Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI
Abstract The regression analysis method is being widely adopted to analyse the tunnel strain, most of which ignore the strain-softening effect of the rock mass and fail to consider the influence of support pressure, initial stress state, and rock mass strength classification in one fitting equation....
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Nature Portfolio
2022-11-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-23587-x |
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author | Lan Cui Qian Sheng Jun Zhang You-kou Dong Zhen-shan Guo |
author_facet | Lan Cui Qian Sheng Jun Zhang You-kou Dong Zhen-shan Guo |
author_sort | Lan Cui |
collection | DOAJ |
description | Abstract The regression analysis method is being widely adopted to analyse the tunnel strain, most of which ignore the strain-softening effect of the rock mass and fail to consider the influence of support pressure, initial stress state, and rock mass strength classification in one fitting equation. This study aims to overcome these deficiencies with a regression model used to estimate the tunnel strain. A group of geological strength indexes (GSI) are configured to quantify the input strength parameters and deformation moduli for the rock mass with a quality ranging from poor to excellent. A specific semi-analytical procedure is developed to calculate the tunnel strain around a circular opening, which is validated by comparison with those using existing methods. A nonlinear regression model is then established to analyse the obtained tunnel strain, combining twelve fitting equations to relate the tunnel strain and the factors including the support pressure, GSI, initial stress state, and critical softening parameter. Particularly, three equations are for the estimation of the critical tunnel strain, critical support pressure, and tunnel strain under elastic behaviour, respectively; and the other nine equations are for the tunnel strain with different strain-softening behaviours. The relative significance between the GSI, the initial stress and the support pressure on the tunnel strain is assessed. |
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institution | Directory Open Access Journal |
issn | 2045-2322 |
language | English |
last_indexed | 2024-04-12T04:09:55Z |
publishDate | 2022-11-01 |
publisher | Nature Portfolio |
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spelling | doaj.art-aaa836b814db47c4bab853c7b121a3692022-12-22T03:48:32ZengNature PortfolioScientific Reports2045-23222022-11-0112111910.1038/s41598-022-23587-xEvaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSILan Cui0Qian Sheng1Jun Zhang2You-kou Dong3Zhen-shan Guo4State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of SciencesState Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of SciencesKey Laboratory of Highway Construction and Maintenance Technology in Loess Region of Ministry of Transport, Shanxi Transportation Technology Research & Development Co., Ltd.College of Marine Science and Technology, China University of GeosciencesKey Laboratory of Highway Construction and Maintenance Technology in Loess Region of Ministry of Transport, Shanxi Transportation Technology Research & Development Co., Ltd.Abstract The regression analysis method is being widely adopted to analyse the tunnel strain, most of which ignore the strain-softening effect of the rock mass and fail to consider the influence of support pressure, initial stress state, and rock mass strength classification in one fitting equation. This study aims to overcome these deficiencies with a regression model used to estimate the tunnel strain. A group of geological strength indexes (GSI) are configured to quantify the input strength parameters and deformation moduli for the rock mass with a quality ranging from poor to excellent. A specific semi-analytical procedure is developed to calculate the tunnel strain around a circular opening, which is validated by comparison with those using existing methods. A nonlinear regression model is then established to analyse the obtained tunnel strain, combining twelve fitting equations to relate the tunnel strain and the factors including the support pressure, GSI, initial stress state, and critical softening parameter. Particularly, three equations are for the estimation of the critical tunnel strain, critical support pressure, and tunnel strain under elastic behaviour, respectively; and the other nine equations are for the tunnel strain with different strain-softening behaviours. The relative significance between the GSI, the initial stress and the support pressure on the tunnel strain is assessed.https://doi.org/10.1038/s41598-022-23587-x |
spellingShingle | Lan Cui Qian Sheng Jun Zhang You-kou Dong Zhen-shan Guo Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI Scientific Reports |
title | Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI |
title_full | Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI |
title_fullStr | Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI |
title_full_unstemmed | Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI |
title_short | Evaluation of input geological parameters and tunnel strain for strain-softening rock mass based on GSI |
title_sort | evaluation of input geological parameters and tunnel strain for strain softening rock mass based on gsi |
url | https://doi.org/10.1038/s41598-022-23587-x |
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