Tunnel dynamic design method based on forepoling deformation

Abstract

The invention discloses a tunnel dynamic design method based on advance support deformation, which relates to the technical field of engineering data processing, and comprises the following steps: adjusting a current support scheme by using a pre-trained particle swarm optimization algorithm; in the construction process, monitoring points are arranged, monitoring data are collected in real time, an alarm value is constructed according to the collected monitoring data, and after an early warning level is determined according to the alarm value and a set alarm threshold value, corresponding emergency response measures are taken; dynamically adjusting the loose circle by combining real-time monitoring data, and continuously updating according to the construction process and the monitoring data; the loose circle range monitored in real time is compared with an initial design value, a deviation coefficient is generated, whether the supporting strength needs to be adjusted or not is judged, and supporting measures are added or supporting parameters are dynamically optimized through a multi-objective optimization algorithm. By dynamically adjusting support parameters, surrounding rock deformation is effectively controlled, risks caused by insufficient support are avoided, and the construction process is more flexible and controllable.

Description

Technical Field

[0001] The invention relates to the technical field of engineering data processing, in particular to a tunnel dynamic design method based on advanced support deformation. Background Art

[0002] With the advancement of transportation infrastructure construction in western my country, tunnel projects, especially tunnel projects that pass through soft surrounding rocks, are increasing. Tunnels with soft surrounding rocks often face safety risks such as large deformation and collapse due to poor geological conditions, low surrounding rock strength, and untimely support, which seriously affect the construction progress, quality and surrounding environment. During tunnel construction, surrounding rock deformation is one of the important factors affecting construction safety and economy. Although the existing New Austrian Tunneling Method has proposed the principle of "less disturbance, early support, frequent measurement, and tight closure", the surrounding rock monitoring is mainly concentrated in the excavated areas such as arch crown settlement and peripheral displacement, ignoring the advanced core soil deformation monitoring of the surrounding rock in front of the face.

[0003] The construction of tunnel projects usually involves complex surrounding rock and support design issues. During tunnel excavation, the stability of the surrounding rock directly affects the safety and construction progress of the project. The loose zone of the surrounding rock (i.e., the area where the surrounding rock is damaged or deformed) is a key factor affecting tunnel safety and support design. In order to ensure the smooth progress of tunnel construction, engineers need to adjust the support plan according to the dynamic changes of the surrounding rock to deal with possible problems such as surrounding rock damage, displacement and deformation. Traditional support design is usually based on empirical formulas or a single numerical simulation, which is difficult to fully and accurately reflect the actual situation of the surrounding rock. Therefore, combining a variety of detection methods and advanced numerical simulation technology to achieve more accurate loose zone assessment and support design optimization has become a technical challenge that needs to be solved in tunnel engineering.

[0004] In the Chinese invention patent with the authorization announcement number CN114329701B, a design method for buffer layer support of large deformation tunnel is provided, which is used to propose a specific structural scheme of buffer layer support of large deformation tunnel under the condition of considering the yield stress, yield amount and energy absorption characteristics, and provide accurate and effective data support for the design of buffer layer support of deformation tunnel. The method includes: obtaining the ultimate bearing capacity of the secondary lining structure corresponding to the buffer layer support of the target large deformation tunnel; screening out the second candidate filling material whose termination stress of the yield stage is less than the ultimate bearing capacity of the secondary lining structure; screening out the target candidate filling material whose sum of energy absorption in the elastic stage and energy absorption in the yield stage is the maximum as the filling material of the buffer layer support of the target large deformation tunnel; obtaining the required yield deformation of the buffer layer support of the target large deformation tunnel; determining the thickness of the buffer layer support of the target large deformation tunnel according to the required yield deformation and the yield stage termination strain of the target candidate filling material.

[0005] The existing tunnel excavation support design methods have great limitations, which are mainly reflected in two aspects. First, the traditional loose zone estimation method relies on empirical formulas. Although it can provide a preliminary design reference, it is difficult to accurately consider the dynamic changes of the surrounding rock during the actual construction process, resulting in insufficient accuracy of the support scheme. Second, the existing support design adjustment method mainly relies on manual judgment and manual optimization, which is inefficient and lacks a real-time feedback mechanism, and cannot adjust the support design in time according to the progress of construction.

[0006] To this end, the present invention provides a tunnel dynamic design method based on advanced support deformation. Summary of the invention

[0007] 1. Technical issues to be solved

[0008] In view of the shortcomings of the prior art, the present invention provides a tunnel dynamic design method based on advanced support deformation, which adjusts the current support scheme by using a pre-trained particle swarm optimization algorithm; during the construction process, monitoring points are arranged and monitoring data is collected in real time, and an alert value is constructed from the collected monitoring data. After the warning level is determined based on the alert value and the set alert threshold, corresponding emergency response measures are taken; the loosening circle is dynamically adjusted in combination with real-time monitoring data, and continuously updated according to the construction progress and monitoring data; the loosening circle range monitored in real time is compared with the initial design value, a deviation coefficient is generated, and it is determined whether the support strength needs to be adjusted, including adding support measures or dynamically optimizing support parameters through a multi-objective optimization algorithm. By dynamically adjusting the support parameters, the surrounding rock deformation is effectively controlled, the risks caused by insufficient support are avoided, and the construction process is made more flexible and controllable. A dynamic loosening circle evaluation method based on multiple monitoring technologies and three-dimensional numerical simulation is combined with a particle swarm optimization algorithm to optimize the support scheme, so that the dynamic changes of the surrounding rock and the support design can be matched in real time, and the safety and economy of the support can be optimized.

[0009] (II) Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: a tunnel dynamic design method based on advanced support deformation, including using multiple detection methods to collect geological detection data of surrounding rocks, preliminarily estimating the range of the loosening zone in combination with empirical formulas, analyzing the surrounding rock deformation during excavation through three-dimensional numerical simulation, and outputting a two-dimensional cross-sectional diagram or a three-dimensional spatial distribution diagram of the initial surrounding rock loosening zone;

[0011] After matching the corresponding support scheme according to the estimated loose circle range, the surrounding rock displacement control value is used as the optimization constraint condition, and the construction safety and economy are used as the optimization goals. The pre-trained particle swarm optimization algorithm is used to adjust the current support scheme.

[0012] During the construction process, monitoring points are set up and monitoring data is collected in real time. The warning value V is constructed based on the collected monitoring data.final , according to the warning value V final After determining the warning level with the set warning threshold, take corresponding emergency response measures;

[0013] Dynamically adjust the loosening zone in combination with real-time monitoring data. Based on the adjusted loosening zone range, use the inversion model to calculate the dynamic loosening zone distribution of the surrounding rock, draw a two-dimensional profile distribution map or a three-dimensional model of the loosening zone, and continuously update it according to the construction progress and monitoring data;

[0014] Compare the real-time monitored loose circle range with the initial design value to generate the deviation coefficient D total And determine whether the support strength needs to be adjusted, including adding support measures or dynamically optimizing support parameters through a multi-objective optimization algorithm.

[0015] Furthermore, geological radar detection is used to detect and identify fracture concentration areas through reflected signals, core samples obtained through drilling are used to determine the rock mass mechanical parameters, and in-hole imaging technology is used to collect distribution data of joints and fractures;

[0016] Detect changes in the surrounding rock and geological structure in front of the tunnel and collect seismic detection data; after merging the groundwater distribution data, use the seismic imaging method to generate a three-dimensional geological structure map of the surrounding rock from the geological detection data.

[0017] Furthermore, according to the characteristics of different surrounding rock types, empirical formulas are used to estimate the initial surrounding rock loosening zone; the rock mass mechanical parameters of the surrounding rock are input, and after pre-setting the boundary conditions, a three-dimensional numerical model is used to simulate the excavation process of the tunnel section, and the corresponding simulated excavation data is obtained after applying the influence of initial support.

[0018] Furthermore, the principal stress distribution diagram of the surrounding rock and the range data of the plastic zone are extracted, and the empirical formula results and the numerical simulation output are compared. If the deviation is greater than expected, the estimation results of the loosening zone are iteratively optimized;

[0019] The support layout parameters are matched according to the estimated initial loose zone depth and distribution range, the loose zone distribution is integrated with the support layout parameters, and the coverage range and key parameters of the support design are marked.

[0020] Furthermore, at the beginning of construction, monitoring points are arranged according to the tunnel section size, the determined construction method and the geological conditions, and the monitoring equipment array periodically collects monitoring data and records the time, location and initial state of the deformation data, including,

[0021] Point displacement of tunnel surrounding rock and support, deformation data of the entire section of the tunnel, internal strain change data of anchor rods, steel frames and shotcrete, local strain data and surface settlement data.

[0022] Furthermore, after collecting and analyzing monitoring data, including surrounding rock displacement, support deformation and surface settlement data, the warning value V is generated according to the following method: final :

[0023]

[0024] Where: W h is the horizontal displacement weight matrix, U is the displacement vector, W s is the support deformation rate weight matrix, is the support deformation rate vector, W d is the sedimentation rate weight matrix, is the surface settlement rate vector; σ(R(t)) is the surrounding rock stress tensor, which represents the stress state of the surrounding rock at different times t. σ(R(t)) is the surrounding rock stress tensor, which represents the stress state of the surrounding rock at different times t. is the stress divergence.

[0025] Furthermore, if the warning value V final If the value V is lower than the first warning threshold, no additional processing is performed; if the warning value V final Between the first and second warning thresholds, strengthen monitoring density and support intensity; if the warning value V final If the level is higher than the second warning threshold, stop excavation and add support measures.

[0026] Furthermore, the real-time monitoring data, including support displacement data, support strain data, and settlement data, are combined; according to the increment of the real-time monitoring data, the adjusted empirical formula is used to update the range of the loosening zone;

[0027] The adjusted dynamic loosening zone range is used as the initial condition of the inversion model, and the relevant parameters in the inversion model are adjusted in combination with the surrounding rock classification, rock mechanical parameters and monitoring data of the construction stage; the dynamic depth and expansion range of the surrounding rock loosening zone are obtained by correcting the calculation results through real-time data based on the loosening zone distribution model of stress inversion.

[0028] Furthermore, on the basis of obtaining the initial surrounding rock loosening zone, the deviation coefficient D is generated after obtaining the actual depth, distribution range and expansion rate of the current surrounding rock loosening zone. total , as follows:

[0029]

[0030] Where: R current (t,x,y) represents the real-time loose circle depth at time t and position (x,y), R initial(x, y) is the depth of the initial design loose zone, dV is the spatial volume element, representing the volume integral of the entire construction area; dt is the time integral element, representing the time span of the construction progress.

[0031] Furthermore, adjustment measures are determined based on the deviation coefficient: if the obtained deviation coefficient is greater than the design value, the support strength should be increased, such as adding anchors and thickening the shotcrete; if the obtained deviation coefficient is less than the design value, the support layout is optimized, the cost is reduced, and optimization instructions are issued to the outside; after receiving the optimization instruction, the support specification parameters are optimized using the pre-trained multi-objective optimization algorithm; the dynamically adjusted support specification parameters are output, including anchor layout parameters, shotcrete thickness and strength grade, steel frame spacing and model.

[0032] (III) Beneficial effects

[0033] The present invention provides a tunnel dynamic design method based on advanced support deformation, which has the following beneficial effects:

[0034] 1. The output 2D cross-section diagram, 3D distribution diagram and displacement contour lines of the loosening zone range can provide support for support design and construction process adjustment; according to the distribution of the plastic zone volume and the main stress concentration area, the construction footage and support sequence can be optimized to reduce construction risks.

[0035] 2. By simulating the deformation of the surrounding rock during excavation through a three-dimensional numerical model, the expansion range and depth of the loose zone can be accurately predicted, providing an accurate basis for support design; the role of dynamic simulation support can help optimize the initial support design and ensure that the surrounding rock remains stable during excavation; by comparing the simulation results with the estimated values ​​of the empirical formula, the prediction accuracy of the loose zone can be tested and the support design can be adjusted in time.

[0036] 3. According to the horizontal and vertical extension range of different loose circles, adjust the support parameters, such as anchor length, spacing, shotcrete thickness, etc., to ensure that the support measures are fully matched with the loose circles. By adjusting the support design, especially increasing the density of support in stress concentration areas, the safety of support measures can be effectively enhanced.

[0037] 4. By setting up monitoring points at different locations, the deformation of surrounding rock and supporting structure can be fully monitored to detect potential risks in advance; the warning value V is generated through monitoring data final By comparing with the set warning threshold, abnormal deformation of the surrounding rock can be discovered in time. Through real-time monitoring and rapid emergency response, construction risks can be reduced.

[0038] 5. The loosening circle range can be dynamically adjusted through real-time monitoring data, so that the loosening circle can more accurately reflect the deformation of the surrounding rock during construction. According to the dynamic adjustment of the loosening circle, it can be evaluated in real time whether the support design is sufficient to cover the loosening circle, and the support design can be adjusted in time to avoid failure of the support system.

[0039] 6. By using the real-time updated loosening zone range as the initial condition of the inversion model, the calculation results can be corrected to ensure that the inversion model reflects the actual deformation of the surrounding rock. Through stress inversion calculation, the dynamic loosening zone range of the surrounding rock can be accurately predicted, providing more reliable data support for support design. The support design parameters are dynamically adjusted according to the inversion results to ensure that the support scheme is fully matched with the loosening zone range and improve the support effect.

[0040] 7. By comparing the real-time loosening circle with the initial design value, it is possible to determine whether support needs to be strengthened based on the deviation coefficient, adjust the support strength in time, optimize the support design and reduce construction costs. By dynamically adjusting the support parameters, the deformation of the surrounding rock can be effectively controlled to avoid the risks caused by insufficient support. Through the optimization algorithm, the support design can be dynamically adjusted according to real-time data and construction progress, making the construction process more flexible and controllable. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic flow chart of the tunnel dynamic design method based on advanced support deformation of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] See also Figure 1 The present invention provides a tunnel dynamic design method based on advanced support deformation.

[0044] Step 1: Use a variety of detection methods to collect geological detection data of surrounding rocks, combine empirical formulas to preliminarily estimate the range of the loose zone, analyze the surrounding rock deformation during excavation through three-dimensional numerical simulation, and output a two-dimensional cross-sectional diagram or a three-dimensional spatial distribution diagram of the initial surrounding rock loose zone;

[0045] The step 1 includes the following contents:

[0046] Step 101: Use geological radar to detect and identify fracture concentration areas through reflected signals;

[0047] The core samples obtained through drilling are used to measure the rock mechanical parameters of the rock mass, such as rock strength σc, density ρ and elastic modulus E, and the distribution data of joints and cracks, such as crack density and azimuth, are collected through in-hole imaging technology;

[0048] Use the propagation characteristics of seismic waves to detect changes in the surrounding rock and geological structure in front of the tunnel, and collect seismic detection data such as longitudinal wave velocity, shear wave velocity, wave velocity ratio, seismic wave amplitude attenuation and seismic reflection coefficient;

[0049] The acquired rock mass mechanical parameters, faults, cracks, seismic detection data and groundwater distribution data are summarized to generate a geological detection data set; through seismic imaging methods such as velocity inversion, waveform inversion and full wave field modeling, a three-dimensional geological structure map of the surrounding rock is generated from the geological detection data; at this time, the three-dimensional geological model generated by wave velocity inversion can intuitively display the stratification, faults, cracks and water-bearing areas of the surrounding rock in front of the tunnel.

[0050] It should be noted that the advanced seismic wave method sends seismic waves inside the tunnel by applying artificial seismic sources (such as explosion sources, hammer sources, vibration sources), and records the propagation time, amplitude and attenuation characteristic data of seismic waves in the surrounding rock through receivers; among them, longitudinal waves (P waves): mainly reflect the density and elastic modulus of the rock mass, and are sensitive to groundwater distribution and weak zones; transverse waves (S waves): reflect the shear strength of the rock mass, and can better identify fault fracture zones and weak surrounding rocks;

[0051] Furthermore, the source position is usually set at the tunnel face or close to the tunnel face to ensure that the seismic waves can cover the advanced detection range. The source form is usually an explosion source, a hammer source or a directional vibration source, and the appropriate form is selected according to the tunnel depth and rock properties.

[0052] Receiver arrays are arranged along the tunnel wall to form a linear or planar acquisition layout. Depending on the tunnel scale and accuracy requirements, the receiver spacing is usually 0.5-1 meter. The number of receivers arranged determines the accuracy of seismic wave detection, and the density needs to be increased in weak surrounding rock areas. After the source is excited, the receiver records the time, waveform and amplitude changes of the seismic waves propagating from the source to different parts of the surrounding rock. To ensure sampling accuracy, the sampling frequency is usually 10 times the main frequency of the seismic wave.

[0053] Step 102: according to the characteristics of different surrounding rock types (such as self-stabilization time and loose zone development law), an empirical formula (such as an empirical formula for the depth of the loose zone) is used to estimate and obtain the initial surrounding rock loose zone, wherein the empirical formula includes an empirical formula based on the surrounding rock coefficient, a formula based on the surrounding rock strength and stress, and a time model for the depth of the loose zone;

[0054] Empirical formula for self-stabilization time: Where: k is the surrounding rock coefficient, σmax is the maximum principal stress of the surrounding rock, L is the tunnel span; the formula for the depth of the loose zone is: d = k·H; where: d is the depth of the loose zone (m), H is the tunnel excavation height (m), and k is the surrounding rock coefficient, which depends on the surrounding rock type; the time model of the loose zone depth, formula: d(t) = d0 + v d ·t; where: d is the initial loose zone depth (m); Ua is the loose zone expansion rate (m / day); t is time (day);

[0055] Input the rock mass mechanical parameters of the surrounding rock, including elastic modulus E, Poisson's ratio ν, compressive strength, cohesion c and internal friction angle φ, etc. After presetting the boundary conditions, the actual ground stress field and tunnel excavation load are applied, the top boundary is a free boundary, and the bottom boundary and side wall boundary are set with constraint conditions; a three-dimensional numerical model is used to simulate the excavation process of the tunnel section, and commonly used software includes FLAC3D, ABAQUS, PLAXIS, etc.; the influence of initial support (such as shotcrete, anchors, etc.) is applied during the excavation process to obtain the corresponding simulated excavation data;

[0056] The range of the loosening zone estimated by the empirical formula (such as the initial expansion range in the horizontal and vertical directions) can be used as an input reference for the three-dimensional numerical model to set reasonable boundary conditions and preliminary excavation parameters. The results of the empirical formula can also be used to verify the output accuracy of the three-dimensional numerical simulation and provide a basis for the subsequent determination of the range of the loosening zone.

[0057] Step 103: simulate the dynamic process of tunnel excavation in the three-dimensional numerical model. In the excavation stage, a step-by-step loading method is adopted, that is, the ground stress of the surrounding rock is gradually released according to the construction progress. At the same time, initial support (such as anchors and shotcrete) is dynamically applied, and the influence of the timeliness of the initial support on the range of the loosening circle is considered.

[0058] The input parameters of simulated excavation include the physical and mechanical properties of the surrounding rock and the distribution of the ground stress field, and the initial excavation range is determined by combining the preliminary estimated values ​​of the empirical formula;

[0059] The extracted surrounding rock principal stress distribution diagram and plastic zone range data can be used to verify whether the loosening zone range estimated by the empirical formula in step 102 is accurate, and compare the empirical formula results with the numerical simulation output (such as horizontal expansion distance, vertical expansion distance and plastic zone volume). If the existing deviation is greater than expected, it is necessary to adjust the three-dimensional numerical model parameters (such as initial stress field, surrounding rock strength index, etc.) and re-simulate to iteratively optimize the estimation result of the loosening zone;

[0060] In the three-dimensional numerical model, the principal stress distribution diagram of the surrounding rock is extracted and the stress concentration area is analyzed to obtain the horizontal displacement, vertical displacement and total displacement field distribution of the surrounding rock; the Mohr-Coulomb yield criterion is used to determine whether the surrounding rock has entered a plastic state. If the shear stress τ of the surrounding rock exceeds the shear strength, the area is regarded as a plastic zone, and the range of the plastic zone is output as a reference for the loosening zone;

[0061] The 2D cross-sectional diagram or 3D spatial distribution diagram of the initial surrounding rock loosening zone is output from the 3D numerical model, and the plastic zone range, displacement contour lines reflecting the deformation amplitude of the surrounding rock, and the principal stress distribution diagram are marked in the diagram; among which, the main parameters of the loosening zone range include the maximum expansion distance dh in the horizontal direction, the maximum expansion distance dv in the vertical direction, and the volume Vp of the plastic zone;

[0062] When using, combine the contents in steps 101 to 103:

[0063] The output 2D cross-section diagram, 3D distribution diagram and displacement contour lines of the loosening zone can provide support for support design and construction process adjustment; for example, according to the maximum horizontal and vertical expansion distances of the loosening zone, support parameters such as anchor arrangement spacing and shotcrete thickness can be dynamically adjusted; according to the distribution of the plastic zone volume and the main stress concentration area, the construction footage and support sequence can be optimized to reduce construction risks.

[0064] By combining the empirical formula with the physical and mechanical parameters of the surrounding rock, the preliminary estimated range of the loosening zone can be quickly obtained, which is convenient for the preliminary planning of the support design: the results of the empirical formula are used as the input reference of the three-dimensional numerical model to verify the accuracy of the numerical simulation and adjust the support design according to the actual situation: based on the estimated range of the loosening zone, the support design can preliminarily match the range of the loosening zone to ensure the stability of the support system.

[0065] By simulating the deformation of the surrounding rock during excavation using a three-dimensional numerical model, the expansion range and depth of the loosening zone can be accurately predicted, providing an accurate basis for support design; the role of dynamic simulation support (such as anchors, shotcrete, etc.) can help optimize the initial support design and ensure that the surrounding rock remains stable during excavation; by comparing the simulation results with the estimated values ​​of the empirical formula, the prediction accuracy of the loosening zone can be tested and the support design can be adjusted in a timely manner.

[0066] Step 2: After matching the corresponding support scheme according to the estimated loose circle range, the surrounding rock displacement control value is used as the optimization constraint condition, and construction safety and economy are used as the optimization goals. The pre-trained particle swarm optimization algorithm is used to adjust the current support scheme;

[0067] The step 2 includes the following contents:

[0068] Step 201, matching the support layout parameters according to the estimated initial loose circle depth and distribution range, including the length, spacing, number of anchor rods, thickness and strength of shotcrete, type of steel frame and layout spacing, etc.; for example, the support design needs to be closely matched with the loose circle range: the anchor rod length should be 1.2-1.5 times the loose circle depth, the anchor rod spacing is dynamically adjusted according to the uniformity of the loose circle distribution, and the spacing is reduced in the stress concentration area (such as from 1.5m to 0.8m);

[0069] The thickness of shotcrete is calculated as 10% to 15% of the depth of the loosening zone, and the support coverage exceeds the extension range of the loosening zone by at least 20% to 30% to improve support safety; the spacing of steel frames is adjusted in combination with the tunnel section size and surrounding rock type, and the steel frames are densely arranged in areas with larger loosening zones;

[0070] In the two-dimensional profile diagram, the loosening zone distribution (such as stress contours and plastic zone range) is integrated with the support layout parameters, and the coverage and key parameters of the support design are marked to ensure that the layout range of anchor rods, shotcrete and steel frames completely covers the loosening zone, and highlight the changes in support parameters in different areas (such as arranging denser supports in stress concentration areas).

[0071] According to the horizontal and vertical extension range of different loose circles, the support parameters, such as anchor length, spacing, shotcrete thickness, etc., are adjusted to ensure that the support measures are fully matched with the loose circles. By adjusting the support design, especially increasing the density of support in stress concentration areas, the safety of support measures can be effectively enhanced. Under different surrounding rock conditions, the support parameters can be flexibly adjusted to cope with different deformation and stress states of the surrounding rock.

[0072] Step 202: In combination with the tunnel section size, with improving economy and safety as the optimization goal, with the loosening zone range parameter as input, the current support scheme is optimized using the pre-trained particle swarm optimization algorithm, with the surrounding rock displacement control value as the optimization constraint condition, and the optimal support parameter combination is output, including anchor spacing, concrete thickness, and steel frame spacing, etc.; wherein the surrounding rock displacement control value generally refers to the maximum allowable value of the horizontal displacement, vertical displacement, and total displacement of the surrounding rock during the tunnel or underground excavation process. The displacement control value not only involves the direct deformation of the surrounding rock, but is also closely related to the bearing capacity, construction safety, and structural stability of the support system;

[0073] When using, combine the contents in steps 201 and 202:

[0074] The support parameters are automatically adjusted through the particle swarm optimization algorithm, so that the support design can meet the safety requirements and achieve economic optimization. By optimizing the support scheme, the construction cost can be reduced and the construction efficiency can be improved while ensuring safety. The optimization algorithm can be used to reduce manual intervention, realize the intelligence and automation of support design, and improve the design accuracy and execution effect.

[0075] Step 3: Set up monitoring points during the construction process and collect monitoring data in real time, and construct the warning value V based on the collected monitoring data. final , according to the warning value V final After determining the warning level with the set warning threshold, take corresponding emergency response measures;

[0076] The step three includes the following contents:

[0077] Step 301: At the beginning of construction, monitoring points are arranged according to the tunnel section size, the determined construction method and the geological conditions. The monitoring points should cover the front of the tunnel face, the tunnel vault, the side wall and the tunnel periphery. The monitoring equipment array periodically collects monitoring data and records the time, position and initial state of the deformation data, including:

[0078] The point displacement of the tunnel surrounding rock and support is accurately measured using a total station, which is arranged in a stable position outside the tunnel face, and a reflective prism is installed at the monitoring point; a laser scanner is used to obtain deformation data of the entire tunnel section, and optical fiber sensors are used to monitor the internal strain changes of anchor rods, steel frames and shotcrete. The optical fiber sensors are buried in the key stress-bearing parts of the support structure;

[0079] The resistance strain gauge is installed on the steel frame or anchor surface to collect local strain data, and the positioning module is used to monitor the surface settlement in real time over a wide area. The base station and monitoring points are distributed above the construction area and surrounding buildings.

[0080] Use a level to accurately monitor ground settlement, with monitoring points arranged along the tunnel axis, usually at intervals of 10-30m;

[0081] Summarize the collected point displacements of tunnel surrounding rock and support, deformation data of the entire section of the tunnel, internal strain change data of anchors, steel frames and shotcrete, local strain data, and surface settlement data;

[0082] By deploying monitoring points at different locations, the deformation of surrounding rock and support structure can be fully monitored, potential risks can be discovered in advance, and precise instruments (such as total stations, laser scanners, fiber optic sensors, etc.) can be used to accurately monitor the deformation of surrounding rock and support structure, providing accurate data support for subsequent decision-making;

[0083] Step 302: After collecting and analyzing monitoring data, including surrounding rock displacement, support deformation and surface settlement data, a warning value V is generated according to the following method:final :

[0084]

[0085] Where: W h is the horizontal displacement weight matrix, which indicates the importance of the horizontal displacement of different monitoring points in the comprehensive warning value. The elements of the matrix reflect the contribution of each monitoring point to the overall system displacement. U is the displacement vector, which indicates the horizontal displacement data (such as surrounding rock displacement) of each monitoring point. The data is collected by monitoring equipment (such as total station, laser scanner, etc.) and reflects the surrounding rock deformation during tunnel construction. s is the support deformation rate weight matrix, which indicates the weight of the support deformation rate in the warning value. Different support structures (such as anchors, steel frames, shotcrete, etc.) have different influences on the deformation rate. The weight matrix is ​​used to weight these rate data. is the support deformation rate vector, which indicates the deformation rate of the support structure (such as anchor rods, steel frames, etc.), which is monitored in real time by deformation sensors such as optical fiber sensors and strain gauges, reflecting the working status of the support system; W d is the settlement rate weight matrix, which indicates the weight of the surface settlement rate in the warning value. The settlement rates at different monitoring points may have different impacts on safety. The weight matrix is ​​used to weight the settlement rate data. is the surface settlement rate vector, which indicates the rate of surface settlement. It is collected by settlement monitoring equipment (such as level, surface settlement meter, etc.) and reflects the surface deformation during the construction process. σ(R(t)) is the surrounding rock stress tensor, which indicates the stress state of the surrounding rock at different times t. The stress tensor takes into account the anisotropy of the surrounding rock and different types of stress (such as axial stress, shear stress, etc.). σ(R(t)) is the surrounding rock stress tensor, which indicates the stress state of the surrounding rock at different times t. The stress tensor takes into account the anisotropy of the surrounding rock and different types of stress (such as axial stress, shear stress, etc.). Stress divergence: It represents the spatial variation of stress in the surrounding rock. The divergence operation reflects the diffusion of stress in space, which is related to the evolution of the loose zone of the surrounding rock and the stress transfer during the excavation process;

[0086] According to historical data and management expectations of the construction status, the first and second warning thresholds are pre-set, wherein the second warning threshold is higher than the first warning threshold;

[0087] If the warning value V final If it is below the first warning threshold, no additional processing will be performed;

[0088] If the warning value V final Between the first and second warning thresholds, the intensity of monitoring and support efforts should be strengthened;

[0089] If the warning value Vfinal If the water level is higher than the second warning threshold, stop excavation immediately and add support measures. Then adjust the construction plan, such as shortening the excavation advance, increasing the length or number of anchor rods, thickening the shotcrete, adding small advance guide tubes, etc.

[0090] When using, combine the contents in steps 301 and 302:

[0091] Generate warning value V through monitoring data final By comparing with the set warning threshold, abnormal deformation of the surrounding rock can be discovered in time to ensure construction safety. Through real-time monitoring and rapid emergency response, construction risks can be reduced and catastrophic accidents can be avoided. By discovering and dealing with deformation problems in advance, accidents caused by excessive deformation during construction can be avoided, ensuring the smooth progress of the construction process.

[0092] Step 4: Dynamically adjust the loosening zone in combination with real-time monitoring data. Based on the adjusted loosening zone range, use the inversion model to calculate the dynamic loosening zone distribution of the surrounding rock, draw a two-dimensional profile distribution map or a three-dimensional model of the loosening zone, and continuously update it according to the construction progress and monitoring data;

[0093] The step 4 includes the following contents:

[0094] Step 401: Combined with real-time monitoring data, including support displacement data: monitoring the displacement of support structures (such as anchors, shotcrete, steel frames, etc.) to reflect the deformation degree of surrounding rock and support structure; support strain data: monitoring the strain changes of surrounding rock and support structure through strain gauges or optical fiber sensors to obtain the stress condition of surrounding rock; settlement data: monitoring the settlement of surrounding rock and tunnel floor to reflect the compaction or loosening of surrounding rock;

[0095] According to the increment of real-time monitoring data (displacement, strain, settlement, etc.), the adjusted empirical formula is used to update the range of the loosening zone; the adjusted depth and extension range of the loosening zone should reflect the deformation of the surrounding rock and support in the current construction process. For example, the displacement increment and strain increment can be used to adjust the depth and extension range of the loosening zone:

[0096] The displacement control formula is as follows: h (t) = d h0 +k v ·Δu;d v (t) = d v0 +k v Δu;

[0097] Where: d h (t), d v (t) are the horizontal and vertical extension depths of the loose circle at the current moment; d h0 ,d v0is the initial loose zone depth, Δu is the displacement increment monitored in real time, k T is the relaxation coefficient of the surrounding rock material, which can be calibrated through test data; the strain control formula is as follows:

[0098] d h (t) = d h0 ·(1+Δε / ε y )

[0099] Where: Δε is the monitored strain increment of the surrounding rock, ε y is the yield strain of surrounding rock;

[0100] The loosening zone range is dynamically adjusted through real-time monitoring data (displacement, strain, etc.), so that the loosening zone can more accurately reflect the deformation of the surrounding rock during construction. According to the dynamic adjustment of the loosening zone, it is possible to evaluate in real time whether the support design is sufficient to cover the loosening zone, so as to adjust the support design in time to avoid failure of the support system;

[0101] Step 402: using the dynamic loosening zone range adjusted in step 401 (such as horizontal extension depth and vertical depth updated in real time) as the initial condition of the inversion model, and adjusting the relevant parameters in the inversion model in combination with surrounding rock classification, rock mass mechanical parameters and monitoring data in the construction stage (such as support displacement, surrounding rock deformation, etc.);

[0102] Based on the loosening zone distribution model of stress inversion, the dynamic depth and extension range of the surrounding rock loosening zone are obtained by correcting the calculation results with real-time data. The two-dimensional profile distribution map or three-dimensional model of the loosening zone is drawn using the inversion results, and is continuously updated according to the construction progress and monitoring data to show the extension range and change trend of the loosening zone;

[0103] After outputting the loose zone distribution map, the inversion results are verified by the following methods:

[0104] Compare with monitoring data: compare the inversion results (such as plastic zone range, principal stress distribution) with the monitored displacement field and strain field distribution to verify whether the inversion results are reasonable;

[0105] Comparison with numerical simulation results: Compare and calibrate the inversion results with the simulation results of the three-dimensional numerical model (such as FLAC3D, ABAQUS) to ensure model consistency;

[0106] Feedback to support design: According to the changing trend of the loosening zone range (such as expansion rate, range increment), dynamically optimize support parameters (such as increasing anchor rod length, adjusting shotcrete thickness, etc.).

[0107] When using, combine the contents in steps 401 and 402:

[0108] By using the real-time updated loosening zone range as the initial condition of the inversion model, the calculation results can be corrected to ensure that the inversion model reflects the actual deformation of the surrounding rock. Through stress inversion calculation, the dynamic loosening zone range of the surrounding rock can be accurately predicted, providing more reliable data support for support design. The support design parameters can be dynamically adjusted according to the inversion results to ensure that the support scheme is fully matched with the loosening zone range and improve the support effect.

[0109] Step 5: Compare the real-time monitored loose circle range with the initial design value to generate the deviation coefficient D total And determine whether the support strength needs to be adjusted, including adding support measures or dynamically optimizing support parameters through a multi-objective optimization algorithm;

[0110] The step five includes the following contents:

[0111] Step 501: compare the real-time loose zone range with the initial design value, wherein, based on the initial surrounding rock loose zone, the actual depth, distribution range and expansion rate of the current surrounding rock loose zone are obtained and the deviation coefficient D is generated. total , as follows:

[0112]

[0113] Where: R current (t,x,y) represents the real-time loose circle depth at time t and position (x,y), R initial (x, y) is the depth of the initial design loose zone, usually a spatial field, indicating the range of the loose zone during design; dV is the spatial volume element, indicating the volume integral of the entire construction area; dt is the time integral element, indicating the time span of the construction progress;

[0114] Determine adjustment measures based on the deviation coefficient: if the obtained deviation coefficient is greater than the design value, the support strength should be increased, such as adding anchor rods and thickening shotcrete; if the obtained deviation coefficient is less than the design value, optimize the support layout and reduce costs, and issue optimization instructions to the outside;

[0115] Step 502: After receiving the optimization instruction, the support specification parameters are optimized using a pre-trained multi-objective optimization algorithm with the improvement of safety and economy as the optimization goals; the dynamically adjusted support specification parameters are output, including anchor arrangement parameters (length, spacing and quantity, etc.), shotcrete thickness and strength grade, steel frame spacing and model;

[0116] When using, combine the contents in steps 501 and 502:

[0117] By comparing the real-time loose circle with the initial design value, it is possible to determine whether support needs to be strengthened based on the deviation coefficient and adjust the support strength in time to ensure construction safety.total If it is smaller than expected, the support design can be optimized, unnecessary support materials can be reduced, and thus the construction cost can be reduced;

[0118] Through the multi-objective optimization algorithm, safety and economy can be considered at the same time, and support parameters can be optimized under the premise of ensuring construction safety, thereby improving project efficiency. By dynamically adjusting support parameters, surrounding rock deformation can be effectively controlled to avoid risks caused by insufficient support. Through the optimization algorithm, the support design can be dynamically adjusted according to real-time data and construction progress, making the construction process more flexible and controllable.

[0119] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0120] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0121] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only some logical function divisions. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A tunnel dynamic design method based on advanced support deformation, characterized by: include, Use a variety of detection methods to collect geological detection data of surrounding rocks, combine empirical formulas to preliminarily estimate the range of the loose zone, analyze the surrounding rock deformation during excavation through three-dimensional numerical simulation, and output a two-dimensional cross-sectional diagram or three-dimensional spatial distribution diagram of the initial surrounding rock loose zone; After matching the corresponding support scheme according to the estimated loose circle range, the surrounding rock displacement control value is used as the optimization constraint condition, and the construction safety and economy are used as the optimization goals. The pre-trained particle swarm optimization algorithm is used to adjust the current support scheme. During the construction process, monitoring points are set up and monitoring data is collected in real time. The warning value V is constructed based on the collected monitoring data. final , according to the warning value V final After determining the warning level with the set warning threshold, take corresponding emergency response measures; Dynamically adjust the loosening zone in combination with real-time monitoring data. Based on the adjusted loosening zone range, use the inversion model to calculate the dynamic loosening zone distribution of the surrounding rock, draw a two-dimensional profile distribution map or a three-dimensional model of the loosening zone, and continuously update it according to the construction progress and monitoring data; Compare the real-time monitored loose circle range with the initial design value to generate the deviation coefficient D total And determine whether the support strength needs to be adjusted, including adding support measures or dynamically optimizing support parameters through a multi-objective optimization algorithm.

2. The tunnel dynamic design method based on advanced support deformation according to claim 1 is characterized in that: Use geological radar to detect and identify fracture concentration areas through reflected signals, obtain core samples through drilling, measure rock mass mechanical parameters, and collect distribution data of joints and fractures through in-hole imaging technology; Detect changes in the surrounding rock and geological structure in front of the tunnel and collect seismic detection data; after merging the groundwater distribution data, use the seismic imaging method to generate a three-dimensional geological structure map of the surrounding rock from the geological detection data.

3. The tunnel dynamic design method based on advanced support deformation according to claim 2 is characterized in that: According to the characteristics of different surrounding rock types, the initial surrounding rock loosening zone is estimated using empirical formulas; the rock mass mechanical parameters of the surrounding rock are input, and after pre-setting the boundary conditions, a three-dimensional numerical model is used to simulate the excavation process of the tunnel section, and the corresponding simulated excavation data is obtained after applying the influence of the initial support.

4. The tunnel dynamic design method based on advanced support deformation according to claim 3 is characterized in that: The principal stress distribution diagram of the surrounding rock and the range data of the plastic zone are extracted, and the empirical formula results and numerical simulation output are compared. If the deviation is greater than expected, the estimation results of the loosening zone are iteratively optimized; The support layout parameters are matched according to the estimated initial loose zone depth and distribution range, the loose zone distribution is integrated with the support layout parameters, and the coverage range and key parameters of the support design are marked.

5. The tunnel dynamic design method based on advanced support deformation according to claim 4 is characterized in that: At the beginning of construction, monitoring points are arranged according to the tunnel section size, determined construction method and geological conditions. The monitoring equipment array periodically collects monitoring data and records the time, location and initial state of deformation data. include, Point displacement of tunnel surrounding rock and support, deformation data of the entire section of the tunnel, internal strain change data of anchor rods, steel frames and shotcrete, local strain data and surface settlement data.

6. The tunnel dynamic design method based on advanced support deformation according to claim 5 is characterized in that: After collecting and analyzing monitoring data, including surrounding rock displacement, support deformation and surface settlement data, the warning value V is generated according to the following method: final : Where: W h is the horizontal displacement weight matrix, U is the displacement vector, W s is the support deformation rate weight matrix, is the support deformation rate vector, W d is the sedimentation rate weight matrix, is the surface settlement rate vector; σ(R(t)) is the surrounding rock stress tensor, which represents the stress state of the surrounding rock at different times t. σ(R(t)) is the surrounding rock stress tensor, which represents the stress state of the surrounding rock at different times t. is the stress divergence.

7. The tunnel dynamic design method based on advanced support deformation according to claim 6 is characterized in that: If the warning value V final If the value V is lower than the first warning threshold, no additional processing is performed; if the warning value V final Between the first and second warning thresholds, strengthen monitoring density and support intensity; if the warning value V final If the level is higher than the second warning threshold, stop excavation and add support measures.

8. The tunnel dynamic design method based on advanced support deformation according to claim 7 is characterized in that: Combined with real-time monitoring data, including support displacement data, support strain data, and settlement data; based on the increment of real-time monitoring data, the adjusted empirical formula is used to update the range of the loosening zone; The adjusted dynamic loosening zone range is used as the initial condition of the inversion model, and the relevant parameters in the inversion model are adjusted in combination with the surrounding rock classification, rock mass mechanical parameters and monitoring data during the construction stage; Based on the loosening zone distribution model of stress inversion, the dynamic depth and extension range of the surrounding rock loosening zone are obtained by correcting the calculation results with real-time data.

9. The tunnel dynamic design method based on advanced support deformation according to claim 8 is characterized in that: On the basis of obtaining the initial surrounding rock loosening zone, the deviation coefficient D is generated after obtaining the actual depth, distribution range and expansion rate of the current surrounding rock loosening zone. total , as follows: Where: R current (t,x,y) represents the real-time loose circle depth at time t and position (x,y), R initial (x, y) is the depth of the initial design loose zone, dV is the spatial volume element, representing the volume integral of the entire construction area; dt is the time integral element, representing the time span of the construction progress.

10. The tunnel dynamic design method based on advanced support deformation according to claim 9 is characterized in that: Adjustment measures are determined based on the deviation coefficient: if the obtained deviation coefficient is greater than the design value, the support strength should be increased, such as adding anchor rods and thickening shotcrete; if the obtained deviation coefficient is less than the design value, the support layout is optimized, the cost is reduced, and optimization instructions are issued to the outside; after receiving the optimization instruction, the support specification parameters are optimized using the pre-trained multi-objective optimization algorithm; the dynamically adjusted support specification parameters are output, including anchor rod layout parameters, shotcrete thickness and strength grade, steel frame spacing and model.

Images