Study on seepage and deformation characteristics of coal microstructure by 3D reconstruction of CT images at high temperatures
International Journal of Mining Science and Technology, ISSN: 2095-2686, Vol: 31, Issue: 2, Page: 175-185
2021
- 125Citations
- 24Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations125
- Citation Indexes125
- 125
- CrossRef1
- Captures24
- Readers24
- 24
Article Description
To study the seepage and deformation characteristics of coal at high temperatures, coal samples from six different regions were selected and subjected to computed tomography (CT) scanning studies. In conjunction with ANSYS software, 3D reconstruction of CT images was used for the establishment of fluid-solid conjugate heat transfer model and coal thermal deformation model based on the microstructures of coal. In addition, the structure of coal was studied in 2D and 3D perspectives, followed by the analysis of seepage and deformation characteristics of coal at high temperatures. The results of this study indicated that porosity positively correlated with the fractal dimension, and the connectivity and seepage performances were roughly identical from 2D and 3D perspectives. As the porosity increased, the fractal dimension of coal samples became larger and the pore-fracture structures became more complex. As a result, the permeability of coal samples decreased. In the meantime, fluid was fully heated, generating high-temperature water at outlet. However, when the porosity was low, the outlet temperature was very high. The average deformation of coal skeleton with different pore-fracture structures at high temperatures showed a trend of initial increase and subsequent decrease with the increase of porosity and fractal dimension. The maximum deformation of coal skeleton positively correlated with connectivity but negatively correlated with the fractal dimension.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2095268620309319; http://dx.doi.org/10.1016/j.ijmst.2020.11.003; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85099501786&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2095268620309319; https://api.elsevier.com/content/article/PII:S2095268620309319?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S2095268620309319?httpAccept=text/plain; https://dul.usage.elsevier.com/doi/; http://sciencechina.cn/gw.jsp?action=cited_outline.jsp&type=1&id=6971405&internal_id=6971405&from=elsevier; https://dx.doi.org/10.1016/j.ijmst.2020.11.003
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know