Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information
Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluati...
Ausführliche Beschreibung
Autor*in: |
Peng He [verfasserIn] Gang Wang [verfasserIn] Shangqu Sun [verfasserIn] Weiteng Li [verfasserIn] Feng Jiang [verfasserIn] Chengcheng Zheng [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Übergeordnetes Werk: |
In: Geomatics, Natural Hazards & Risk - Taylor & Francis Group, 2016, 11(2020), 1, Seite 1528-1541 |
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Übergeordnetes Werk: |
volume:11 ; year:2020 ; number:1 ; pages:1528-1541 |
Links: |
Link aufrufen |
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DOI / URN: |
10.1080/19475705.2020.1803996 |
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Katalog-ID: |
DOAJ060735988 |
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520 | |a Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. | ||
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10.1080/19475705.2020.1803996 doi (DE-627)DOAJ060735988 (DE-599)DOAJ0f6d17667c5e49489d6a4ff0cb9afc62 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Peng He verfasserin aut Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. tunnel engineering surrounding rock stability discontinuous deformation analysis removable blocks digital characterization of joint information Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Gang Wang verfasserin aut Shangqu Sun verfasserin aut Weiteng Li verfasserin aut Feng Jiang verfasserin aut Chengcheng Zheng verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 11(2020), 1, Seite 1528-1541 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:11 year:2020 number:1 pages:1528-1541 https://doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/article/0f6d17667c5e49489d6a4ff0cb9afc62 kostenfrei http://dx.doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2020 1 1528-1541 |
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10.1080/19475705.2020.1803996 doi (DE-627)DOAJ060735988 (DE-599)DOAJ0f6d17667c5e49489d6a4ff0cb9afc62 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Peng He verfasserin aut Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. tunnel engineering surrounding rock stability discontinuous deformation analysis removable blocks digital characterization of joint information Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Gang Wang verfasserin aut Shangqu Sun verfasserin aut Weiteng Li verfasserin aut Feng Jiang verfasserin aut Chengcheng Zheng verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 11(2020), 1, Seite 1528-1541 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:11 year:2020 number:1 pages:1528-1541 https://doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/article/0f6d17667c5e49489d6a4ff0cb9afc62 kostenfrei http://dx.doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2020 1 1528-1541 |
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10.1080/19475705.2020.1803996 doi (DE-627)DOAJ060735988 (DE-599)DOAJ0f6d17667c5e49489d6a4ff0cb9afc62 DE-627 ger DE-627 rakwb eng TD1-1066 GE1-350 Peng He verfasserin aut Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. tunnel engineering surrounding rock stability discontinuous deformation analysis removable blocks digital characterization of joint information Environmental technology. Sanitary engineering Environmental sciences Risk in industry. Risk management HD61 Gang Wang verfasserin aut Shangqu Sun verfasserin aut Weiteng Li verfasserin aut Feng Jiang verfasserin aut Chengcheng Zheng verfasserin aut In Geomatics, Natural Hazards & Risk Taylor & Francis Group, 2016 11(2020), 1, Seite 1528-1541 (DE-627)626457491 (DE-600)2553648-5 19475713 nnns volume:11 year:2020 number:1 pages:1528-1541 https://doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/article/0f6d17667c5e49489d6a4ff0cb9afc62 kostenfrei http://dx.doi.org/10.1080/19475705.2020.1803996 kostenfrei https://doaj.org/toc/1947-5705 Journal toc kostenfrei https://doaj.org/toc/1947-5713 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2020 1 1528-1541 |
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Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information |
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Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. |
abstractGer |
Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. |
abstract_unstemmed |
Since all available surrounding rock classification approaches don't consider the size effect of the tunnel excavation span and unfavourable geologic bodies, it’s impossible to evaluate the systematic stability of the surrounding rock by rock mass classification alone. In addition, the evaluation results usually have poor robustness because of the uncertainty of structural information. In this paper, the actual distribution information and probability distribution model of the joints in tunnel face are obtained. Many random numbers that meet the probabilistic distribution models can be produced by Monte carlo simulation, and many random rating values of these evaluation indices are also obtained. The distribution probability affiliated with different rock mass levels can be attained by inductive statistics, and a robust evaluation of surrounding rock classification is carried out. The deformation and failure process of surrounding rock are simulated based on the discontinuous deformation analysis. A comparison analysis of removable blocks and their distribution characteristics is carried out by UJN. The most likely damaged parts and rockfall styles are indicated, and a comparison between calculation result and practical collapse of Laohushan tunnel is carried out, which are nearly the same. The research results offer practical guidance for field construction and supporting optimization. |
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Reliable stability analysis of surrounding rock for super section tunnel based on digital characteristics of joint information |
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