Abstract
The paper presents an application of milli- and micro-XCT to mesostructure characterization of CGPs and failure patterns analysis using dynamic impact simulations. In this study, XCT scanning experiments are firstly conducted on CGPs, followed by a series of image analyses with qualitative results. Then, the 3D mesomorphological parameters and internal composition of individual particles are quantitatively characterized. Finally, dynamic impact loading in y-axis direction is modelled to investigate the 3D mesostructure and different impact velocity effects on failure patterns of individual particles. The studies show that the mesomorphological parameters present different distribution characteristics in individual CGPs. The approximate location of gangue phase is the key parameter that should be taken into account to study failure patterns as well as fracture mechanism of the heterogeneous rock materials. The XCT image-based numerical model proved to be an effective tool that gives insights into the mesodeformation mechanisms of heterogeneous coal rock (HCR) undergoing dynamic impact failure behavior.
Highlights
Multiscale experiments and modelling of multiphase mineral materials, such as coal, gangue, and various composite materials, are of critical importance for the detailed analysis of the mesostructure and failure patterns of coal ores
In order to illustrate internal damage of the individual CGPs, the original CT image of the selected coal particle shown in Figure 10(a) is typically segmented and reconstructed (Figure 10(b)) from the packed particle bed
Due to the impact loading process always occurs within a few microseconds, the continuous investigations of the entire fracture process with the current X-ray computed tomography (XCT) techniques is not workable for technical reasons yet
Summary
Multiscale experiments and modelling of multiphase mineral materials, such as coal, gangue, and various composite materials, are of critical importance for the detailed analysis of the mesostructure and failure patterns of coal ores. E 3D image data obtained from Philips milli-CT equipment contain 901 projections of 512 × 512 pixels with a voxel resolution of 470 μm Another micro-XCT-400 machine with much higher resolution (Figure 1(c)) is used to scan the fine particles with size 1∼5 mm [26]. Identifying internal composition and internal damage in particles by XCT can be challenging, due to insufficient contrast boundaries or small characteristics near the resolution limit In this regard, a feature-based classification method, which takes image intensities and a series of image features into account to identify particle boundaries [29], is proposed to extract useful features to realize better segmentation effect [30]. Different mineral phases and background regions are selected as a training set to segment different mineral phases from the background (air). e improved segmentation results for the small-scale image and artificial CT image shown in Figure 5 are satisfactory for subsequent segmentation process and for detailed quantitative analysis
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