Surrounding Rock Level Research Articles

Tunnel entrance crossing spoil heap deformations control by micropile combine with coupling beams

Aiming at the deformation control problem of the tunnel entrance crossing the spoil heap at the Xialao junction, this paper adopts the micropile combined with the coupling beams method to treat the spoiled layers. The results show that the excavation of the tunnel after the construction of the micropile and coupling beam will cause vertical deformation of the tunnel and the slope surface. The main reason is that the soil layer structure is loose, and the tunnel excavation causes the whole displacement of the loose body. In addition, the buried depth of the tunnel is shallow, so it cannot form an effective soil arch. The stability process after the construction of the micropile method is the process of stress redistribution, and the rock and soil are gradually compressed and compacted. That is, the construction by the micropile method changes the surrounding rock level of the tunnel and reduces the height of the soil arch. Therefore, it is suggested that the tunnel excavation should be carried out when the micropile is constructed after the soil layers are consolidated completely. The micropile method treats the loose spoiled soil at the tunnel entrance, which saves 73% of the total cost compared with the scheme of directly digging out the accumulation, and the economic benefit is very obvious.

Influence Analysis of Rock Mass Mechanical Properties on Tunnel Rock Stability Based on Sensor Data Integration

This study takes the multisensor monitoring data of tunnel support structure and surrounding rock mechanical properties during TBM construction as the research object, integrates the monitoring data of multisensor through an intelligent optimization algorithm, and explores the self‐consistent fusion characteristics between the multisensor structural mechanical properties and the field monitoring data. At the same time, the support structure parameters and construction progress in the tunnel construction process are dynamically adjusted and scientifically integrated through the information feedback of monitoring data. The research results are as follows: (1) The tunnel excavation rate is different under different rock strengths and surrounding rock levels. The overall performance is that the harder the surrounding rock, the lower the surrounding rock level, and the faster the tunnel excavation rate. The relationship between the FPI parameters of surrounding rock and the deformation of tunnel surrounding rock is closer, and the correlation coefficient reaches 98%. The mechanical properties of the surrounding rock have the greatest influence on its deformation. (2) The rotation speed, thrust, and torque of TBM machinery as well as the surrounding rock workability index and the tunnel surrounding rock deformation maintain a good fitting relationship, with a fitting rate of more than 85%. After the improved PSO‐BP algorithm is used to calculate and fit the four parameters of torque, rotational speed, thrust, and surrounding rock drivable coefficient during TBM mechanical construction, the fitting accuracy is higher than 94%. (3) At the same time, according to the analysis of the fitting results, the fitting effect of TBM mechanical thrust is the best among the four‐parameter algorithm analysis fitting degrees, which is 99.3%. (4) The measured points are evenly distributed near the surrounding rock deformation surface calculated by the improved PSO‐BP algorithm, and the fitting variance is 0.972. With the tunnel excavation, the settlement deformation of surrounding rock first increases rapidly, and then, the settlement deformation enters a slow growth stage and finally reaches a relatively stable state. (5) After the jam occurs, the tunnel is expanded from the telescopic shield or tail shield to the outer side of the shield to reduce the contact area between the shield and the surrounding rock to reduce the extrusion of the surrounding rock pressure on the shield.

A probability prediction method for the classification of surrounding rock quality of tunnels with incomplete data using Bayesian networks

The classification of surrounding rock quality is critical for the dynamic construction and design of tunnels. However, obtaining complete parameters for predicting the surrounding rock grades is always challenging in complex tunnel geological environment. In this study, a new method based on Bayesian networks is proposed to predict the probability for the classification of surrounding rock quality of tunnel with incomplete data. A database is collected with 286 cases in 10 tunnels, involving nine parameters: rock hardness, weathering degree, rock mass integrity, rock mass structure, structural plane integrity, in-situ stress, groundwater, rock basic quality, and surrounding rock level. Moreover, the Bayesian network structure is built using the collected database and quantitatively verified by strength analysis. Then, the accuracy, precision, recall, F-measure and receiver operating characteristic (ROC) curves are utilized for model evaluation. The average values of accuracy, precision, recall, F-measure, and area under the curve (AUC) are approximately 89.2%, 91%, 92%, 91%, and 0.98, respectively. These results indicate that the established classification model has high accuracy, even with small sample size and imbalanced samples. Ten additional sets of tunnel cases (incomplete data) are also used for verification. The results reveal that compared with the traditional Q-system (Q) and rock mass rating (RMR) classification methods, the proposed classification model has the lowest error rate and is capable of using incomplete data to predict sample results. Finally, sensitivity analysis suggests that the rock hardness and rock mass integrity have the strongest impact on the quality of tunnel surrounding rock. Overall, the findings of this study can serve as a useful reference for future rock mass quality evaluation in tunnels, underground powerhouses, slopes, etc.

Risk assessment of collapse in mountain tunnels and software development

As most frequent geological hazard, the collapse is a great threat to safe construction of tunnels. The risk assessment method for collapse in mountain tunnels was presented with six evaluation indices, including surrounding rock level I1, rock mass integrity I2, buried depth I3, bias angle I4, groundwater I5, and construction factors I6. According to the non-linear relationship between the collapse and its influencing factors, the synthetic attribute assessment model was improved based on the concept of normal distribution. The weight of each index consisted of two parts: the subjective weight obtained by analytic hierarchy process (AHP) and the objective weight determined by correlation analysis. The Mountain Tunnel Collapse Risk Assessment System (TCAS) was developed based on Visual Studio 2012 and C# programming language. The TCAS was applied to assess the collapse risk of Hongyansi tunnel from Baoyi to Yichang expressway (Xiangyang section). The result was a good agreement with actual excavation situation that a “closed door” collapse happened. Therefore, the software system can not only accurately assess the risk level of collapse but also will play an important role in rapid assessment in the whole process of tunnel construction.

Numerical Simulation of Explosion of Late-excavated Tunnel Parts of Double-arch Tunnel without Middle Drift

Compared with the construction method of a tunnel with a middle drift, the construction method of a tunnel without a middle drift is a more advanced, novel, efficient, and energy efficient. Moreover, the blasting excavation of late-excavated tunnel parts exerts a vibration impact on the lining structure of early excavated tunnel parts. To analyze and predict the influence of late-excavated tunnel blasting on an early excavated tunnel and surrounding rocks in a triangular area, this study uses the Ansys LS-DYNA software to build a three-dimensional tunnel model simulating multihole blasting and the fluid–solid interaction method to assess the interaction of different materials. In addition, the different working conditions of surrounding rock levels and explosive equivalents are simulated. The distribution law of peak particle vibration velocity and maximum principal stress peak value of surrounding rocks and the lining along the transverse and longitudinal directions of the early excavated tunnel are generalized based on the numerical simulation results. The influence of the blasting of a late-excavated tunnel on the initial lining, secondary lining, and the middle triangular area of a double-arch tunnel is analyzed. The relationship between the surrounding rock level, explosive equivalent, and vibration velocity peak value is concluded. The field experiment-measured vibration velocities from the double-arch tunnel without a middle drift in the Chenjiachong tunnel of the Chuyao expressway in Yunnan Province, China, are in satisfactory agreement with the numerical simulation results. The results of this study are verified by the field blasting vibration data of the Chenjiachong and Changba tunnels and can provide reference and guidance for the blasting engineering practices of late-excavated double-arch tunnels without a middle drift.

A Dynamic Risk Assessment Method for Deep-Buried Tunnels Based on a Bayesian Network

In view of the shortcomings in the risk assessment of deep-buried tunnels, a dynamic risk assessment method based on a Bayesian network is proposed. According to case statistics, a total of 12 specific risk rating factors are obtained and divided into three types: objective factors, subjective factors, and monitoring factors. The grading criteria of the risk rating factors are determined, and a dynamic risk rating system is established. A Bayesian network based on this system is constructed by expert knowledge and historical data. The nodes in the Bayesian network are in one-to-one correspondence with the three types of influencing factors, and the probability distribution is determined. Posterior probabilistic and sensitivity analyses are carried out, and the results show that the main influencing factors obtained by the two methods are basically the same. The constructed dynamic risk assessment model is most affected by the objective factor rating and monitoring factor rating, followed by the subjective factor rating. The dynamic risk rating is mainly affected by the surrounding rock level among the objective factors, construction management among the subjective factors, and arch crown convergence and side wall displacement among the monitoring factors. The dynamic risk assessment method based on the Bayesian network is applied to the No. 3 inclined shaft of the Humaling tunnel. According to the adjustment of the monitoring data and geological conditions, the dynamic risk rating probability of level I greatly decreased from 81.7% to 33.8%, the probability of level II significantly increased from 12.3% to 34.0%, and the probability of level III increased from 5.95% to 32.2%, which indicates that the risk level has risen sharply. The results show that this method can effectively predict the risk level during tunnel construction.

Influence of adjacent surface building on seismic response of shallow buried subway station structure

Taking the 6-storey frame structure as an example, using FLAC numerical simulation, the influence of the adjacent multi-storey buildings on the seismic response of the metro station structure (including the internal force and bias state of the station structure) is studied systematically, and the relationship between the influence and surrounding rock level change is analyzed. The research shows that the existence of surface buildings has obvious amplification effect on the internal force of the subway station and above. It mainly shows that the eccentricity of the vault of the subway station is increased, and the eccentricity of the arch waist is reduced. It has a great influence on the internal force and distribution range of the station structure. The worse the surrounding rock, the greater the internal force and influence range of the building to the station structure.

Dynamic Risk Assessment Method of Collapse in Mountain Tunnels and Application

The collapse is one of the most frequent and harmful geological hazards in the construction process of mountain tunnels. In order to effectively control the occurrence of collapse, a new dynamic risk assessment methodology for collapse based on attribute synthetic evaluation model was established, which includes primary assessment before the excavation and second assessment between excavation and support. According to statistical analysis of many collapse cases, the surrounding rock level I1, rock mass integrity I2, buried depth I3, bias angle I4, groundwater I5, construction factors I6 were selected as assessment indices. Their weights were calculated by using a combination method: subjective weight based on frequency statistic method and objective weight based on analytic hierarchy process. According to the proposed method, the Mountain Tunnel Collapse Risk Assessment System (TCAS) was developed to carry out the real-time assessment for collapse in the mountain tunnel. The TCAS was applied in Hongyansi Tunnel and Shimenya Tunnel. The results were a good agreement with actual excavation situation and the results of other methods.

Case Study of Modified H–B Strength Criterion in Discrimination of Surrounding Rock Loose Circle

Intermediate principal stress is a significant factor when calculate to determine the surrounding rock loose circles. Based on it, this paper is trying to modify the Hoek–Brown strength criterion, and put forwards a theoretical formula of the loose circle radius. The theoretical formula is applied to Shimen Tunnel, and a comparative analysis between theoretical calculations and field test results is conducted. Here are the results as follows: 1) With an increase of intermediate principal stress, the strength of the rock mass increases and the surrounding rock becomes more difficult to break. Consequently, loose circle thickness is gradually reduced and forms a significant negative linear relationship with the Lode parameter. 2) The results indicate that with a decrease of surrounding rock level in a three-lane hard rock tunnel, the radius of the loose circle increases continuously. 3) The results of the field acoustic wave test show that the theoretical calculation values are consistent with the field measurement results. According to above analysis, the deduced formula is feasible.

Study of the basement structure load under the dynamic loading of heavy-haul railway tunnel

ABSTRACT The base structure in heavy-haul railway tunnels is greatly affected by the train load, which leads to a much higher rate of basal structure disease compared with that of an ordinary tunnel. In this paper, two different axle loads of a heavy-haul train, 270 and 300 kN, are set as the research objects, and calculations for the additional load on the surface of the basement structure, including the ballast, invert arc filling, invert arc and rock, caused by a heavy-haul train in single and double lines when the classifications of the surrounding rock are III, IV and V are carried out. These calculations are all based on existing domestic specifications, research results and the layered elastic theory. In addition to the theoretical calculations, research methods including a field-embedded optical fibre grating sensor, large vibration test and real-time remote monitoring have been applied to obtain measurements that could verify the calculation. According to the study results, taking each type of rock and axle load condition into consideration, the calculations and measurements reveal that the maximal additional dynamic loads on the heavy-haul railway appear in the vertical direction of the track, and they decrease when the basal structure goes deeper. The study also finds that the surrounding rock level has a great effect on the maximal load and its attenuation in the vertical direction.

Influence of factors on collapse risk of loess tunnel: a multi-index assessment model

PurposeBecause of the properties of loess, the occurrence of collapse following deformation of a large settlement is a common problem during the excavation of tunnels on loess ground. Hence, risk management for safer loess tunnel construction is of great significance. The purpose of this paper is to explore the influence of factors on collapse risk of loess tunnels and establish a risk assessment model using rough set theory and extension theory.Design/methodology/approachThe surrounding rock level, groundwater conditions, burial depth, excavation method and support close time were selected as the factors and settlement deformation was the verification index for risk assessment. First, using rough set theory, the influence of risk factors on the collapse risk of loess tunnels was calculated by researching engineering data of excavated sections. Then, a collapse risk assessment model was developed based on extension theory. As the final step, the model was applied to practical engineering in the Loess Plateau of China.FindingsThe weights of surrounding rock level, groundwater conditions, burial depth, excavation method and support close time obtained using rough set theory were respectively 10.811 per cent, 18.919 per cent, 24.324 per cent, 40.541 per cent and 5.406 per cent. The assessment results obtained using the model were in good agreement with field observations.Originality/valueThis study highlights key points in collapse risk management of loess tunnels, which could be very useful for future construction methods. The model, using easily obtained parameters, helps in predicting the collapse risk level of loess tunnels excavated under different geological conditions and by different construction organizations and provides a reference for future studies.

Analysis of factors influencing tunnel deformation in loess deposits by data mining: A deformation prediction model

Due to the special properties of loess, the deformation of tunnels constructed in loess is generally large and easily induced. To control deformation during construction, the degree of influence of multiple factors on tunnel deformation is analyzed by data mining and a deformation prediction model is established, based on tunnels along the Menghua railway of China. Both objective environment and manual operation are considered. The surrounding rock level, groundwater condition, burial depth, excavation method and support close time are selected as the main factors influencing tunnel deformation. The influence degree of each factor is calculated through mining statistical data collected from the project. Finally, using influencing factors as evaluation indices, a Rough set-extension model for predicting loess tunnel deformation is established and tested. Results obtained via the prediction model are in good agreement with field observations. The study quantifies the influence degree of each selected factor on deformation of the loess tunnel, which in turn can help in deformation control efforts. Moreover, the Rough set-extension model realizes a multi-criteria prediction of the loess tunnel's deformation and provides a practical guide for construction of similar projects.

Vibratory Influential Zoning for Grade-Separated Tunnels Under the Load of Trains

Grade-separated tunnels are even more vulnerable components in high-speed railway engineering structures. The dynamic characteristics of tunnels under a train load are key indicators that influence the safe operation and durability of the entire line. In this study, with consideration of the major factors influencing grade-separated tunnels for high-speed rails, such as train speed, traffic mode, surrounding rock type, between-tunnel height, and crossing angle, a parameterized finite element model is established based on an orthogonal experimental design. In the proposed model, tensile stress (under which any vibration-induced structural damage is caused) is defined as a main evaluation index, and thus the empirical formula for each influencing factor is obtained. When the index was determined under multiple factors and at different levels, rock height between tunnels is found to be the biggest factor influencing the response of grade-separated tunnels to the vibratory load of the trains, followed by train speed, surrounding rock level, and crossing angle. Finally, based on the relevant standards for concrete stress, the zoning of grade-separated tunnels under the vibratory load of trains is established by multiple factors. Such zoning provides important theoretical references for future structural design, maintenance, and reinforcement of grade-separated tunnels for high-speed rails.

The Reasearch of the Level of Tunnel Surrounding Rock and the Stability Based on Fractal Theory

A new nonlinear discipline named Fractal theory which is a scientific theory and method studied the irregular of nature and complex phenomena has been used in civil engineering direction successfully in recent years. Take the Kuo changshan tunnel as an example, this paper will use the Range finder to measure the shape of surrounding rock along different longitudinal section contour line, then using the fractal theory to analyze it as follows: using section assumption, box counting method and higher dimensional method to calculate the fractal dimension, and to explore the relative relations between fractal dimension and stability of surrounding rock of the tunnel. The research results show that the more rough the tunnel longitudinal section contour line, the bigger the fractal dimension, the worse the corresponding stability of surrounding rock and the worse the lower the level of surrounding rock . Above all the tunnel longitudinal irregular section contour line has obvious fractal characteristics.

Study on Bolt (Cable) Supporting Design Method Based on Tunnel Fall Hidden Dangers Classification

In order to give scientific and rational targeted support design of the roadway under the different rock conditions, ensure the safety of the roadway, and reduce support costs. By theoretical analysis, establishing the roadway hidden dangers grading mechanical model, proposing the method of tunnel fall hidden dangersclassification, on this basis, giving adaptive evaluation through existing branch of engineering analogy, loose circle test method, the theoretical calculations, numerical simulation methods supporting design methods, determining the theoretical calculation method based on the roadway roof stability classification for the design of bolt (Cable) support of roadway,giving the formula of roadway support parameters parameter quantitative. The same time, the research based on tunnel fall hidden dangers grading and the parameters design method of supporting, givingroof support parameter design examples of different surrounding rock level conditions anddifferent support mode.