397 results about "Rock tunnel" patented technology

The invention discloses a real-time surrounding rock deformation monitoring and data acquisition method and system, which is applied to long-distance weak surrounding rock tunnel construction, and comprises the following steps: determining the dynamic change trend of underground water seepage rate and ground stress distribution gradient by adopting a time sequence analysis method; based on the trend, carrying out risk partitioning on the tunnel construction section by adopting a K-means clustering algorithm, determining a deformation sensitive area, and optimizing the spatial distribution of the monitoring points according to the deformation sensitive area; monitoring data are acquired in real time, and when the data fluctuation period exceeds a threshold value, the data acquisition frequency of the corresponding monitoring point is automatically improved; processing high-frequency acquired data by adopting a long-short-term memory network to obtain a real-time surrounding rock deformation prediction result; the prediction result and the multi-source real-time geological parameters are fused, a Bayesian updating method is adopted for processing, a quantitative surrounding rock stability evaluation result is obtained, closed-loop self-adaptive optimization of a monitoring scheme and accurate risk prediction are achieved, and the safety early warning capacity of tunnel construction and the utilization efficiency of monitoring resources are remarkably improved.

The invention provides a soft rock tunnel surrounding rock parameter dynamic identification method and system based on data driving, and relates to the technical field of underground tunnel mechanical parameter dynamic identification, and the method comprises the steps: obtaining multi-element tunnel surrounding rock parameters, and building a joint probability distribution model of the multi-element surrounding rock parameters based on a Copula theory; performing Monte Carlo simulation, and generating a high-dimensional parameter sample library meeting physical constraints in the parameter constraint space based on the joint probability distribution model; establishing a tunnel three-dimensional numerical model and performing automatic numerical simulation to generate multivariate response data; constructing a Kriging agent model of a Gaussian kernel function based on multivariate response data training, establishing a nonlinear mapping relation between parameter input and deformation output, constructing an inversion objective function by taking the minimum root-mean-square error of multi-measurement-point displacement as an objective, and performing inversion solution by using an adaptive particle swarm optimization algorithm to obtain inversion identification parameters, and a dynamic feedback mechanism is constructed to realize adaptive tracking of the time-varying characteristics of the surrounding rock parameters.

The invention relates to the field of tunnel engineering geology and support design, and discloses a weak surrounding rock tunnel deformation risk discrimination method based on shear expansion-shear constitutive, which comprises the following steps: constructing a nonlinear coupling model between a shear expansion angle and shear stress, normal stress and joint parameters, and obtaining the shear expansion angle; establishing a volumetric strain rate discrimination formula; inverting an initial crustal stress tensor field; reconstructing an irregular tunnel boundary; constructing a risk level discrimination model, and outputting a risk level; supporting schemes such as supporting rigidity, anchor rod parameters and spraying layer thickness are matched according to the risk grades; establishing a model to predict a risk trend; a support adjustment suggestion is generated; collecting monitoring data to dynamically correct model parameters; and all the modules are integrated in a deployment system. According to the method, the coupling relation between the shear expansion angle and the shear strength is introduced, the coupling type constitutive discrimination model is established, the risk grading system and the support correction strategy associated with the support response are constructed, and active early warning of the high-risk section and dynamic adjustment of the support rigidity are achieved.

The invention relates to an intelligent soft rock tunnel surrounding rock deformation automatic monitoring and early warning system, and belongs to the field of tunnel construction safety monitoring. According to the system, multi-source data of surrounding rocks are synchronously acquired through a micron-sized laser displacement sensor, a fiber grating strain sensor, a pore water pressure sensor and a three-dimensional micro-seismic sensor array which are distributed; the edge calculation node fuses the data in real time and calculates the displacement rate, the strain gradient and the osmotic pressure coupling coefficient, and local early warning is triggered in combination with a dynamic threshold value; the cloud early warning platform predicts a deformation trend based on an LSTM-Transform fusion model, generates a multi-stage early warning signal through a risk grading engine, and is linked with the supporting equipment to regulate and control pressure; and meanwhile, a self-calibration device, an explosion-proof shell and a piezoelectric-thermal energy self-powered system are integrated. According to the method, closed-loop control from millimeter-level deformation sensing to active supporting can be achieved, and tunnel construction safety is remarkably improved.

The invention discloses a surrounding rock tunnel blasting dynamic simulation method, and belongs to the technical field of data simulation. The method comprises the following steps: acquiring three-dimensional geological data; constructing an initial mechanical parameter field of the surrounding rock based on the three-dimensional geological data; based on the initial mechanical parameter field, discretizing the surrounding rock area by adopting a finite element method, dividing grids and initializing mechanical attributes of each unit; based on the mechanical properties, blasting simulation is conducted, in the simulation process, the stress distribution state of the surrounding rock is monitored in real time, and whether the stress concentration phenomenon exists or not is judged; calculating a propagation path and an attenuation rate of a stress wave generated by explosive explosion in the surrounding rock through numerical simulation based on a judgment result; based on the propagation path and attenuation rate of the stress wave, the fracture mode and fragment distribution characteristics of the surrounding rock are analyzed; and obtaining a final blasting simulation result based on the stress distribution state, the fracture mode and the fragment distribution characteristics of the surrounding rock. The method can reflect the dynamic response of the surrounding rock and predict the blasting effect.

The invention discloses a soft rock tunnel pre-grouting reinforcement treatment method and equipment, and relates to the technical field of soft rock tunnel grouting reinforcement. Drilling operation is conducted on a tunnel face of a soft rock tunnel in a preset construction area so that a plurality of grouting holes distributed at intervals can be formed in the tunnel face, and a grouting pipe is installed in each grouting hole; and grouting equipment is sequentially communicated with the grouting pipes, grouting operation is conducted on the corresponding grouting holes through the grouting pipes, so that the piston nails in all the grout outlet holes are pushed to be anchored to the hole walls of the grouting holes, and grouting reinforcement operation is completed. Anchoring and connection with a geologic body on a tunnel face are achieved through the arranged grouting pipe and the piston nail installed in the grout outlet hole in the grouting pipe, the contact area between the grouting pipe and the geologic body can be increased through cooperation of the arranged grouting pipe and the piston nail, and the contact area between a grouting reinforcing body and the geologic body is increased; the strength of the geologic body is improved, the deformation trend of the geologic body is reduced, and the grouting reinforcement effect on the soft rock tunnel is improved.

The invention provides a spatial variability soft rock tunnel deformation prediction method based on deep learning, and belongs to the technical field of tunnel deformation prediction, and the method comprises the steps: constructing a surrounding rock parameter database, and determining the optimal edge distribution of different surrounding rock parameters through employing an akaike information criterion; constructing a reference value initial model, and generating a related standard uniformly distributed random field; performing equal probability transformation on the correlation standard uniformly distributed random field to generate a cross-correlation non-Gaussian distributed random field; encoding the data matrix of the non-Gaussian distribution random field into a parameter field image; and performing soft rock tunnel deformation prediction on the parameter field image by adopting a trained deformation prediction model. According to the method, parameter independent hypothesis limitation is broken through, the multi-parameter coupling space variability is accurately represented, and the prediction precision is remarkably improved.

The invention relates to the technical field of data monitoring, and discloses a soft rock tunnel continuous deformation optical fiber sensor monitoring system, which comprises a monitoring point identification module, a data acquisition module, a deformation probability analysis module, a target monitoring data acquisition module and a continuous deformation monitoring result generation module, identifying a monitoring point corresponding to a tunnel feature region in the three-dimensional tunnel model; monitoring data and image data corresponding to the monitoring points are collected according to the initial angle and the initial collection frequency of the optical fiber sensor, data fusion is carried out, and the deformation probability of the fused data is analyzed; performing adaptive adjustment on the angle and the acquisition frequency according to the deformation probability, and acquiring target monitoring data corresponding to the monitoring point according to the adaptively adjusted angle and acquisition frequency; and determining a deformation trend corresponding to the monitoring point according to the target monitoring data and the monitoring data, and generating a continuous deformation monitoring result of the soft rock tunnel according to the deformation trend. According to the invention, the accuracy of soft rock tunnel continuous deformation monitoring can be improved.

The invention discloses a construction method for going out of a hole of an ultra-shallow buried large-section soft rock tunnel, and relates to the technical field of tunnel construction.The construction method comprises the steps that a guide wall is constructed on a stratum where a hole to be formed is located, and a guide structure is buried in the guide wall; constructing a tunnel portal supporting structure on the stratum where the tunnel portal is located along the guide structure; concrete is poured into the first grouting pipes, so that a primary pipe shed supporting structure is formed; the tunnel face of the tunnel is excavated towards the hole opening to the position away from the hole opening by a first preset distance; a three-step method is adopted to excavate the tunnel to the position away from the portal by a second preset distance, and an upper step tunnel face, a middle step tunnel face and a lower step tunnel face are formed; a small pilot tunnel is excavated in the tunnel face of the upper step towards the portal until the tunnel is communicated with the outside; according to the method, the possibility of collapse of the ultra-shallow-buried large-section soft rock tunnel in the out-of-hole process can be reduced.

The invention discloses a soft rock tunnel deformation monitoring method, and relates to the technical field of tunnel construction.A target image set of a soft rock tunnel is obtained by carrying out photography and video recording on the soft rock tunnel subjected to excavation construction, and then a three-dimensional digital reference model of the soft rock tunnel is established according to the target image set; continuously carrying out photography and video recording operation on the soft rock tunnel to obtain a current image set corresponding to each acquisition moment, importing the current image set into the unit digital reference model, and comparing and analyzing the current joint trend with the joint trend model to obtain the current displacement of the geologic body; and finally, the deformation monitoring result of the soft rock tunnel is obtained according to the current displacement, so that the deformation condition of the geologic body of the soft rock tunnel can be identified in a photographing and video recording mode, a sensor does not need to be installed in the geologic body of the excavated and formed soft rock tunnel, and the monitoring cost is reduced.

The invention discloses a soft rock tunnel overexcavation backfill method, and relates to the technical field of tunnel construction.The soft rock tunnel overexcavation backfill method comprises the steps that a three-dimensional live-action image in a tunnel is scanned; establishing a three-dimensional live-action model according to the three-dimensional live-action image; establishing a digital twin model of the tunnel according to a design drawing; carrying out geometric intersection on the three-dimensional live-action model and the digital twin model to obtain geometric parameters of an overexcavation area; a concrete mold is subjected to 3D printing according to the geometric parameters of the overexcavation area; concrete is poured into the concrete mold, and a backfill body is formed; and the backfill body is backfilled to the overexcavation area. Due to the fact that the formed backfill body is tightly attached to the tunnel wall of the overexcavation area, the backfill precision is effectively improved, the construction quality is improved, the stability and the bearing capacity of the inner wall of the tunnel are enhanced, potential safety hazards are reduced, the concrete backfill work amount can be accurately controlled, the construction cost is reduced, and material waste is avoided.

The invention relates to the technical field of tunnel engineering safety prevention and control, and provides a gypsum rock tunnel water disaster risk evaluation and prevention and control scheme selection method which comprises the following steps: step 1-3, based on parameters such as rock mass structural integrity, stratum karst development degree, water yield property, groundwater corrosivity, gypsum rock mineral composition, expansibility and corrosion property, establishing a grading evaluation system, dividing corresponding grades and determining influence indexes R1-R8; 4, adopting an AHP method, an entropy weight method and a CRITIC method to perform multi-dimensional weight calculation on the subjectivity, objectivity and conflict influence indexes, correcting abnormal weights in combination with expert experience and verification rules, generating a comprehensive score, dividing risk grades, and matching graded prevention and control measures; and 5, optimizing and adjusting prevention and control measures in real time through a parameter risk level dynamic judgment and construction method matching mechanism. According to the method, multi-source parameter dynamic empowerment can be fused, and a full-life-cycle prevention and control method with accuracy, timeliness and self-adaptability is provided for tunnel engineering.

The invention discloses a dynamic early warning method and system for soft rock tunnel extrusion large deformation catastrophe, and the method comprises the steps: building a soft rock tunnel surface reference model, carrying out the point cloud registration, updating the soft rock tunnel surface model, recognizing a deformation mode, adjusting a deformation mode threshold value, carrying out the apparent dynamic early warning, and carrying out the multi-scale compensation. Constructing a Bayesian catastrophe prediction network based on a control-state coupling mechanism to obtain a large-deformation dynamic catastrophe index, adjusting a threshold value of the large-deformation dynamic catastrophe index to perform internal dynamic early warning, performing multiple regression to obtain a damage mapping relation set, constructing a deformation feature vector, and performing dynamic early warning; and constructing a dangerous event prediction model based on semi-supervised learning, obtaining a dangerous event prediction result in combination with the destruction mapping relation set, and performing event dynamic early warning. The method not only can improve the precision of dynamic early warning of the soft rock tunnel extrusion large deformation catastrophe, but also has good interpretability, and can be directly applied to a dynamic early warning system of the soft rock tunnel extrusion large deformation catastrophe.

The invention mainly relates to the technical field of underground engineering safety, and provides a tunnel rockburst pretreatment method and system based on multi-physics field parameters while drilling in order to improve the rockburst risk recognition and pressure relief effect through the multi-physics field parameters in the deep hard rock tunnel drilling process. The core of the method is that a surrounding rock three-dimensional geologic model is established based on multi-source physical field parameters in the surrounding rock while-drilling process; establishing a rockburst risk index prediction model of the surrounding rock three-dimensional geologic model based on an improved D-S evidence theory to calculate a rockburst risk index; and determining simulated pressure relief parameters according to the rockburst risk indexes, performing simulated pressure relief, judging whether the change rate of the multi-source physical field parameters meets the set requirements or not, if so, performing pressure relief according to the simulated pressure relief parameters, otherwise, re-determining the pressure relief parameters, and performing pressure relief until the change rate of the multi-source physical field parameters meets the set requirements.

The invention relates to the technical field of tunnel supporting, in particular to a self-expanding pipe shed advance supporting system for a weak water-rich surrounding rock tunnel, which comprises a tunnel face stability identification module, a grouting effect extraction module, a component supporting adaptation module, a pipe shed expansion execution module and a surrounding rock instability early warning module. According to the method, a particle loose section is identified through the change trend of the void ratio of the tunnel face and the contact pressure, the waterstop coverage integrity is analyzed by combining the multi-dimensional comparison of the grouting diffusion range and the permeation speed, and the component adaptability is judged by extracting the anchoring depth of the component and the joint state information according to the design requirement; and the confining pressure change rate before and after expansion is collected to recognize a section with insufficient supporting force and mark a position needing to be processed, a tunnel face stability threshold value is constructed according to the displacement rate and the crack growth trend, accurate early warning of a risk section is achieved, and a supporting control closed loop integrating recognition, verification, adaptation, intervention and early warning is constructed.

The invention discloses a design method for anti-erosion tunnel parameters. The design method comprises the steps that tunnel environment information and a tunnel safety index range are acquired; determining a catastrophe risk of the tunnel based on the tunnel environment information; determining a tunnel structure parameter range based on the catastrophe risk of the tunnel; determining tunnel structure parameters based on the tunnel structure parameter range; determining tunnel safety indexes based on the tunnel structure parameters; and determining or adjusting tunnel structure parameters based on a comparison result of the tunnel safety index and the tunnel safety index range. According to the design method of the anti-erosion tunnel parameters, blindness and randomness of composite corrosion and erosion surrounding rock tunnel structure parameter values are avoided, the tunnel rigidity and durability are effectively guaranteed, and the later tunnel structure degradation risk is reduced.

The invention relates to small-section rock tunnel construction integrated equipment and a construction method. The small-section rock tunnel construction integrated equipment comprises a heading machine, a spraying mechanism, a supporting mechanism and a transport vehicle, wherein the spraying mechanism and the supporting mechanism are carried on a heading machine vehicle body, and the transport vehicle corresponds to a slag outlet of a cantilever type heading device. The concrete wet spraying device and the anchor rod drilling device are carried on the upper portion of the cantilever type heading machine body, and uninterrupted continuous operation of tunneling, deslagging and supporting can be achieved by reasonably arranging the positions and the operation sequence of the concrete wet spraying system, the anchor rod drilling device, the deslagging vehicle and the concrete mixer truck. And meanwhile, participation of constructors is effectively reduced, manpower is saved, and the efficiency and safety of tunnel construction are improved.

The utility model relates to the field of tunnel construction, and discloses a pipe following structure of a shallow-buried weak surrounding rock tunnel advanced pipe shed, which comprises a bottom frame, a left vertical plate and a right vertical plate are respectively arranged at two ends of the top surface of the bottom frame, a moving plate is arranged between the left vertical plate and the right vertical plate, and a sleeve is arranged between the moving plate and the right vertical plate in a penetrating manner; first connecting plates are arranged on the outer walls of the four sides of the moving plate, threaded rods are arranged at the two ends of each first connecting plate in a penetrating mode, arc-shaped plates are connected to the bottom ends of the threaded rods through bearings, second connecting plates are arranged on the outer walls of the four sides of the right vertical plate, side plates are arranged on the outer walls of the two sides of each second connecting plate, and a rolling wheel is connected between every two opposite side plates through a shaft rod; a knob is arranged at the top end of the threaded rod; the problems that the rock mass void ratio is high, rock soil collapses, and hole forming is not easy can be solved, one-time drilling and pipe laying are adopted, the pipe pushing work after hole drilling is omitted, the hole forming speed is high, operation is easy, construction is convenient, the work rate is high, and the construction cost is saved.

The invention discloses a deep learning-based large deformation prediction method for a high ground stress soft rock tunnel, and belongs to the field of tunnel engineering geological disaster prediction. By constructing a double-branch network architecture of'geological mode identification-deep learning prediction ', accurate prediction of large deformation of the tunnel is realized. The method comprises the following steps: firstly, collecting six qualitative indexes such as a rock mass structure, a weathering degree and an underground water condition and three quantitative indexes such as a strength-stress ratio, support rigidity and an equivalent hole diameter, performing encoding and normalization preprocessing, and respectively inputting the indexes into an upper-layer network and a lower-layer network; outputting probability distribution of six types of modes prone to large deformation, such as a weak homogeneous type mode and a block crack structure type mode; and the lower layer predicts the deformation and divides risk levels through a full-connection neural network based on the geological mode identification result and the quantitative index. According to the method, the complex coupling mechanism of large deformation of the high-crustal-stress soft rock tunnel can be fully reflected; adaptability prediction is realized for different geological modes.

The present invention relates to the technical field of soft rock tunnel support, and particularly relates to a yielding filling support structure for soft rock tunnels and a construction method. This structure is obtained by constructing according to this method. This method includes obtaining in-situ stress data, rock stratum mechanical data, and surrounding rock deformation data; when the surrounding rock deformation data exceeds the deformation threshold, locking the surrounding rock deformation area and the amount of excavation enlargement through model simulation; increasing the length of the corresponding step according to the amount of excavation enlargement and reducing the height of the corresponding step; installing bolts to seal the surrounding rock surface; laying steel arch frames; reserving injection holes at the top of the surrounding rock deformation area, injecting filling materials to form a yielding filling layer; and spraying concrete again on the surrounding rock contour surfaces corresponding to each step to form an initial support structure. The present invention can ensure the safety of tunnel construction and operation when the deformation of soft rock tunnels is large and lasts for a long time, and reduce the construction cost and workload.

The invention relates to the technical field of electric digital data processing, in particular to a soft rock tunnel blasting simulation analysis method, system, equipment and medium, firstly, a three-dimensional model is constructed based on soft rock tunnel face information, and an area containing a plurality of vertical blast holes is selected on the lower portion of one side of a face to serve as a sub-model; then, trend line fitting is carried out on the tensile stress peak value of the detection point position through the sub-model under the condition of different proportions of the charge amount to the free surface area, and an empirical curve between the corresponding charge amount and the tensile stress peak value is obtained; the area proportion of the free surface to be processed is combined with the obtained empirical curve, the conditions meeting the requirements in the detection points are screened, finally, the minimum value of the explosive charge is taken, the blasting requirement is met, the construction cost is controlled, meanwhile, the blasting effect is guaranteed, and explosive waste is prevented.

The invention discloses a full-anchoring anchor rod structure for mine roadway supporting, belongs to the technical field of roadway supporting, and aims to solve the problems that an anchor rod cannot be limited after being inserted into an anchor hole and is easy to move, and the stability of anchor rod supporting is influenced. Under the limiting action of a sliding groove, when the rotating pipe rotates, a fixing rod can be pushed to slide in the sliding groove under the action of a first hinge column, a second hinge column and a hinge rod, and the fixing rod slides towards the outer end of the sliding groove by controlling the rotating direction of the rotating pipe; at the moment, the three sets of fixing rods extrude the inner side wall of the anchor hole, the anchor rod can be stably fixed to the middle of the anchor hole, the anchor rod does not shift when grouting is conducted on the anchor rod, the stability of the anchor rod during grouting is improved, and the supporting quality of the anchor rod can be improved; meanwhile, the contact area between the anchor rod and the anchor hole can be increased through the fixing rod after follow-up grouting is completed, and the stability of the anchor rod for supporting the soft rock roadway is further improved.

The invention provides a deep learning grading prediction method and system based on hard rock tunnel surrounding rock large deformation. The method comprises the steps of collecting characteristic data of a target tunnel project in a preset time period, performing processing to obtain multiple groups of same test data sets, performing processing through multiple different preset prediction models according to the test data sets, and obtaining multiple groups of corresponding grading prediction results, performing comparison processing on the multiple groups of grading prediction results and an actual grading prediction result to obtain multiple groups of corresponding prediction deviation rate data, screening out a preset prediction model set meeting requirements, obtaining real-time characteristic data of the target tunnel engineering, performing processing through the preset prediction model set to obtain a corresponding grading prediction result set, and performing classification prediction on the real-time characteristic data of the target tunnel engineering. And processing to obtain a final grading prediction result, obtaining a corresponding risk grade according to the final grading prediction result, and responding to a corresponding plan, thereby realizing a deep learning grading prediction technology based on the large deformation of the surrounding rock of the hard rock tunnel.

The present application discloses a small-turn compact open-type full-section rock tunnel boring machine, comprising: a main beam equipped with a main drive and a support shoe propulsion system capable of driving the main drive to move; a rear supporting system equipped with a second anchor drilling system capable of performing anchor support; a cutterhead equipped in front of the main drive, the main drive capable of driving the cutterhead to rotate; a slag discharge system capable of conveying rock slag equipped in the cutterhead; a shield capable of adhering to the tunnel wall equipped around the main drive; a first anchor drilling system capable of performing anchor support and an advance drilling system capable of drilling and grouting reinforcement in front of the cutterhead equipped around the support shoe propulsion system; and a rear support capable of holding the tunnel wall tight. The above-mentioned small-turn compact open-type full-section rock tunnel boring machine has a compact main beam structure, shortens the total length of the main beam, and enables the rock tunnel boring machine to adapt to small-turn rock tunnel excavation, thereby improving the scope of application of the rock tunnel boring machine.

The invention relates to a soft rock tunnel quick reloading mechanical abrasion cutting construction method, and mainly relates to a temporary inverted arch template system, a steel frame temporary upright support, a steel arch quick extension technology, a cyclic utilization prefabricated grout stop wall and an advanced jet grouting pile construction platform. The structure mainly comprises a tunnel primary lining, an inverted arch, an inverted arch template, a steel trestle, a temporary upright support, a steel frame, a tunnel face, an advanced jet grouting pile and the like. According to the abrasion cutting construction method for the soft rock tunnel rapid reloading machine, a more scientific and reasonable solution is provided for construction of the soft rock hydraulic tunnel, and positive contributions are made for promoting development of hydraulic engineering construction.

A comprehensive monitoring and handling method for a destruction region after an extremely strong time-delayed rockburst occurs, which method relates to the technical field of deep-underground hard-rock tunnel engineering. By means of providing micro-seismic monitoring systems in a destruction region of an extremely strong time-delayed rockburst, carrying out a crustal stress test (1), an acoustic wave test and borehole imaging (2), and blasting vibration monitoring of the surface and interior of surrounding rock, and performing long-term disturbance stress monitoring on the destruction region of the extremely strong time-delayed rockburst. Therefore, with regard to the aftermath of an extremely strong time-delayed rockburst, the monitoring efficiency is improved, and a rational and effective support system is established, thereby ensuring later-stage safety.

The invention belongs to the technical field of underground gas storage, and particularly relates to an energy-storage and hydrogen-storage modified asphalt slip layer for an underground rock cave and a preparation method of the energy-storage and hydrogen-storage modified asphalt slip layer. The modified asphalt slip layer disclosed by the invention has a lubricating effect, and can promote interlayer slip between structures and reduce the friction resistance of the contact surface of the concrete lining and the steel lining, so that the tensile stress of the steel lining is reduced, and the fatigue damage of the steel lining of a sealing layer caused by frequent inflation and deflation is relieved. Wherein through the modification of the styrene-butadiene-styrene block copolymer, the slippage layer has higher durability; the long-fiber polyester felt base cloth and the talcum powder are used, so that the thickness of the slip layer is increased and can reach 5-6 mm; and the viscosity of the slip layer is increased by using the hot melt adhesive, so that the slip layer can be quickly adhered to a structure to realize quick construction. An effective solution is provided for reducing fatigue damage and deterioration of the sealing layer steel lining and guaranteeing the sealing performance of the underground rock tunnel energy storage and hydrogen storage facility, and the method is suitable for large-scale application and popularization.

The invention discloses a tunnel forepoling method suitable for soft rock geology, and relates to the technical field of soft rock tunnel construction.The tunnel forepoling method suitable for the soft rock geology comprises the steps that surrounding rock of the soft rock geology corresponding to a tunnel is divided into a core reinforcing layer, a transition buffer layer and a peripheral protection layer along the excavation contour line of the tunnel; performing grouting reinforcement on the core reinforcement layer, the transition buffer layer and the peripheral protection layer to form an advance support surface; constructing a cross anchoring network by utilizing the forepoling surface; and a stress monitoring system is installed through the forepoling face, and tunnel forepoling construction of the soft rock geology is completed. The surrounding rock is divided into the core reinforcement layer, the transition buffer layer and the peripheral protection layer for differential grouting reinforcement, and the cross anchoring network is constructed to cooperatively control the shear slippage of the structural surface, so that the construction safety of the soft rock tunnel is improved.

The invention discloses a graded blasting construction method for a shallow-buried soft rock tunnel sensitive section. The method comprises the steps that measuring points are arranged in a tunnel chamber, a ground surface non-cavity section and a cavity section, and blasting vibration data are obtained; peak vibration velocity prediction models are established in a partitioned mode, an attenuation model is adopted in a chamber, a correction term is introduced into a non-cavity section of the earth surface to correct the attenuation model, and a multivariable model is established for the cavity section through dimensional analysis by integrating the horizontal distance, the elevation difference, the explosive quantity, the rock mass density and the tensile strength; determining a ground surface vibration velocity safety threshold, and quantifying a cavity vibration velocity amplification coefficient and an influence range thereof; based on the peak vibration velocity probability distribution and a preset safety level, establishing a safe dose prediction model and a safe range model; and dividing control areas according to the model, and implementing graded construction. According to the method, the vibration propagation law can be accurately described, the cavity amplification effect can be quantified, dynamic prediction of the blasting safety explosive quantity and range is achieved, and disturbance of blasting vibration to surrounding rock is effectively controlled through hierarchical management and control.

The present application relates to a kind of large section deep soft rock tunnel combined support system and construction method, the present application is combined with elastic shell theory and equivalent section method, a steel arch frame-grating combined support mode suitable for deep large section soft rock tunnel is proposed, the support rigidity of simply using steel arch frame or grid steel frame is overcome or supported, the disadvantage of lower in long-term large deformation unfavorable surrounding rock stability and deformation control, solve the problem that the stress of existing support structure is larger, the self-bearing capacity of surrounding rock cannot be fully exerted, cause material waste is serious, the safety factor of support structure is low, difficult to guarantee the stability of tunnel, and provide a simple and practical construction method for tunnel excavation and support.