LAPSE:2023.6548
Published Article

LAPSE:2023.6548
Computed Tomography Observation and Image-Based Simulation of Fracture Propagation in Compressed Coal
February 24, 2023
Abstract
In this study, the fracture propagation characteristics and associated mechanisms of coal are investigated by using computed tomography (CT) observation and image-based simulation. The spatial distribution and the structural morphology of original fractures provide significant influences on the failure behavior of fractured coal. The fractures with small dip angles and large openings result in more-obvious fracture closure and stable propagation stages, while failure pattern is more sensitive to those with large dip angles. The coal tends to experience brittle failure, which transits from a splitting to mixed-splitting faulting mode because of the difference in original fracture distribution. The final failure fracture network originates mainly from the propagation of original fractures, driven by localized tensile stress. Fracture interaction and mineral influence tend to increase the complexity in the failure fracture network. Moreover, image-based numerical models are established on the basis of CT reconstruction, where the spatial distribution and the structural morphology of original fractures are properly considered. Numerical modeling reproduces similar stress−strain responses and failure fracture networks to that observed in the experiment. The predicted distribution of tensile stress shows a similar evolution trend to the failure fracture network, implying that the fracture propagation of coal is dominated by tensile failure. Shear cracks emerge mainly after the large fracture running through the coal sample has been formed.
In this study, the fracture propagation characteristics and associated mechanisms of coal are investigated by using computed tomography (CT) observation and image-based simulation. The spatial distribution and the structural morphology of original fractures provide significant influences on the failure behavior of fractured coal. The fractures with small dip angles and large openings result in more-obvious fracture closure and stable propagation stages, while failure pattern is more sensitive to those with large dip angles. The coal tends to experience brittle failure, which transits from a splitting to mixed-splitting faulting mode because of the difference in original fracture distribution. The final failure fracture network originates mainly from the propagation of original fractures, driven by localized tensile stress. Fracture interaction and mineral influence tend to increase the complexity in the failure fracture network. Moreover, image-based numerical models are established on the basis of CT reconstruction, where the spatial distribution and the structural morphology of original fractures are properly considered. Numerical modeling reproduces similar stress−strain responses and failure fracture networks to that observed in the experiment. The predicted distribution of tensile stress shows a similar evolution trend to the failure fracture network, implying that the fracture propagation of coal is dominated by tensile failure. Shear cracks emerge mainly after the large fracture running through the coal sample has been formed.
Record ID
Keywords
CT observation, failure pattern, fracture propagation, image-based model, tensile stress
Subject
Suggested Citation
Wang Z, Sun W, Shui Y, Liu P. Computed Tomography Observation and Image-Based Simulation of Fracture Propagation in Compressed Coal. (2023). LAPSE:2023.6548
Author Affiliations
Wang Z: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China; Coal Industry Engineering Research Center of Top-Coal Caving Mining, Beijing 100083, China [ORCID]
Sun W: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Shui Y: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Liu P: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Sun W: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Shui Y: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Liu P: School of Energy and Mining Engineering, China University of Mining and Technology, Beijing 100083, China
Journal Name
Energies
Volume
16
Issue
1
First Page
260
Year
2022
Publication Date
2022-12-26
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16010260, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.6548
This Record
External Link

https://doi.org/10.3390/en16010260
Publisher Version
Download
Meta
Record Statistics
Record Views
192
Version History
[v1] (Original Submission)
Feb 24, 2023
Verified by curator on
Feb 24, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.6548
Record Owner
Auto Uploader for LAPSE
Links to Related Works
