Optimized back-analysis for tunneling-induced ground movement using equivalent ground loss model

Chi, Shue‐Yeong; Chern, J. M.; Lin, Chien‐Liang

doi:10.1016/s0886-7798(01)00048-7

Cited by 66 publications

(24 citation statements)

References 4 publications

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“…Ou and Tang (1994) proposed a nonlinear optimization technique to determine soil parameters for deep excavation finite element analysis and studied a hypothetical excavation case under a variety of ground conditions. Chi et al (2001) obtained optimized parameters by applying an optimization technique for back-analysis that produced results in good agreement with field measurements.…”

Section: Introductionmentioning

confidence: 81%

Prediction of Diaphragm Wall Deflection in Deep Excavations Using Evolutionary Support Vector Machine Inference Model (ESIM)

Cheng

2009

Proceedings of the 2009 International Symposium on Automation and Robotics in Construction (ISARC 2009)

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Problems in deep excavations are full of uncertain, vague, and incomplete information. In most instances, successfully solving such problems depends on experts' knowledge and experience. The primary object of this research was to propose an "Evolutionary Support Vector Machine Inference Model (ESIM)" to predict wall deformation in deep excavation in Taipei Basin. ESIM is developed based on a hybrid approach that fuses support vector machines (SVM) and fast messy genetic algorithm (fmGA). SVM is primarily concerned with learning and curve fitting; and fmGA with optimization. Fifty-seven wall deformation monitoring database were collected based on monitoring data and compiled from prior projects. Fifty-two of 57 were selected for training, leaving 5 valid cases available for testing. Results show that ESIM can successfully predict the deflection and apply to contractors utilizes the knowledge and experience from past projects to predict wall deformation of new projects. Therefore the construction and foundation construction contractors can update wall deflection monitoring data of different stages during deep excavation process, in order to predict the wall deformation of the next stage and examine whether the max deflection is within the controlled range. The results are used as guidelines on site safety and risk management.

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Section: Introductionmentioning

confidence: 81%

Prediction of Diaphragm Wall Deflection in Deep Excavations Using Evolutionary Support Vector Machine Inference Model (ESIM)

Cheng

2009

Proceedings of the 2009 International Symposium on Automation and Robotics in Construction (ISARC 2009)

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“…The model yields 49.9 and 58.7 mm of initial maximum surface settlements for the right and the left tube tunnel, which is 100 mm behind the right tube, respectively. There are several analytical models for the prediction of short-term maximum surface settlements for shielded tunneling operations (Lee et al 1992;Loganathan and Poulos 1998;Chi et al 2001;Chou and Bobet 2002;Park 2004). The method suggested by Loganathan and Poulos (1998) is used in this study.…”

Section: Surface Settlement Prediction With Semi-theoretical and Analmentioning

confidence: 99%

Surface settlement predictions for Istanbul Metro tunnels excavated by EPB-TBM

2010

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In this study, short-term surface settlements are predicted for twin tunnels, which are to be excavated in the chainage of 0 ? 850 to 0 ? 900 m between the Esenler and Kirazlı stations of the Istanbul Metro line, which is 4 km in length. The total length of the excavation line is 21.2 km between Esenler and Basaksehir. Tunnels are excavated by employing two earth pressure balance (EPB) tunnel boring machines (TBMs) that have twin tubes of 6.5 m diameter and with 14 m distance from center to center. The TBM in the right tube follows about 100 m behind the other tube. Segmental lining of 1.4 m length is currently employed as the final support. Settlement predictions are performed with finite element method by using Plaxis finite element program. Excavation, ground support and face support steps in FEM analyses are simulated as applied in the field. Predictions are performed for a typical geological zone, which is considered as critical in terms of surface settlement. Geology in the study area is composed of fill, very stiff clay, dense sand, very dense sand and hard clay, respectively, starting from the surface. In addition to finite element modeling, the surface settlements are also predicted by using semi-theoretical (semi-empirical) and analytical methods. The results indicate that the FE model predicts well the short-term surface settlements for a given volume loss value. The results of semi-theoretical and analytical methods are found to be in good agreement with the FE model. The results of predictions are compared and verified by field measurements. It is suggested that grouting of the excavation void should be performed as fast as possible after excavation of a section as a precaution against surface settlements during excavation. Face pressure of the TBMs should be closely monitored and adjusted for different zones.

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“…This deformation mode of Equation 7 is same as that proposed by some scholars. 20,30,31 When b ′ 1 ¼ 0 and a ′ 2 ¼ 0, Equation 3 can be simplified as Equation 8:…”

Section: Tunnel Cross-section Unified Deformation Functionmentioning

confidence: 99%

Displacement analytical prediction of shallow tunnel based on unified displacement function under slope boundary

Kong

et al. 2018

Num Anal Meth Geomechanics

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Summary For slope condition of ground surface, the asymmetrical deformation about the vertical center line and the horizontal center line of the tunnel cross section can be formed. A unified displacement function expressed by the Fourier series is presented to express the asymmetrical deformation of the tunnel cross section. Five basic deformation modes corresponding to the expansion order 2 are a complete deformation mode to reflect deformation behaviors of the tunnel cross section under slope boundary. Such this complete displacement mode is implemented into the complex variable solution for analytically predicting tunneling‐induced ground deformation under slope boundary. All of these analytical solutions are verified by good agreements of the comparison between the analytical solutions and finite element method results. A parameter study is carried out to investigate the influence of deformation modes of the tunnel cross section, geometrical conditions of the tunnel and the slope angle, and “Buoyancy effect” on the displacement field. Finally, the proposed method is consistent with measured data of the Hejie tunnel in China qualitatively. The presented solution can provide a simplified indication for evaluating the ground deformation under slope condition of ground surface.

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Optimized back-analysis for tunneling-induced ground movement using equivalent ground loss model

Cited by 66 publications

References 4 publications

Prediction of Diaphragm Wall Deflection in Deep Excavations Using Evolutionary Support Vector Machine Inference Model (ESIM)

Prediction of Diaphragm Wall Deflection in Deep Excavations Using Evolutionary Support Vector Machine Inference Model (ESIM)

Surface settlement predictions for Istanbul Metro tunnels excavated by EPB-TBM

Displacement analytical prediction of shallow tunnel based on unified displacement function under slope boundary

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