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Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D
To investigate the mechanical properties of fractured dolomite, this study analyzed the fracture characteristics (dip angle, length, position, quantity) using the Pearson coefficient and MIC coefficient. Subsequently, the data pertaining to fracture characteristics is preprocessed using a third-degr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435573/ https://www.ncbi.nlm.nih.gov/pubmed/37591985 http://dx.doi.org/10.1038/s41598-023-40254-x |
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author | Chen, Yi Rao, Junying Zhao, Changjie Xue, Yanghao Liu, Chang Yin, Quan |
author_facet | Chen, Yi Rao, Junying Zhao, Changjie Xue, Yanghao Liu, Chang Yin, Quan |
author_sort | Chen, Yi |
collection | PubMed |
description | To investigate the mechanical properties of fractured dolomite, this study analyzed the fracture characteristics (dip angle, length, position, quantity) using the Pearson coefficient and MIC coefficient. Subsequently, the data pertaining to fracture characteristics is preprocessed using a third-degree polynomial, and a three-classification strategy is implemented to improve the logistic regression algorithm to establish the strength prediction model of fractured dolomite. Furthermore, the significance order of the impact of fracture characteristics on rock strength was determined using the numerical simulation software PFC3D, and the dip angle effect was explained from the perspective of internal fracture propagation within the rock. The results show that: (1) When the regularization coefficient λ = 10,000, the algorithm has the highest prediction accuracy and the strongest model generalization ability. (2) The numerical simulation analysis software PFC3D can accurately invert rock failure process and characteristics, and the order of influence of fracture characteristics on rock strength is dip angle > length > position. |
format | Online Article Text |
id | pubmed-10435573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104355732023-08-19 Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D Chen, Yi Rao, Junying Zhao, Changjie Xue, Yanghao Liu, Chang Yin, Quan Sci Rep Article To investigate the mechanical properties of fractured dolomite, this study analyzed the fracture characteristics (dip angle, length, position, quantity) using the Pearson coefficient and MIC coefficient. Subsequently, the data pertaining to fracture characteristics is preprocessed using a third-degree polynomial, and a three-classification strategy is implemented to improve the logistic regression algorithm to establish the strength prediction model of fractured dolomite. Furthermore, the significance order of the impact of fracture characteristics on rock strength was determined using the numerical simulation software PFC3D, and the dip angle effect was explained from the perspective of internal fracture propagation within the rock. The results show that: (1) When the regularization coefficient λ = 10,000, the algorithm has the highest prediction accuracy and the strongest model generalization ability. (2) The numerical simulation analysis software PFC3D can accurately invert rock failure process and characteristics, and the order of influence of fracture characteristics on rock strength is dip angle > length > position. Nature Publishing Group UK 2023-08-17 /pmc/articles/PMC10435573/ /pubmed/37591985 http://dx.doi.org/10.1038/s41598-023-40254-x Text en © The Author(s) 2023 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 Chen, Yi Rao, Junying Zhao, Changjie Xue, Yanghao Liu, Chang Yin, Quan Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title | Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title_full | Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title_fullStr | Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title_full_unstemmed | Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title_short | Strength prediction model of fractured dolomite and analysis of mechanical properties based on PFC3D |
title_sort | strength prediction model of fractured dolomite and analysis of mechanical properties based on pfc3d |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435573/ https://www.ncbi.nlm.nih.gov/pubmed/37591985 http://dx.doi.org/10.1038/s41598-023-40254-x |
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