Water leakage susceptible areas in loess multi-arch tunnel operation under the lateral recharge conditions

Mao, Zhengjun; Wang, Xiaokang; An, Ning; Li, Xiaojun; Wei, Rongyu; Wang, Yaqiong; Wu, Hao

doi:10.1007/s12665-020-09083-3

Cited by 14 publications

(3 citation statements)

References 19 publications

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“…For example, Wang et al (2013) developed a prediction method for WS based on real-time monitoring data during tunnel construction. Mao et al (2020) applied 3D numerical simulations to determine the distribution of the total water head and water pressure in cracks for all combinations of water leakage positions during the operation periods of multi-arch tunnels in loess areas. Shi et al (2013) introduced the improved analytic hierarchy process (AHP) into leakage risk assessment for a highway tunnel.…”

Section: Literature Reviewmentioning

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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Section: Literature Reviewmentioning

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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“…However, as the weak part of the concrete structures, deformation joints increase the risk of water seepage. In deep aquifer zones, nearly 90% of subway stations have leakage problems, and nearly 30% of the leakage occurs at deformation joints [3,4]. Once water seepage occurs, it will not only reduce the strength of the concrete structure but also bring safety hazards to later operations.…”

Section: Introductionmentioning

confidence: 99%

Numerical Computing Research on Tunnel Structure Cracking Risk under the Influence of Multiple Factors in Urban Deep Aquifer Zones

Ma,

Wang,

et al. 2023

Mathematics

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During the operation period of tunnels in urban deep aquifer zones, the geological environment around the tunnel is complex and the surrounding strata are rich in groundwater, which often poses a risk of structure cracking and groundwater leakage, seriously threatening the tunnel’s safety. To reduce the risk of tunnel cracking, a theoretical calculation model and a three-dimensional concrete–soil interaction thermo-mechanical coupling numerical computing model was established to analyze the tunnel structure cracking risk under the influence of multiple factors in urban deep aquifer zones. The response mechanism of structural stress and deformation under the influence of the grade of rock and soil mass, overburden thickness, temperature difference, structure’s length–height ratio, structure’s thickness, and structure’s elastic modulus was investigated, and the stress and deformation response characteristics of the structure with deformation joints were explored. The results show that the maximum longitudinal tensile stress of the structure increases with the increase in the grade of rock and soil mass, overburden thickness, temperature difference, structure’s length–height ratio, and elastic modulus. The temperature difference has the most significant impact on the longitudinal tensile stress of the structure, with the maximum tensile stress of the structure increasing by 2.8 times. The tunnel deformation joints can effectively reduce the longitudinal tensile stress of the structure, and the reduction magnitude of the tensile stress is the largest at the deformation joints, which is 64.7%.

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“…ere is a big difference between the waterproof and drainage of multiarch tunnels and separate tunnels. Mao et al [20,21] used 3D numerical simulation to analyze the water leakage susceptible area of the loess multiarch tunnel.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Physical and Chemical Reactions on Water Leakage in a Multiarch Tunnel

Shi

et al. 2020

Advances in Civil Engineering

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In many tunnels in China, the groundwater is acidic and carbonated, causing in challenges in the prevention and control of leakages of the existing tunnels and tunnels under construction. Research on tunnel leakage and the physical and chemical effects of water due to water-rock interactions is a trending topic. In addition, there is a big difference between the waterproof and drainage of multiarch tunnels and separate tunnels. In this study, the mechanism of the interaction between the groundwater and the surrounding rock of a multiarch tunnel were analyzed. The relationship between the leakage of a multiarch tunnel and the interaction between the surrounding rocks and groundwater was determined by analyzing the interaction between the chemical components in the groundwater, rocks, and the concrete lining. A mathematical model was established based on the physical and chemical reactions in the rock surrounding the tunnel, and the RNCDX.FOR program was compiled using the simplex Monte Carlo method. The total free energy in the entire system varied significantly, and the value of objective function (J) reflected the trend of the system's spontaneous reaction. As J decreased, the reaction power of the system increased. The more significant the erosion of the rocks was by the groundwater, the more channels were created by the groundwater in the rock, and the more likely the water leakage was.

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Water leakage susceptible areas in loess multi-arch tunnel operation under the lateral recharge conditions

Cited by 14 publications

References 19 publications

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

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

Numerical Computing Research on Tunnel Structure Cracking Risk under the Influence of Multiple Factors in Urban Deep Aquifer Zones

The Influence of Physical and Chemical Reactions on Water Leakage in a Multiarch Tunnel

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