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A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla
Coal mining may lead to ground subsidence in a long term and is widely distributed, which can cause environmental damage and other disasters. Predicting the dynamic process of ground subsidence in real time is very important for offering theoretical or technical guidance to deal with the consequence...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626622/ https://www.ncbi.nlm.nih.gov/pubmed/36319670 http://dx.doi.org/10.1038/s41598-022-23303-9 |
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author | Zhang, Xingsheng Yan, Shaobin Tan, Haicheng Dong, Jinyu |
author_facet | Zhang, Xingsheng Yan, Shaobin Tan, Haicheng Dong, Jinyu |
author_sort | Zhang, Xingsheng |
collection | PubMed |
description | Coal mining may lead to ground subsidence in a long term and is widely distributed, which can cause environmental damage and other disasters. Predicting the dynamic process of ground subsidence in real time is very important for offering theoretical or technical guidance to deal with the consequences of mining. In this study, we developed a prediction method for dynamic ground subsidence using a time function model that considers two stages of surface subsidence and reflects the law of surface subsidence in goaf. We applied the model to the Barapukuria mine, and our simulation shows that the prediction results are in good agreement with the monitoring data. Our results suggest that the dynamic development of the ground subsidence basin may be an effective measure to assess the loss of ground and provide early warning of oncoming hazards. |
format | Online Article Text |
id | pubmed-9626622 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96266222022-11-03 A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla Zhang, Xingsheng Yan, Shaobin Tan, Haicheng Dong, Jinyu Sci Rep Article Coal mining may lead to ground subsidence in a long term and is widely distributed, which can cause environmental damage and other disasters. Predicting the dynamic process of ground subsidence in real time is very important for offering theoretical or technical guidance to deal with the consequences of mining. In this study, we developed a prediction method for dynamic ground subsidence using a time function model that considers two stages of surface subsidence and reflects the law of surface subsidence in goaf. We applied the model to the Barapukuria mine, and our simulation shows that the prediction results are in good agreement with the monitoring data. Our results suggest that the dynamic development of the ground subsidence basin may be an effective measure to assess the loss of ground and provide early warning of oncoming hazards. Nature Publishing Group UK 2022-11-01 /pmc/articles/PMC9626622/ /pubmed/36319670 http://dx.doi.org/10.1038/s41598-022-23303-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhang, Xingsheng Yan, Shaobin Tan, Haicheng Dong, Jinyu A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title | A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title_full | A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title_fullStr | A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title_full_unstemmed | A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title_short | A time function-based prediction model of mining subsidence: application to the Barapukuria coal mine, Bangla |
title_sort | time function-based prediction model of mining subsidence: application to the barapukuria coal mine, bangla |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626622/ https://www.ncbi.nlm.nih.gov/pubmed/36319670 http://dx.doi.org/10.1038/s41598-022-23303-9 |
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