Twin tunnel configuration for Greater Cairo metro line No. 4

Abd-el.rahim, Hamdy H.A.; Enieb, Mahmoud; Khalil, Ahmed A.; Ahmed, Abdou S.

doi:10.1016/j.compgeo.2015.03.015

Cited by 26 publications

(3 citation statements)

References 4 publications

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“…It can be seen from the Figure 11,12,13 show that the axial force (pressure is negative, tension is positive) of the grid steel frame is pressure, and the pressure range is about −250 ÷ 0 kN; the axial force of the grid steel frame is generally characterized by 'large arch, followed by side wall and small inverted arch'. Based on field test, the maximum axial force of the grid steel frame occurs at the side wall (6#) position, which is -247.14 kN.…”

Section: Internal Force Analysis Of Initial Supportmentioning

confidence: 98%

“…Choi and Shin [12] utilzed three-dimensional finite difference software to simulate the actual situation and proposes the optimal support scheme. Rahim et al [13] studied the rock response of shallow doublehole excavation by numerical analysis. Qu et al [14] studied the initial release load law of steel arch support and the change law of bearing capacity of two support structures with time, and gave the applicable conditions of steel arch and steel grid.…”

Section: Introductionmentioning

confidence: 99%

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Archives of Civil Engineering

Han,

Xiao,

Shi

et al. 2022

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The optimization process of design parameters for composite lining of heavy haul railway tunnel is a key problem to be solved in tunnel engineering design. In order to put forward a better design scheme of composite lining for heavy haul railway tunnel, combined with field measurement and numerical simulation, the optimal working condition design is carried out by changing the thickness of shotcrete layer, the type of grid steel frame and the thickness of secondary lining. The influence of the above design parameters on the stress state of the composite lining is analyzed to obtain the optimal design parameters. Finally, the safety performance of the optimized lining is evaluated by the ultimate bearing capacity curve of the secondary lining section. The research shows that: 1) The optimal design parameters of the composite lining of the tunnel are the thickness of the shotcrete layer of 25 cm, the type of the grid steel frame of H180, the thickness of the secondary lining arch waist and the side wall of 40 cm and 35 cm respectively; 2) Different from the single-track heavy haul railway tunnel, the displacement value of the vault settlement of the double-track heavy haul railway tunnel is significantly greater than that of the inner convergence. Increasing the thickness of the shotcrete layer and changing the type of the grid steel frame have better effects on reducing the vault settlement, and have little effect on the inner convergence.

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Section: Internal Force Analysis Of Initial Supportmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Archives of Civil Engineering

Han,

Xiao,

Shi

et al. 2022

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“…With the increase in urbanization and population influx around the world, urban problems such as insufficient urban space capacity and frequent traffic jams are constantly emerging (Zho et al, 2019;He et al, 2019;Zhang et al, 2020aZhang et al, , 2020b. Urban metro systems are popular due to their energy savings, high passenger flow, safety, green transportation characteristics, and so on (Rahim et al, 2015;Qian et al, 2019;Pan et al, 2019c). By the end of 2019, metros had been built and had begun operating in 40 areas in mainland China, with a total length of approximately 6700 km.…”

Section: Introductionmentioning

confidence: 99%

Risk Prediction and Diagnosis of Water Seepage in Operational Shield Tunnels Based on Random Forest

Liu

Chen

Zhang

et al. 2021

Journal of Civil Engineering and Management

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Water seepage (WS) is a paramount defect during tunnel operation and directly affects the operational safety of tunnels. Effectively predicting and diagnosing WS are problems that urgently need to be solved. This paper presents a standard and an evaluation index system for WS grades and constructs a sample dataset from monitoring recoreds for demonstration purposes. First, we use bootstrap resampling to build a random forest (RF) seepage risk prediction model. Second, the optimal branch and parameters are selected by the 5-fold cross-validation method to establish the RF prediction training model. Additionally, to illustrate the effectiveness of the method, the operational stage of Wuhan Metro Line 3 in China is taken as a case study. The results conclude that the segment spalling area, crack width, and loss rate of the rebar cross-section have a strong influence on WS. Finally, the test data are predicted, and the prediction result error index is calculated. Compared with the predictions of some traditional machine learning methods, such as support vector machines and artificial neural networks, RF prediction has the highest accuracy and is the closest to the true value, which demonstrates the accuracy of the model and its application potential.

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