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Data on analysis of temperature inversion during spontaneous combustion of coal
Data in this article presents the characteristic parameters of spontaneous combustion of coal with different ranks, including lignite, long flame coal, and anthracite. The coal samples were tested by the temperature programmed method. The gas concentration data produced at different temperature poin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698773/ https://www.ncbi.nlm.nih.gov/pubmed/31440550 http://dx.doi.org/10.1016/j.dib.2019.104304 |
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author | Guo, Jun Wen, Hu Liu, Yin Jin, Yongfei |
author_facet | Guo, Jun Wen, Hu Liu, Yin Jin, Yongfei |
author_sort | Guo, Jun |
collection | PubMed |
description | Data in this article presents the characteristic parameters of spontaneous combustion of coal with different ranks, including lignite, long flame coal, and anthracite. The coal samples were tested by the temperature programmed method. The gas concentration data produced at different temperature points during the heating process are obtained. Through monitoring the spontaneous combustion of coal in a coal mine, the field data in goaf are obtained. Through processing on the data from the experiment and field, three gas indices were obtained, which include CO/CO(2), Graham value and Alkane ratio. The data is made available for further use and for furthering the understanding of the key findings of the related research, such as the early warning for spontaneous combustion of coal. For more insight please see A method for evaluating the spontaneous combustion of coal by monitoring various gases (Guo et al., 2019). |
format | Online Article Text |
id | pubmed-6698773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-66987732019-08-22 Data on analysis of temperature inversion during spontaneous combustion of coal Guo, Jun Wen, Hu Liu, Yin Jin, Yongfei Data Brief Engineering Data in this article presents the characteristic parameters of spontaneous combustion of coal with different ranks, including lignite, long flame coal, and anthracite. The coal samples were tested by the temperature programmed method. The gas concentration data produced at different temperature points during the heating process are obtained. Through monitoring the spontaneous combustion of coal in a coal mine, the field data in goaf are obtained. Through processing on the data from the experiment and field, three gas indices were obtained, which include CO/CO(2), Graham value and Alkane ratio. The data is made available for further use and for furthering the understanding of the key findings of the related research, such as the early warning for spontaneous combustion of coal. For more insight please see A method for evaluating the spontaneous combustion of coal by monitoring various gases (Guo et al., 2019). Elsevier 2019-07-24 /pmc/articles/PMC6698773/ /pubmed/31440550 http://dx.doi.org/10.1016/j.dib.2019.104304 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Engineering Guo, Jun Wen, Hu Liu, Yin Jin, Yongfei Data on analysis of temperature inversion during spontaneous combustion of coal |
title | Data on analysis of temperature inversion during spontaneous combustion of coal |
title_full | Data on analysis of temperature inversion during spontaneous combustion of coal |
title_fullStr | Data on analysis of temperature inversion during spontaneous combustion of coal |
title_full_unstemmed | Data on analysis of temperature inversion during spontaneous combustion of coal |
title_short | Data on analysis of temperature inversion during spontaneous combustion of coal |
title_sort | data on analysis of temperature inversion during spontaneous combustion of coal |
topic | Engineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698773/ https://www.ncbi.nlm.nih.gov/pubmed/31440550 http://dx.doi.org/10.1016/j.dib.2019.104304 |
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