solves a problem of hyperparameters selection, which is a major challenge in an implementation of TV based reconstruction algorithms.

scholarly journals Three‐dimensional X‐ray‐computed tomography of 3300‐ to 6000‐year‐old Citrullus seeds from Libya and Egypt compared to extant seeds throws doubts on species assignments

2021 ◽  
Author(s):  
Katherine A. Wolcott ◽  
Guillaume Chomicki ◽  
Yannick M. Staedler ◽  
Krystyna Wasylikowa ◽  
Mark Nesbitt ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
X Ray ◽  
X Ray Computed
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