Characteristics, numerical analysis and countermeasures of mud inrush geohazards of Mountain tunnel in karst region

Chen, Long-Long; Wang, Zhi-Feng; Zhang, Wu; Wang, Ya-Qiong

doi:10.1080/19475705.2023.2242691

Cited by 5 publications

(2 citation statements)

References 61 publications

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“…However, sensitivity analyses of the factors influencing the stability of karst tunnels [22,23] have rarely been conducted in the published literature, and the application of machine-learning algorithms to characterise the importance of factors [24] affecting karst tunnels is also relatively rare. In this paper, the orthogonal experimental design method and random forest algorithm [25] are combined to rank the influencing factors of karst tunnels according to sensitivity from high to low and to determine the optimal level of combination.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Influencing Factors of Karst Tunnel Construction Based on Orthogonal Tests and a Random Forest Algorithm

Wu,

Sun,

Meng

2024

Applied Sciences

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To conduct a sensitivity analysis of the relevant parameters that impact the mechanics of tunnel construction in karst areas, firstly, the orthogonal design and range analysis method is applied to sort the 11 kinds of karst-tunnel-influencing factors from high to low according to the sensitivity degree. Secondly, the random forest algorithm based on an orthogonal experimental design is applied to the feature importance ranking of the influencing factors of karst tunnels. Thirdly, according to the results of the sensitivity analysis, the optimum combinations of influencing factors of tunnel construction in karst areas is obtained. The research based on these two methods shows that when taking the vertical displacement as the target variable, the parameters with the highest feature importance are A6 (tunnel diameter) and A10 (tunnel buried depth). When taking the first principal stress as the target variable, the most important influencing factors are A10 (tunnel buried depth) and A9 (location of karst cave). When taking the principal stress difference as the target variable, the most important influencing factors are A10 (tunnel buried depth) and A6 (tunnel diameter). The level combination of the 11 influencing factors obtained by taking the principal stress difference as the target variable was more balanced than the vertical displacement and the principal stress difference as the target variables. The results of this study will provide a theoretical basis to study key parameters in the response of mechanical characteristics to the safe construction of tunnels in karst areas.

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Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of Influencing Factors of Karst Tunnel Construction Based on Orthogonal Tests and a Random Forest Algorithm

Wu,

Sun,

Meng

2024

Applied Sciences

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“…With the development of express highways, high-speed railways, hydropower stations and other civil engineering projects, a large number of tunnels have been under construction in recent years 1 , 2 . Inevitably, the construction of tunnels is risky when encountering karst landforms, which account for one-third of China’s land area 3 .Water and mud inrushes have become common geological disasters that occur in karst regions 4 .…”

Section: Introductionmentioning

confidence: 99%

Development and experimental validation of analytical models for water and mud inrushes through a filled karst conduit

Wu,

Yang,

Jing

2024

Sci Rep

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Water or mud inrush has become a common geological disaster during tunnel construction in karst areas. To study forming process and mechanism of water and mud inrushes through a filled karst conduit, water inrush and mud inrush model tests were carried out with a self-developed 3D model test system. The results show that the forming processes of water inrush and mud inrush have different forming modes. For water inrush, the forming process follows: flowing instability of filling material particles—formation of water inrush channel—water inrush occurring; while for mud inrush, the forming process follows: stability—sliding instability of the whole filling material suddenly—mud inrush occurring. Accordingly, a local instability model of critical hydraulic pressure causing water inrush and an integral sliding instability model of critical hydraulic pressure causing mud inrush were established respectively. The two analytical models reveal the mechanism of water inrush and mud inrush experiments to an extent. The calculated critical hydraulic pressures for water inrush and mud inrush are in good agreement with the test results. The distinguishment of water inrush and mud inrush through a karst conduit was discussed based on the critical hydraulic pressure and the evolution law of seepage water pressure in tests, and a criterion was given. The research results might provide guidance for the forecast of water and mud inrush disasters during the construction of tunnels in karst area.

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Research on environmental geological problems caused by water and mud inrush in tunnels and long-term drainage: taking Chaoyang Tunnel of Guinan High-Speed Railway as an example

Dai,

Wei,

Pan

et al. 2024

Carbonates Evaporites

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Characteristics, numerical analysis and countermeasures of mud inrush geohazards of Mountain tunnel in karst region

Cited by 5 publications

References 61 publications

Sensitivity Analysis of Influencing Factors of Karst Tunnel Construction Based on Orthogonal Tests and a Random Forest Algorithm

Sensitivity Analysis of Influencing Factors of Karst Tunnel Construction Based on Orthogonal Tests and a Random Forest Algorithm

Development and experimental validation of analytical models for water and mud inrushes through a filled karst conduit

Research on environmental geological problems caused by water and mud inrush in tunnels and long-term drainage: taking Chaoyang Tunnel of Guinan High-Speed Railway as an example

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