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Research on construction deformation prediction and disaster warning of karst slope based on mutation theory
In the study of deformation prediction and disaster warning during karst slope construction, the influencing factors and deformation law should be comprehensively considered. The layout of the deformation monitoring points of karst slope is affected by the thickness of karst overburden soil, dissolu...
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/PMC9452683/ https://www.ncbi.nlm.nih.gov/pubmed/36071177 http://dx.doi.org/10.1038/s41598-022-19380-5 |
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author | Qi, Yanli Tian, Gang Bai, Mingzhou Song, Linlin |
author_facet | Qi, Yanli Tian, Gang Bai, Mingzhou Song, Linlin |
author_sort | Qi, Yanli |
collection | PubMed |
description | In the study of deformation prediction and disaster warning during karst slope construction, the influencing factors and deformation law should be comprehensively considered. The layout of the deformation monitoring points of karst slope is affected by the thickness of karst overburden soil, dissolution and fragmentation degree, karst development degree, slope cracking degree, fault or weak interlayer and other factors. In this paper, the author aimed at the problem of construction deformation prediction and disaster warning of karst slope, proposed an improved model of cusp mutation by applying and optimizing the cusp mutation model, analysed the deformation trend and sudden change type of the slope, and obtained the critical control early warning value of slope deformation. Therefore, it is feasible to analyse the deformation and mutation characteristics of karstified slope by using a virtual reality-mutation model. In addition, based on the empirical formula of the slope sliding limit deformation rate and grey prediction model, the critical control warning value of slope deformation is obtained, which provides a basis to quantify the deformation index of risk evaluation. This method provides a new idea to predict karst slope construction deformation and catastrophic deformation warning and has a reference value for similar engineering examples. |
format | Online Article Text |
id | pubmed-9452683 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94526832022-09-09 Research on construction deformation prediction and disaster warning of karst slope based on mutation theory Qi, Yanli Tian, Gang Bai, Mingzhou Song, Linlin Sci Rep Article In the study of deformation prediction and disaster warning during karst slope construction, the influencing factors and deformation law should be comprehensively considered. The layout of the deformation monitoring points of karst slope is affected by the thickness of karst overburden soil, dissolution and fragmentation degree, karst development degree, slope cracking degree, fault or weak interlayer and other factors. In this paper, the author aimed at the problem of construction deformation prediction and disaster warning of karst slope, proposed an improved model of cusp mutation by applying and optimizing the cusp mutation model, analysed the deformation trend and sudden change type of the slope, and obtained the critical control early warning value of slope deformation. Therefore, it is feasible to analyse the deformation and mutation characteristics of karstified slope by using a virtual reality-mutation model. In addition, based on the empirical formula of the slope sliding limit deformation rate and grey prediction model, the critical control warning value of slope deformation is obtained, which provides a basis to quantify the deformation index of risk evaluation. This method provides a new idea to predict karst slope construction deformation and catastrophic deformation warning and has a reference value for similar engineering examples. Nature Publishing Group UK 2022-09-07 /pmc/articles/PMC9452683/ /pubmed/36071177 http://dx.doi.org/10.1038/s41598-022-19380-5 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 Qi, Yanli Tian, Gang Bai, Mingzhou Song, Linlin Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title | Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title_full | Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title_fullStr | Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title_full_unstemmed | Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title_short | Research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
title_sort | research on construction deformation prediction and disaster warning of karst slope based on mutation theory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452683/ https://www.ncbi.nlm.nih.gov/pubmed/36071177 http://dx.doi.org/10.1038/s41598-022-19380-5 |
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