Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring

As tunnel excavation and resource extraction progressively extend into deeper underground environments, the frequency of large deformation incidents in soft surrounding rock tunnels is increasing worldwide. To accurately and efficiently predict the large deformation tendencies of such tunnels, this...

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Main Authors: Qiang Wang, Xuzhi Xie, Munan Sun, Ming Zhao, Yuepeng Sun
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/adce/8860238
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author Qiang Wang
Xuzhi Xie
Munan Sun
Ming Zhao
Yuepeng Sun
author_facet Qiang Wang
Xuzhi Xie
Munan Sun
Ming Zhao
Yuepeng Sun
author_sort Qiang Wang
collection DOAJ
description As tunnel excavation and resource extraction progressively extend into deeper underground environments, the frequency of large deformation incidents in soft surrounding rock tunnels is increasing worldwide. To accurately and efficiently predict the large deformation tendencies of such tunnels, this study establishes, validates, and applies a multi-index evaluation method based on microseismic (MS) source parameters in the context of plateau railway soft surrounding rock tunnels. A multi-index evaluation approach based on an attribute recognition model is proposed, which comprehensively considers four key MS event parameters: the number of events (N), moment magnitude (mW), seismic energy (E), and the tunnel’s convergence deformation value. By analyzing various practical engineering cases, the weight of each parameter is assessed using a fuzzy comprehensive evaluation method. The identification model for large deformation tendencies in soft surrounding rock tunnels is constructed through weighted evaluation and the attribute measurement function of each index. The accuracy and applicability of the proposed multi-index evaluation method are validated through the analysis of large deformation instances in soft surrounding rock tunnels from field engineering. The results demonstrate that the prediction of large deformation tendencies based on MS monitoring closely aligns with the actual occurrences of large deformations in soft surrounding rock tunnels. The findings provide a foundation for assessing significant deformation tendencies in tunnels subjected to high-ground stress in weak surrounding rocks, with important implications for forecasting large deformation risks in such tunnels.
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spelling doaj-art-755b977a3c1b4de4a72bfc030ab88d1a2025-08-20T02:24:58ZengWileyAdvances in Civil Engineering1687-80942025-01-01202510.1155/adce/8860238Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation MonitoringQiang Wang0Xuzhi Xie1Munan Sun2Ming Zhao3Yuepeng Sun4Power China Sinohydro Bureau 7 Co., Ltd.Power China Sinohydro Bureau 7 Co., Ltd.Power China Sinohydro Bureau 7 Co., Ltd.Power China Sinohydro Bureau 7 Co., Ltd.State Key Laboratory of Hydraulics and Mountain River EngineeringAs tunnel excavation and resource extraction progressively extend into deeper underground environments, the frequency of large deformation incidents in soft surrounding rock tunnels is increasing worldwide. To accurately and efficiently predict the large deformation tendencies of such tunnels, this study establishes, validates, and applies a multi-index evaluation method based on microseismic (MS) source parameters in the context of plateau railway soft surrounding rock tunnels. A multi-index evaluation approach based on an attribute recognition model is proposed, which comprehensively considers four key MS event parameters: the number of events (N), moment magnitude (mW), seismic energy (E), and the tunnel’s convergence deformation value. By analyzing various practical engineering cases, the weight of each parameter is assessed using a fuzzy comprehensive evaluation method. The identification model for large deformation tendencies in soft surrounding rock tunnels is constructed through weighted evaluation and the attribute measurement function of each index. The accuracy and applicability of the proposed multi-index evaluation method are validated through the analysis of large deformation instances in soft surrounding rock tunnels from field engineering. The results demonstrate that the prediction of large deformation tendencies based on MS monitoring closely aligns with the actual occurrences of large deformations in soft surrounding rock tunnels. The findings provide a foundation for assessing significant deformation tendencies in tunnels subjected to high-ground stress in weak surrounding rocks, with important implications for forecasting large deformation risks in such tunnels.http://dx.doi.org/10.1155/adce/8860238
spellingShingle Qiang Wang
Xuzhi Xie
Munan Sun
Ming Zhao
Yuepeng Sun
Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
Advances in Civil Engineering
title Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
title_full Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
title_fullStr Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
title_full_unstemmed Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
title_short Research on the Development Trend and Graded Early Warning of Large Deformations in Soft Rock Tunnels: Microseismic and Deformation Monitoring
title_sort research on the development trend and graded early warning of large deformations in soft rock tunnels microseismic and deformation monitoring
url http://dx.doi.org/10.1155/adce/8860238
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AT munansun researchonthedevelopmenttrendandgradedearlywarningoflargedeformationsinsoftrocktunnelsmicroseismicanddeformationmonitoring
AT mingzhao researchonthedevelopmenttrendandgradedearlywarningoflargedeformationsinsoftrocktunnelsmicroseismicanddeformationmonitoring
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