Water Inrush In Karst Tunnels Research Articles

Risk prediction of water inrush in karst tunnels and analysis of surrounding rock stability

Karst tunnel construction has always been an important and difficult point in tunnel engineering. Based on the Yilai Expressway Wantan Tunnel Project, this paper analyzes the water-bearing lithofacies of the surrounding rock of the Wantan Tunnel and the karst hydrogeological conditions of the tunnel site area, and predicts the risk of tunnel water inrush disaster. Through monitoring and measurement, the existing construction technology was analyzed and the following conclusions were drawn: The surrounding rock of the Wantan Tunnel is a typical carbonate phase stratum, with a large amount of water inflow during the rainy season. There are local caves and karst pipes, and the comprehensive water inrush assessment level is III (medium risk); According to the monitoring, the displacement and deformation of each monitoring section in the tunnel changes normally, and the cumulative deformation value is less than 1/3 of the limit value. The stability of the surrounding rock is good, and the construction safety is high.

Experimental Study on Similar Materials for Fluid–Solid Coupling for Model Test of Water Inrush in Karst Tunnel

Experimental Study on Similar Materials for Fluid–Solid Coupling for Model Test of Water Inrush in Karst Tunnel

Study on Catastrophe Information Characteristics of Water Inrush in Karst Tunnel by Drilling and Blasting Method

When building tunnels in karst areas, the hidden high-pressure water-bearing karst caves are prone to cause geological disasters such as water inrush and mud gushing. In order to study the disaster process of water and mud resistant rock mass with the quasi-masonry structure and the accompanying catastrophe information of water inrush in karst tunnels by the drilling and blasting method, a new method based on the DEM and fictitious joint technology is adopted to simulate the evolution process of water inrush and study the evolutionary characteristics of catastrophe information like seepage pressure and displacement under the conditions of different joint inclination angles, tunnel depths, and thickness of the water and mud resistant rock mass. The research results show that (1) the seepage pressure and displacement in the water and mud resistant rock mass decrease and increase respectively along the water and mud resistant rock mass from top to bottom in the process of water inrush. (2) The displacement and seepage pressure in the water and mud-resistant rock mass increases with the increase of the joint inclination angle. The greater the tunnel depth and thickness of the water and mud-resistant rock mass, the faster the propagation speed of the fissure zone. (3) With the increase of the water and mud-resistant rock mass thickness, the failure mode of the tunnel outburst layer structure gradually changes from the overall collapse to the partial collapse of the vault to form a relatively stable slump arch. The research results can provide some guidance for tunnel construction in the karst tunnel.

Research on the Mechanism and Safe Thickness of Karst Tunnel-Induced Water Inrush under the Coupling Action of Blasting Load and Water Pressure

When the drilling and blasting method is used to construct a tunnel through the karst stratum, the coupling effect of the blasting load and the karst water pressure in front of the tunnel face exposes the tunnel face to the risk of water inrush, which threatens the safety of personnel and property. It is very important for the design and construction of related tunnels to study the evolution mechanism of water inrush in karst tunnels and determine the minimum thickness of outburst prevention under blasting. Relying on the Dejiang tunnel Project in Tongren City, this paper adopts the Smoothed Particle Hydrodynamic–Finite Element Method (SPH-FEM) coupling calculation method to study the evolution process of water inrush in karst tunnels under blasting, analyzing the results of water inrush in tunnels under different rock wall thicknesses under blasting. Then, according to the regression of rock wall stress peak data, the analysis determines the minimum outburst prevention thickness of the karst tunnel. The research results show that there is a superposition effect between the blasting stress wave and the gravitational interaction of the karst water itself, and that the Smoothed Particle Hydrodynamic (SPH) particles in the aquifer cause damage and cracks to the rock wall under the coupling action of the blasting load and the karst water pressure, further leading to the expansion of the cracks and the formation of inrush channels. the stress, vibration velocity, and displacement of the unit at the junction of the aquifer and the rock layer show a trend that first decreases, then increases, and then decreases with an increase in the thickness of the rock wall. Based on the actual geological conditions of the Dejiang tunnel project parameters, when the thickness of the rock wall is 3.08 m, the peak stress of the rock formation unit at the junction with the aquifer reaches the maximum value. In order to avoid water inrush during blasting, the minimum outburst prevention thickness should be greater than 3.08 m. Based on the analysis results, a corresponding water inrush prevention plan was formulated on site which effectively guaranteed construction safety and, at the same time, verified the reliability of the analysis results. The relevant research results can provide useful references for similar projects.

Research on the Evolution Mechanism of Water Inrush in Karst Tunnel and the Safety Thickness of Water-Resisting Rock Mass

Research on the Evolution Mechanism of Water Inrush in Karst Tunnel and the Safety Thickness of Water-Resisting Rock Mass

A New Bayesian Network Model for the Risk Assessment of Water Inrush in Karst Tunnels

Water inrush seriously restricts the safe construction of a karst tunnel. Once it occurs, it will cause serious consequences such as economic loss and casualties. Due to the complexity of an underground environment, it is difficult to calculate the probability of karst tunnel water inrush. Therefore, it is of great engineering significance to establish an effective risk assessment model. Based on the Bayesian theory, interpretation structure model, and generative adversarial network, a Bayesian network risk assessment model is established. The results show that firstly, twelve indexes selected can not only characterize the karst tunnel water inrush but also are easy to be counted, which effectively improves the accuracy of the Bayesian risk assessment model. Secondly, the Bayesian network risk assessment model overcomes the shortcomings of other risk assessment models that rely too much on geological data and improves the accuracy through massive data training. Thirdly, the corresponding noninrush samples are generated by the generative adversarial network and analytic hierarchy process, which effectively solve the problem of an unbalanced database. Finally, the Bayesian network risk assessment model is applied to the DK490+373 section of the Shangshan Tunnel. The assessment model is operable, effective, and practical, and it is also suitable for the situation of incomplete index statistics.

Risk assessment of water inrush in karst tunnels based on fuzzy comprehensive evaluation considering misjudgment losses: a case study

Risk assessment of water inrush in karst tunnels based on fuzzy comprehensive evaluation considering misjudgment losses: a case study

Study of the mechanism of water inrush in karst tunnel based on transparent rock mass physical model test

Water inrush is the main geological disaster occurred during karst tunnel excavation, which will cause huge economic losses and casualties. Therefore, it is important to investigate the water inrush mechanism of karst tunnel surrounding rock mass for preventing water inrush disasters in karst tunnel construction. Herein, Xinjie Tunnel of Kaili Ring Expressway in Guizhou Province is chosen as an object, where a large water-filled karst cave may locate on the upper right side of the tunnel cross section according to the geological survey report. Then taking the typical tunnel cross section as the prototype, a three-dimensional geomechanical model of Xinjie tunnel is made by using transparent rock mass material based on similarity theory, on which laboratory water inrush physical model tests are performed. Based on laboratory physical model test results, the mechanism of water inrush in karst tunnel is investigated, from which it indicates that the groundwater mainly flows through the fissures of the tunnel surrounding rock during water inrush process, and the water inflow rate mainly depends on the initial water pressure of the water-filled karst cave. When water pressure increases from 0.1MPa to 0.2MPa, the water inflow increases by 84.4%, but the increase rate of water inflow will slow down when water pressure further increases. Compared with the previous level of water pressure, the water inflow only increases by 7.2%. Hence, in the excavation of karst tunnel, it is necessary to seal the fractures by grouting timely and release the water pressure of the karst cave for preventing water inrush accident. The research results will provide important guiding significance for the excavation of karst tunnel.

Model on Improved Variable Weight-Matter Element Theory for Risk Assessment of Water Inrush in Karst Tunnels

This paper presents an improved risk assessment model to evaluate the risk of water inrush in karst tunnels based on matter element theory and ideal point method. The 4 first-grade evaluation indexes and 13 s-grade factors are selected to establish the evaluation index system by considering the occurrence conditions of water inrush. All second-grade evaluation indexes are quantitatively divided into four risk grades. Based on improved Analytical Hierarchy Process and Triangular Fuzzy Number, the constant weights are obtained. The variable weights are determined according to the state variable weight theory and the values of evaluation indexes. The risk grade of water inrush is recognized by the closeness degree analysis. The proposed risk assessment model was applied to 3# inclined shaft of Yuelongmen tunnel, and the accuracy of the assessment result was verified by comparing with advance geological forecast and excavation. This proposed model provides a practical tool to evaluate the risk of water inrush in karst tunnels.

The non-Darcy characteristics of fault water inrush in karst tunnel based on flow state conversion theory

The fault water inrush is a key factor which leads to tunnel construction in karst regions. Based on the fluid mechanics principles, the paper addresses a numer?ical coupled model for karst fault tunnel with COMSOL Multiphysics software. Besides, the Darcy law equation, Brinkman equation, and Navier-Stokes equation are inserted to stimulate the steady flow of aquifer, the non-linear seepage of fault and the free flow in tunnel excavating area in software, respectively. Then, the pres?sure and flow velocity in three flow fields are analyzed under different permeability ratios in numerical model. It is shown that the fault permeability is the key factor affecting water inrush, and that the pressure and flow velocity change visibly in adjacent domains between two flow fields.

Uncertainty Evaluation of Water Inrush in Karst Tunnels Based on Epistemic Uncertainty with Possibility Theory

In the risk assessment of water inrush in karst tunnel, it is most important to provide an available theoretical model for qualifying the epistemic uncertainties due to a lack of knowledge and information. Firstly, a mechanical model dependent on geology is introduced associating with four parameters, i.e., the elastic modulus E, the Poisson ratio μ, the water differential pressure q, and the tunnel radius a. Then, a mathematical model representing epistemic uncertainty is represented with probability theory and possibility theory. The methodology was computerized to calculate the distribution of the margin and uncertainty and then to determine the ratio of “margin/uncertainty.” Analyses involving possibility theory and possibility theory are illustrated with the same engineering example used in the presentation indicated above to illustrate the use of probability to represent aleatory and epistemic uncertainty in QMU analyses. The comparison between the uses of possibility theory and probability theory for the representation of aleatory and epistemic uncertainty indicates that the possibility is not only has a better mathematical structure than probability theory but also has some challenges.

Risk assessment of water inrush in tunnels based on attribute interval recognition theory

Water inrush is one of the most serious geological hazards in underground engineering construction. In order to effectively prevent and control the occurrence of water inrush, a new attribute interval recognition theory and method is proposed to systematically evaluate the risk of water inrush in karst tunnels. Its innovation mainly includes that the value of evaluation index is an interval rather than a certain value; the single-index attribute evaluation model is improved non-linearly based on the idea of normal distribution; the synthetic attribute interval analysis method based on improved intuitionistic fuzzy theory is proposed. The TFN-AHP method is proposed to analyze the weight of evaluation index. By analyzing geological factors and engineering factors in tunnel zone, a multi-grade hierarchical index system for tunnel water inrush risk assessment is established. The proposed method is applied to ventilation incline of Xiakou tunnel, and its rationality and practicability is verified by comparison with field situation and evaluation results of other methods. In addition, the results evaluated by this method, which considers that water inrush is a complex non-linear system and the geological conditions have spatial variability, are more accurate and reliable. And it has good applicability in solving the problem of certain and uncertain problem.

A new quantitative method for risk assessment of water inrush in karst tunnels based on variable weight function and improved cloud model

Water inrush disaster seriously affects the safety of karst tunnel construction. It’s essential to assess the risk level of water inrush in karst tunnels accurately, and take some effective countermeasures to reduce the damage to the project. We integrates the variable weight theory and cloud model theory to construct the VW&ICM calculation model to evaluate the risk of construction of karst tunnels. First, we select the index factors that affect the risk of water inrush from karst tunnels. Secondly, according to the theory of variable weight, we construct the zoning variable weight model, and the normalization criterion of the data from index factors is established. Thirdly, according to the attribute mathematic theory, we select the numerical characteristics of the improved cloud model, and the normal cloud generator is used to establish the point membership function. Finally, the risk index data is brought into the variable weight vector function and the point membership function to obtain the variable weight vector W and the membership degree matrix R. The risk overall evaluation vector B is further calculated, and the membership degree fluctuation is comprehensively analyzed according to the principle of maximum membership degree. The scope determines the risk of water inrush from karst tunnels. Finally, calculate the variable weight vector W and the membership matrix R, and the overall risk evaluation vector B is further integrated by W and R. According to the max-subjection principle and the fluctuation rule of membership, we get the risk level of water inrush in karst tunnel. The VM&ICM not only can quantitatively evaluate risk by considering the uncertainty of risk assessment and the influence of indicator size on weight, but also can make an analysis of the reliability to make the assessment result more convincing. The model makes improvement in weakening the influence of subjective factors on assessment results and in allocating the weight of indicators. A simple and practical software package is developed, which greatly improves the computational efficiency of VW&ICM method. The VW&ICM calculation model is applied to the risk assessment of water inrush for karst tunnels, and the results are basically consistent with the on-site construction situation.

Study on the risk assessment of water inrush in karst tunnels based on intuitionistic fuzzy theory

Water inrush is a major geological hazard that threatens the safety of karst tunnels. The risk assessment of water inrush is necessary in tunnel engineering. A new model based on intuitionistic fuzzy analysis was proposed to assess the risk of water inrush, which considered the subjective and objective weights of influencing factors. Seven factors were selected to constitute the set of evaluation attributes, namely, formation lithology, unfavourable geological conditions, groundwater level, landform and physiognomy, modified strata inclination, contact zones of dissolvable and insoluble rock, and layer and interlayer fissures. The proposed model was applied in a typical karst tunnel, Xiakou tunnel in China. The sensitivity of the changes in the index weights was analyzed. The results showed that the water inrush risk of section XJK0 + 110 to XJK0 + 060 in Xiakou tunnel was evaluated as grade I (high risk). The risk assessment results were more sensitive to the index weights of landform, formation lithology, and contact zones of dissolvable and insoluble rock than to those of the other indices. Landform was the most sensitive index. The obtained results were identical to the practical findings, and the rationality and feasibility of the model was verified. Intuitionistic fuzzy analysis is a new method for the quantitative risk assessment of water inrush in karst tunnels.

Analysis on the Precursor Information of Water Inrush in Karst Tunnels: A True Triaxial Model Test Study

Water inrush in karst tunnels usually results in casualties, equipment damage, project delays and other serious consequences. An important measure to ensure the safety of tunnel construction is to provide accurate prediction of water inrush during tunnel excavation. To study the stability of the surrounding rock under effect of a water-bearing cave in front of the tunnel face, a true triaxial geomechanical model test was carried out based on the engineering background of the Xiema Tunnel in Chongqing Province. The response regularities of multivariate physical information of the surrounding rock during rock failure and water inrush were obtained by monitoring the displacement, stress and seepage pressure of different monitoring sections. The results show that some internal connections exist among the kinds of physical information. When the tunnel face was adjacent to the disaster source, the change of displacement and stress was in a decreasing trend, and the seepage pressure increased first and then decreased during the tunnel excavation. In addition, by fusion analysis, the sensitivity priority of precursor information for a rock failure and water inrush disaster in karst tunnels was summarized as stress, displacement and seepage pressure. Finally, the theoretical basis of the prediction of water inrush in karst tunnels had been established, which proved the feasibility of predicting disasters according to the precursor information.

Risk Assessment of Water Inrush in Karst Tunnels Based on the Ideal Point Method

Risk Assessment of Water Inrush in Karst Tunnels Based on the Ideal Point Method

Risk assessment of water inrush in karst tunnels excavation based on normal cloud model

Water inrush in karst tunnels is a dynamic process in which internal and external factors are involved. The evaluation of this process is fuzzy, complex, and uncertain. In the current research, few articles give full consideration to the fuzziness and randomness of the water inrush evaluation with useful dynamic feedback. A new assessment method has been proposed for the water inrush evaluation based on a combination of the weighting method and normal cloud model. Specifically, an evaluation index system is forged and each index is quantitatively classified into four grades. A synthetic weighted algorithm combining the analytic hierarchy process, entropy method, and statistical methods is proposed to assign the index weight rationally. Based on the cloud generator algorithm, three numerical characteristics are calculated and a sufficient number of cloud droplets are generated. The membership degree of each index belonging to each grade is constructed and the integrated certain grades are determined. In this paper, the multi-factor normal cloud assessment method is applied to the risk assessment of the Qiyueshan tunnel. The assessment result of the risk grade is accurate, that is, the water inrush risk of different samples at the same risk grade can be reflected in figures. The results not only show high consistency with other assessment methods but are also in good agreement with the excavation results. The proposed cloud model method demonstrates good practical reference for risk assessment of tunnel construction in karst areas and can be applied to tunneling, mining, and other engineering practices in the future.

Risk Assessment of Water Inrush in Karst Tunnels Based on the Efficacy Coefficient Method

Risk Assessment of Water Inrush in Karst Tunnels Based on the Efficacy Coefficient Method

Quantification of Margins and Uncertainties for the Risk of Water Inrush in a Karst Tunnel: Representations of Epistemic Uncertainty with Probability

Accidents involving water inrush in karst tunnels often occur in China, resulting in serious social impact and huge economic loss. So, it is important that engineers provide a method with which to evaluate the risk of water inrush in karst tunnels. There are some problems regarding water inrush such as nonlinearity, and nominal, uncertain variables. Based on the mathematical model of water inrush, this paper proposes a methodology including a mechanical model dependent on geology and a mathematical model with quantification of margins and uncertainties (QMU), to evaluate the risk of water inrush. The following subjects are considered: (1) the risk assessment model is combined with mechanical analysis of water inrush in the karst tunnel in a perfect, dynamic way, (2) the analysis of uncertainty in QMU in the risk of water inrush, (3) the representations of uncertainty with probability theory, (4) the QMU analyses containing only epistemic uncertainty are represented, (5) the sensitivity analysis of parameters was performed through a step-wise regression analysis. This synthetic risk evaluation system provides a powerful and novel tool for systematically evaluating water inrush risk in karst tunnels.

Risk assessment of water inrush in karst tunnels based on two-class fuzzy comprehensive evaluation method

A feasible and accurate method named two-class fuzzy comprehensive evaluation is put forward to assess the risk of water inrush in karst tunnels. In view of regarding tunnel face as the evaluation object, 12 influencing factors of water inrush are selected as the evaluation index system consisting of 4 first-class and 12 second-class indices. Based on fuzzy mathematics theory and expert evaluation method, all the indices are quantitatively graded according to five risk grades. The weights of indices affecting water inrush are rationally distributed by using analytic hierarchy process. Membership functions and weights of indices are utilized to stepwise compute the membership degree of indices corresponding to risk grade, and the principle of maximum membership degree is carried out to discern the risk grade of water inrush. The tunnel faces in seven segments of Qiyueshan tunnel are chosen as the case studies. Evaluation results are derived from the proposed method, and they are generally consistent with the actual results through comparisons. This method provides a cogent way for evaluating the risk of water inrush in karst tunnels.