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Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation
According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry functio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9180210/ https://www.ncbi.nlm.nih.gov/pubmed/35682444 http://dx.doi.org/10.3390/ijerph19116862 |
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author | Yan, Weitao Chen, Junjie Tan, Yi He, Rong Yan, Shaoge |
author_facet | Yan, Weitao Chen, Junjie Tan, Yi He, Rong Yan, Shaoge |
author_sort | Yan, Weitao |
collection | PubMed |
description | According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry function to establish the profile prediction function of the surface damage, which results in a large difference between the prediction result and the actual situation. To solve this problem, this paper takes subsidence velocity as an example. Firstly, the spatial distribution functions of subsidence velocity on both sides were deduced theoretically. Through comparison, it is found that the change rate of the spatial distribution curve of the coal pillar side subsidence velocity is smoother than that of the goaf side and the subsidence velocity curves are skewed to the left. Secondly, based on the idea of lossless propagation of harmonic waves and idealizing the propagation environment, the spatial propagation relationship of surface subsidence velocity in the time domain is established. Then, the Box–Cox transform function is introduced to improve the normal distribution probability density function, and a new dynamic subsidence prediction model based on the Box–Cox transformation is obtained, which is suitable for the full mining stage. The model is tested by practical cases, the prediction accuracy is better than 7%, and the prediction results can meet the needs of engineering prediction accuracy (10%). The results of this research can enrich the existing subsidence prediction theory and provide theoretical and technical support for the prediction of dynamic surface damage caused by similar mining. |
format | Online Article Text |
id | pubmed-9180210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91802102022-06-10 Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation Yan, Weitao Chen, Junjie Tan, Yi He, Rong Yan, Shaoge Int J Environ Res Public Health Article According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry function to establish the profile prediction function of the surface damage, which results in a large difference between the prediction result and the actual situation. To solve this problem, this paper takes subsidence velocity as an example. Firstly, the spatial distribution functions of subsidence velocity on both sides were deduced theoretically. Through comparison, it is found that the change rate of the spatial distribution curve of the coal pillar side subsidence velocity is smoother than that of the goaf side and the subsidence velocity curves are skewed to the left. Secondly, based on the idea of lossless propagation of harmonic waves and idealizing the propagation environment, the spatial propagation relationship of surface subsidence velocity in the time domain is established. Then, the Box–Cox transform function is introduced to improve the normal distribution probability density function, and a new dynamic subsidence prediction model based on the Box–Cox transformation is obtained, which is suitable for the full mining stage. The model is tested by practical cases, the prediction accuracy is better than 7%, and the prediction results can meet the needs of engineering prediction accuracy (10%). The results of this research can enrich the existing subsidence prediction theory and provide theoretical and technical support for the prediction of dynamic surface damage caused by similar mining. MDPI 2022-06-03 /pmc/articles/PMC9180210/ /pubmed/35682444 http://dx.doi.org/10.3390/ijerph19116862 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yan, Weitao Chen, Junjie Tan, Yi He, Rong Yan, Shaoge Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title | Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title_full | Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title_fullStr | Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title_full_unstemmed | Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title_short | Surface Dynamic Damage Prediction Model of Horizontal Coal Seam Based on the Idea of Wave Lossless Propagation |
title_sort | surface dynamic damage prediction model of horizontal coal seam based on the idea of wave lossless propagation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9180210/ https://www.ncbi.nlm.nih.gov/pubmed/35682444 http://dx.doi.org/10.3390/ijerph19116862 |
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