Vertical tunneling in China-A case study of a hydraulic tunnel in Beihai

Wang, Xiao; Behbahani, Seyed Saleh; Iseley, Tom; Azimi, Mohammadamin; Wei, Xinjiang; Wei, Gang; Shi, Yu Cheng

doi:10.1016/j.tust.2020.103650

Cited by 12 publications

(22 citation statements)

References 16 publications

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“…To deal with the sewage from the sewage treatment plant in Beihai, China, the VTM was used to construct vertical standpipes in the sea area, together with the pipe jacking method [1][2][3]. The horizontal tunnel was built by the pipe jacking method firstly, and the diameter was 2000 mm.…”

Section: Construction Processmentioning

confidence: 99%

“…Figure 3 shows the construction flow chart of the VTM. Wang et al depicted a detailed description of the VTM, comprising the construction process [3]. Before the VTM construction started, the soil above the excavation line was excavated.…”

Section: Construction Processmentioning

confidence: 99%

“…The deviation tolerances ranged from 3 to 4 mm in different conditions. More details about the construction process of the VTM can be found in [3]. There were 21 standpipe sections for each standpipe in total; the first standpipe section was 50 cm in length, and the remaining sections were 60 cm in length.…”

Section: Construction Processmentioning

confidence: 99%

“…There are only a few studies related to the jacking force of the VTM available to date [1][2][3]. To calculate the jacking force during the vertical tunneling process in advance, Wang et al regarded standpipes as reverse piles and utilized the Meyerhof foundation theory to compute the maximum jacking force [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…To calculate the jacking force during the vertical tunneling process in advance, Wang et al regarded standpipes as reverse piles and utilized the Meyerhof foundation theory to compute the maximum jacking force [1,2]. To gain insight into the effective factors that influence the jacking force, Wang et al have conducted case research about the vertical tunneling project, concluding that the jacking force is affected by factors such as the average jacking speed, the jacking distance, the geological conditions, and the effective overburden soil pressure [3].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Prediction of Jacking Force in Vertical Tunneling Projects Based on Neuro-Genetic Models

Wei

Wang

Wei

et al. 2021

JMSE

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The vertical tunneling method is an emerging technique to build sewage inlets or outlets in constructed horizontal tunnels. The jacking force used to drive the standpipes upward is an essential factor during the construction process. This study aims to predict the jacking forces during the vertical tunneling construction process through two intelligence systems, namely, artificial neural networks (ANNs) and hybrid genetic algorithm optimized ANNs (GA-ANNs). In this paper, the Beihai hydraulic tunnel constructed by the vertical tunneling method in China is introduced, and the direct shear tests have been conducted. A database composed of 546 datasets with ten inputs and one output was prepared. The effective parameters are classified into three categories, including tunnel geometry factors, the geological factor, and jacking operation factors. These factors are considered as input parameters. The tunnel geometry factors include the jacking distance, the thickness of overlaying soil, and the height of overlaying water; the geological factor refers to the geological conditions; and the jacking operation factors consist of the dead weight of standpipes, effective overburden soil pressure, effective lateral soil pressure, average jacking speed, construction hours, and soil weakening measure. The output parameter, on the other hand, refers to the jacking force. Performance indices, including the coefficient of determination (R2), root mean square error (RMSE), and the absolute value of relative error (RE), are computed to compare the performance of the ANN models and the GA-ANN models. Comparison results show that the GA-ANN models perform better than the ANN model, especially on the RMSE values. Finally, parametric sensitivity analysis between the input parameters and output parameter is conducted, reaching the result that the height of overlaying water, the average jacking speed, and the geological condition are the most effective input parameters on the jacking force in this study.

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Section: Construction Processmentioning

confidence: 99%

Section: Construction Processmentioning

confidence: 99%

Section: Construction Processmentioning

confidence: 99%