2009
DOI: 10.2219/rtriqr.50.81
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Prediction Method of Tunnel Deformation Using Time-dependent Ground Deterioration Model

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Cited by 16 publications
(8 citation statements)
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“…(1) Prediction methods for mountain tunnel deformation [4,5] In mountain tunnels, deformation such as displacement and/or upheaval sometimes occurs due to the action of ground pressure, which may occur over a long period of time. For that reason, geological surveys and long-term monitoring of convergences are conducted.…”
Section: Tunnel Deformation Prediction Methodsmentioning
confidence: 99%
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“…(1) Prediction methods for mountain tunnel deformation [4,5] In mountain tunnels, deformation such as displacement and/or upheaval sometimes occurs due to the action of ground pressure, which may occur over a long period of time. For that reason, geological surveys and long-term monitoring of convergences are conducted.…”
Section: Tunnel Deformation Prediction Methodsmentioning
confidence: 99%
“…Using those data, a numerical analysis method was developed whereby time dependency of the deformation is reproduced by reducing ground strength over the course of time, and the method's applicability to existing tunnels for deformation prediction and measures planning was confirmed (See Fig. 3) [4]. Furthermore, based on this method, another method was developed that can reproduce runnel behavior from the construction stage into the service stage, which can also be used for research into optimization of tunnel structures.…”
Section: Tunnel Deformation Prediction Methodsmentioning
confidence: 99%
“…15, we obtained Eq. (8), which, with a correlation coefficient of 0.9, is the optimal regression line passing through all points and represents the general relation of radial strain and strength factor. : ð8Þ…”
Section: Empirical Correlationsmentioning
confidence: 99%
“…The development of the prediction of tunnel deformation criteria can be relevant to the progress in identification of squeezing ground condition since 1980s. Research on this matter has been conducted by many scholars, e.g., [1,[4][5][6][7][8][9][10][11][12][13][14]. Li et al [1] proposed a new method integrating support vector machine (SVM), particle swarm optimization (PSO) and chaotic mapping (CPSO-SVM) to predict the deformation of tunnel surrounding rock mass.…”
Section: Introductionmentioning
confidence: 99%
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