Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning
Understanding the in-situ stress distribution is crucial for coal mine production. In mining area 105 of Yuandian No. 1 Coal Mine, in-situ stress measurements were carried out using the stress relief method. Based on the collected data, the in-situ stress field was inverted using a Transformer archi...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2025.2545374 |
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| _version_ | 1849227310839889920 |
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| author | Rongqin Deng Yuan Zhang Dong Wu Jiakun Lv Yanan Jing Zheng Zhen Peng Shi |
| author_facet | Rongqin Deng Yuan Zhang Dong Wu Jiakun Lv Yanan Jing Zheng Zhen Peng Shi |
| author_sort | Rongqin Deng |
| collection | DOAJ |
| description | Understanding the in-situ stress distribution is crucial for coal mine production. In mining area 105 of Yuandian No. 1 Coal Mine, in-situ stress measurements were carried out using the stress relief method. Based on the collected data, the in-situ stress field was inverted using a Transformer architecture. The inversion results indicate that the Transformer achieves higher accuracy than the PSO-SVR method, demonstrating its suitability for in-situ stress inversion in near-fault mining areas. The distribution and characteristics of in-situ stress are jointly influenced by the Wugouyangliu-1 fault and burial depth; however, at greater depths, burial depth becomes the primary controlling factor. A significant stress concentration is observed near the fault zone, with stress values increasing by approximately 60%. Moreover, the axes of mining roadways are almost perpendicular to the maximum horizontal principal stress, which adversely affects roadway stability. This work verifies the feasibility of Transformer for in-situ stress field inversion in the near-fault coal mining area. |
| format | Article |
| id | doaj-art-9d09cc5797ff465fac87ba2b6294abef |
| institution | Kabale University |
| issn | 1947-5705 1947-5713 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj-art-9d09cc5797ff465fac87ba2b6294abef2025-08-23T14:48:18ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132025-12-0116110.1080/19475705.2025.2545374Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learningRongqin Deng0Yuan Zhang1Dong Wu2Jiakun Lv3Yanan Jing4Zheng Zhen5Peng Shi6School of Mines, China University of Mining and Technology, Xuzhou, ChinaSchool of Mines, China University of Mining and Technology, Xuzhou, ChinaSchool of Mines, China University of Mining and Technology, Xuzhou, ChinaSchool of Naval Architecture and Civil Engineering, Jiangsu University of Science and Technology, Zhangjiagang, Jiangsu, ChinaSchool of Mines, China University of Mining and Technology, Xuzhou, ChinaSchool of Mines, China University of Mining and Technology, Xuzhou, ChinaSchool of Mines, China University of Mining and Technology, Xuzhou, ChinaUnderstanding the in-situ stress distribution is crucial for coal mine production. In mining area 105 of Yuandian No. 1 Coal Mine, in-situ stress measurements were carried out using the stress relief method. Based on the collected data, the in-situ stress field was inverted using a Transformer architecture. The inversion results indicate that the Transformer achieves higher accuracy than the PSO-SVR method, demonstrating its suitability for in-situ stress inversion in near-fault mining areas. The distribution and characteristics of in-situ stress are jointly influenced by the Wugouyangliu-1 fault and burial depth; however, at greater depths, burial depth becomes the primary controlling factor. A significant stress concentration is observed near the fault zone, with stress values increasing by approximately 60%. Moreover, the axes of mining roadways are almost perpendicular to the maximum horizontal principal stress, which adversely affects roadway stability. This work verifies the feasibility of Transformer for in-situ stress field inversion in the near-fault coal mining area.https://www.tandfonline.com/doi/10.1080/19475705.2025.2545374In-situ stressinversion of in-situ stress fieldfaultdeep learningartificial intelligence |
| spellingShingle | Rongqin Deng Yuan Zhang Dong Wu Jiakun Lv Yanan Jing Zheng Zhen Peng Shi Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning Geomatics, Natural Hazards & Risk In-situ stress inversion of in-situ stress field fault deep learning artificial intelligence |
| title | Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning |
| title_full | Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning |
| title_fullStr | Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning |
| title_full_unstemmed | Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning |
| title_short | Inversion of In-situ stress field in near-fault coal mining area by coupling numerical simulation with deep learning |
| title_sort | inversion of in situ stress field in near fault coal mining area by coupling numerical simulation with deep learning |
| topic | In-situ stress inversion of in-situ stress field fault deep learning artificial intelligence |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2025.2545374 |
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