Evaluation of ground settlement in response to shield penetration using numerical and statistical methods: a metro tunnel construction case

Wang, Fan; Gou, Biancai; Zhang, Qiling; Qin, Yawei; Li, Bo

doi:10.1080/15732479.2015.1076852

Cited by 25 publications

(5 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The principle of virtual work (hereafter PVW) was used. The weak form of the FEM was used, adding Galerkin's approximation (to use the same shape functions as those used for the unknowns of the problem) [21,55]. Firstly, the governing equation as the weighted residual method is defined by a test function, denoted as ∇ω :…”

Section: Fundamentals Of the Finite Element Methods Applied In Porous...mentioning

confidence: 99%

“…There are also empirical formulations with statistical adjustment in reference to tunnelling. In these cases, the original principle of elastic or elastoplastic deformation of the soil is modified to favour the obtention of more accurate predictions [21]. Although useful, these formulations require adaptations to be used in a general manner.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Finite Element Method Integrated with Terzaghi’s Principle to Estimate Settlement of a Building Due to Tunnel Construction

et al. 2023

View full text Add to dashboard Cite

This study presents the application of the finite element method integrated with Terzaghi’s principle. The definition of a model in oedometric or confinement conditions for settlement estimation of a building after the construction of a tunnel, including the effect of Terzaghi’s principle, is an unresolved problem. The objectives of this work include the demonstration of the need for a minimum of three methodological states to estimate said settlement. For this, a specific methodology is applied to a case study, with eight load steps and four types of coarse-grained soils. In the studied case, two layers of 50 m and 5 m with different degrees of saturation are overlaying an assumed impermeable rock layer. The excavation of a tunnel of 15 m in diameter at a depth of 30 m with drainage lining inside the tunnel is assumed. The minimum distance from the tunnel’s outline to the mat foundation is 15.8 m. It is determined that the settlement, according to Terzaghi’s principle, is around 11% of the total settlement for the most compacted soil types, reaching 35% for the loose soil type, from the tunnel’s outline. In the mat foundation, it implies an increase in the differential settlement of up to 12%. It shows a nonlinear relationship between some of the variables in the analysis. To detect the collapse due to uplifting the tunnel invert, it was determined that it was not appropriate to model in oedometric conditions. The novelty of the investigation relies on identifying and determining the need for a minimum of three states for methodological purposes for a proper quantification of the total settlement: (i) before the construction of the tunnel, (ii) immediately after the excavation of the tunnel, but without groundwater inflow into the tunnel, and (iii) after the tunnelling, with stabilised groundwater inflow into the tunnel.

show abstract

Section: Fundamentals Of the Finite Element Methods Applied In Porous...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Finite Element Method Integrated with Terzaghi’s Principle to Estimate Settlement of a Building Due to Tunnel Construction

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Recently, some researchers have successfully used AI-based algorithms to establish a model for predicting the settlement induced by shield tunneling, such as artifcial neural networks (ANNs), fuzzy logic (FL), support vector machine (SVM), and gene expression programming (GEP) [7,14]. Wang et al successfully applied an adaptive relevance vector machine (aRVM) to predict real-time settlement development [9]. Bouayad and Emeriault proposed a methodology that combines the principal component analysis (PCA) with an adaptive neuro-fuzzy-based inference system (ANFIS) to model the nonlinear relationship between ground surface settlements induced by an earth pressure-balanced TBM [7].…”

Section: Ai-based Algorithm Applications For Predictingmentioning

confidence: 99%

“…Terefore, while the TBM is in operation, a safety monitoring system must be active. Tis system collects site data and supervises TBM maneuvers to prevent excessive ground settlement, which can damage existing urban infrastructure and buildings and trigger disastrous accidents [3,5,[9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Self-Tuning Inference Model for Settlement in Shield Tunneling: A Case Study of the Taipei Mass Rapid Transit System’s Songshan Line

Cheng,

Khitam,

Wang

2023

Structural Control and Health Monitoring

View full text Add to dashboard Cite

Constructing tunnels in urban spaces usually uses shield tunneling. Because of numerous uncertainties related to underground construction, appropriate monitoring systems are required to prevent disasters from happening. This study collected the settlement monitoring data for Tender CG291 of the Songshan Line of the Taipei Mass Rapid Transit (MRT) system and considered that influential factors were examined to identify the correlations between predictor variables and settlement outcomes. An inference model based on symbiotic organisms search-least squares support vector machine (SOS-LSSVM) was proposed and trained on the collected data. Moreover, because the dataset used for this study contained far less data at the alert level than at the safe level, the class of the dataset was imbalanced, which could compromise the classification accuracy. This study also employed the probability distribution data balance sampling methods to enhance the forecast accuracy. The results showed that the SOS-LSSVM exhibited the most favorable accuracy compared to four other artificial intelligence-based inference models. Therefore, the proposed model can serve as an early warning reference in tunnel design and construction work.

show abstract

“…Bouayad and Emeriault [27] proposed a method combining principal component analysis (PCA) with adaptive neural fuzzy inference system (ANFIS) to model the nonlinear relationship between ground subsidence caused by soil pressure balance TBM and construction parameters and geological parameters. Wang et al [28] screened the main influencing parameters of land subsidence through threedimensional numerical modeling, and then built a real-time prediction model of land subsidence by using aSVM (Support Vector Machines, SVM). Mahdevari et al [29] used SVM to build the land subsidence prediction model, and used square error (R 2 ) and mean square error (MSE) to evaluate the prediction model.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Axis Attitude Deviation and Deviation Correction Method Based on Data Driven During Shield Tunneling

et al. 2019

View full text Add to dashboard Cite

Due to the complex shield construction characteristics and the complex effects of geological environment, it is difficult to control the direction of shield tunneling and to determine the reasonable tunneling parameters such as tunneling speed and so on. During the tunneling, shield tunneling machine may rise, shift and snake advance, which are not conducive to control tunnel axis. Aiming at the problem that it is difficult to accurately predict and correct the axis attitude deviation in the shield tunneling process, a prediction of axis attitude deviation and deviation correction method based on data driven during shield tunneling was put forward in this paper. Under certain geological conditions, the relationship between the attitude deviation of the construction axis and tunneling parameters during shield tunneling process with different tunneling mileages is established. Based on the tunneling historical data, the XGBoost prediction model is constructed, and the axis deviation variation is predicted and analyzed with the shield construction parameters. The multi-ring deviation correction parameter calculation model based on the fusion of geometric model and association rules is designed to obtain the internal correlation of the deviation amount, the number of deviation correction rings and the deviation correction parameters of each ring under the maximum deviation of different deviation correction sections, so as to realize the accurate prediction and deviation correction of shield axis deviation in the complex construction process. Under the verification of 155 ring data in a certain subway construction section, the method proposed in this paper has higher prediction accuracy, which is important for improving the safety and quality of shield tunneling. Results from the measured shield construction ring data verify the reasonability of the proposed axis attitude deviation prediction and multi-ring deviation correction method.

show abstract

Evaluation of ground settlement in response to shield penetration using numerical and statistical methods: a metro tunnel construction case

Cited by 25 publications

References 34 publications

A Finite Element Method Integrated with Terzaghi’s Principle to Estimate Settlement of a Building Due to Tunnel Construction

A Finite Element Method Integrated with Terzaghi’s Principle to Estimate Settlement of a Building Due to Tunnel Construction

Self-Tuning Inference Model for Settlement in Shield Tunneling: A Case Study of the Taipei Mass Rapid Transit System’s Songshan Line

Prediction of Axis Attitude Deviation and Deviation Correction Method Based on Data Driven During Shield Tunneling

Contact Info

Product

Resources

About