Method and system for optimizing thickness of shield tunnel roof under synchronous construction of subway tunnel station

Abstract

The invention belongs to the technical field of subway tunnel station synchronous construction, and discloses a shield tunnel roof thickness optimization method and system under subway tunnel station synchronous construction. The method comprises the steps that a three-dimensional numerical model is established, and multi-field coupling analysis of an explosive detonation JWL model, a rock mass dynamic response ALE method and a segment damage CSCM model is adopted; the vibration speed, the maximum tensile stress and the joint deformation index of the duct piece under different roof thicknesses are extracted; top plate thickness iterative optimization is carried out; and according to an iterative optimization result, verification and feedback are carried out in combination with field monitoring data. Structural safety is guaranteed by the dynamic damage threshold and the multi-index criterion. Probability optimization reduces redundant design, improves optimization efficiency and saves cost. Quick response is achieved under complex geological conditions, and construction reliability is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of synchronous construction of subway tunnels and stations, and particularly relates to a method and system for optimizing the thickness of the shield tunnel roof slab under synchronous construction of subway tunnels and stations. Background Technique

[0002] With the rapid development of urban rail transit, the synchronous construction technology of subway tunnels and stations has become a key means to improve construction efficiency and shorten the construction period. Due to its advantages such as small disturbance to the stratum and high degree of mechanization, the shield method is widely used in tunnel construction. However, during the synchronous construction of the station and the tunnel, the dynamic load generated by the blasting excavation of the upper rock mass will cause significant impact on the segment structure of the lower shield tunnel. If the design of the roof slab thickness is improper, it is extremely easy to cause segment cracking, joint leakage, and even structural instability. The traditional design of the roof slab thickness mostly relies on empirical formulas or static analysis, and it is difficult to accurately reflect the transient effect of the blasting dynamic load, resulting in conservative design or insufficient safety. In recent years, numerical simulation technologies (such as the finite element method and the discrete element method) have gradually been introduced into the field of tunnel engineering, but their application in the coupled analysis of blasting dynamic response and structural damage still has limitations.

[0003] In the prior art, certain progress has been made in the research on the response of tunnel structures under blasting loads. The existing numerical simulation technologies have not realized the multi-field coupling analysis of explosive detonation (JWL model), rock mass dynamic response (ALE method), and segment damage (CSCM model), and cannot accurately capture the blasting load transfer path and the structural damage evolution process; the existing safety assessments are mostly based on a single index (such as the maximum stress or vibration velocity), ignoring the dynamic damage threshold of concrete and the coordinated control of joint deformation, resulting in one-sided safety criteria; the existing methods do not combine on-site monitoring data to iteratively correct the numerical model, and the design results deviate greatly from the actual working conditions, making it difficult to adapt to complex geological conditions. Summary of the Invention

[0004] To overcome the problems existing in the related technologies, the disclosed embodiments of the present invention provide a method and system for optimizing the thickness of the shield tunnel roof slab under synchronous construction of subway tunnels and stations.

[0005] The technical solution is as follows: A method for optimizing the thickness of the shield tunnel roof slab under synchronous construction of subway tunnels and stations, including the following steps: S1, establish a three-dimensional numerical model according to the tunnel geological parameters, blasting parameters, and shield segment parameters; S2, based on the established three-dimensional numerical model, adopt the multi-field coupling analysis of the explosive detonation JWL model, the rock mass dynamic response ALE method, and the segment damage CSCM model; S3, according to the results of the multi-field coupling analysis, extract the vibration velocity, maximum tensile stress, and joint deformation indexes of the segments under different roof slab thicknesses; S4. Iteratively optimize the thickness of the top plate based on the vibration velocity, maximum tensile stress, and joint deformation index of the segments under different top plate thicknesses extracted; verify and provide feedback based on the iterative optimization results in combination with on-site monitoring data.

[0006] In step S1, establish a three-dimensional numerical model, including: Based on on-site surveys and the design and planning drawings of the tunnel and the station, clarify the geological parameters, blasting parameters, and segment parameters; According to the positions of the station excavation area, shield tunnel, surrounding rock mass, and explosion source, construct a geometric model of the dynamic response of the segment during drill-and-blast excavation under the condition of simultaneous construction of the tunnel and the station.

[0007] In step S2, the JWL model of explosive detonation uses the MAT-HIGH-EXPLOSIVE-BURN material model, and the JWL equation of state is used to calculate the detonation pressure. The JWL equation of state is as follows: ; In the formula, is the detonation pressure, are all material parameters, is the relative volume, is the internal energy per unit volume, is a constant; The air model uses the MAT-NULL material model, and the state is described by the linear polynomial equation of EOS-LINEAR-POLYNOMIAL. The expression is: ; In the formula, is the air constant, , is a dimensionless parameter, , is the density, is the density under standard conditions, is the internal energy of the material; Simplified to the ideal gas model as: ; In the formula, is the specific heat ratio, ; The JWL model of explosive detonation provides the law of energy release of the explosion source, and the air model simulates the propagation dynamics of the shock wave in the air. The JWL model of explosive detonation and the air model achieve the interaction of energy and momentum through the fluid-structure coupling method; The segment damage CSCM model includes compressive damage, tensile cracking, strain rate effect and stiffness degradation; the MAT_PLASTIC_KINEMATIC is used to simulate the steel bars, which are connected to the segments through co-nodes or CONTACT_TIE to ensure stress transfer; The JH-2 model is adopted for the rock mass, and the progressive failure process of the material is described through damage accumulation and strain rate effect; the ALE fluid model uses Eulerian grids, and the structural model uses Lagrangian grids, and the two are coupled by CONSTRAINED_LAGRANGE_IN_SOLID; Meshes are jointly divided for the station, tunnel, rock mass and air, and the mesh density at the fluid-solid interface is increased; Initial ground stress, non-reflective boundary conditions and solution controls are set.

[0008] In step S3, the vibration velocity, maximum tensile stress, and joint deformation indexes of the segments under different roof thicknesses are extracted, including: Perform spectral analysis on the vibration velocity at key positions to identify the main frequency components and analyze whether the vibration main frequency is close to the natural frequency of the segments; Output the principal stress nephogram of the segments through the segment damage CSCM model, and use LS-PrePost to identify the maximum tensile stress area and the stress peak values under each working condition; Monitor the normal displacement difference between the nodes on both sides of the segment joint to obtain the joint opening amount, and monitor the tangential displacement difference between the nodes on both sides of the segment joint to obtain the joint dislocation amount.

[0009] In step S4, iterative optimization of the roof thickness is carried out, including: Input parameters; Select the uncertain parameters as random variables, including elastic modulus , internal friction angle , single-hole explosive , distance from the explosion center , segment thickness ; Use the Latin hypercube sampling method to extract groups of samples, which are evenly distributed to cover the random variable space; Construct a Kriging meta-model, based on the sample points input their responses , and output the surrogate model; Use the Kriging meta-model to calculate the Sobol' index for sensitivity analysis to obtain the contribution degree of each parameter to the response; Adopt the Monte Carlo sampling method to extract groups, input them into the Kriging meta-model to calculate the tunnel failure probability; Draw the relationship curve between the safety roof thickness and the failure probability, and determine the critical safety roof thickness; multiply the critical thickness by the safety factor to obtain the final design thickness.

[0010] Furthermore, the Latin hypercube sampling method is used to extract groups of samples, which are uniformly distributed to cover the random variable space, including: For each parameter , its value range is divided into equi-probability intervals, and a sample point is randomly selected within each interval, and it is ensured that the sample points of each parameter do not have repeated combinations: ; In the formula, is the inverse function of the cumulative distribution function CDF of parameter , is the permutation serial number of the th sample in the th parameter dimension, is the random offset within the interval.

[0011] Furthermore, a Kriging meta-model is constructed. Based on the sample points input its response , and output the surrogate model, including: The Kriging model assumes that the response is a Gaussian process: ; In the formula, is the global mean, is a zero-mean Gaussian process; The covariance function is: ; In the formula, is the covariance function, is a zero-mean Gaussian process, is the variance of the Gaussian process, is the correlation function, and are the input points, are hyperparameters, which are optimized by the maximum likelihood estimation MLE; The correlation function of is: In the formula, is the dimension of the input space, is the dimension index, is the th dimension scaling parameter, is the th point's Dimensional value is the -th dimensional value of the

[0012] Furthermore, the Kriging meta-model is used to calculate the Sobol' index for sensitivity analysis to obtain the contribution degree of each parameter to the response, including: Total variance decomposition: ; In the formula, is the main effect variance of the -th parameter, is the interaction effect variance of the -th and -th parameters, and are the indexes of the input parameters, is the high-order interaction effect variance of all parameters; The total effect Sobol' index is: ; In the formula, is the variance after excluding the parameter .

[0013] Furthermore, the Monte Carlo sampling method is adopted to extract groups and input them into the Kriging meta-model to calculate the tunnel failure probability, including: Define the failure function: ; In the formula, is the allowable stress, is the maximum stress; Then the failure probability: ; In the formula, is the Monte Carlo sample number, is 1 when , otherwise 0.

[0014] Another object of the present invention is to provide a shield tunnel roof thickness optimization system under synchronous construction of subway tunnels and stations. This system implements the shield tunnel roof thickness optimization method under synchronous construction of subway tunnels and stations. This system includes: A three-dimensional numerical model establishment module, which is used to establish a three-dimensional numerical model according to tunnel geological parameters, blasting parameters and shield segment parameters; A multi-field coupling analysis module, which is used to perform multi-field coupling analysis based on the established three-dimensional numerical model, using the JWL model of explosive detonation, the ALE method of rock mass dynamic response and the CSCM model of segment damage; Index extraction module, used to extract the vibration velocity, maximum tensile stress, and joint deformation indexes of the segments under different roof thicknesses based on the results of multi-field coupling analysis; The roof thickness iterative optimization module is used to iteratively optimize the roof thickness according to the extracted vibration velocity, maximum tensile stress, and joint deformation indicators of the pipe segments under different roof thicknesses; verification and feedback are carried out based on the iterative optimization results combined with the on-site monitoring data.

[0015] In combination with all the above technical solutions, the beneficial effects of the present invention are as follows: First, the present invention introduces the ALE-Lagrange fluid-solid coupling technology for the first time in the design of the top plate thickness of the shield tunnel under the condition of synchronous construction of the tunnel station, accurately capturing the propagation path of the explosion shock wave in the rock mass and the dynamic response of the pipe segment; outputting dynamic damage evolution data through the CSCM model, combined with joint deformation monitoring, to form a multi-dimensional safety assessment system; identifying key parameters through Sobol' index sensitivity analysis, realizing the probabilistic design of the top plate thickness, and avoiding excessive reliance on the safety factor; combining field monitoring data feedback with parameter sensitivity analysis, improving the efficiency of model correction and shortening the design verification cycle.

[0016] Second, this optimization method realizes the dynamic optimization of the shield tunnel top plate thickness through multi-field coupling simulation, uncertainty quantification analysis and real-time feedback of field data, which directly promotes the safety, economy and efficiency upgrade of subway tunnel and station synchronous construction technology. Its core value is reflected in: Safety risks are controllable: dynamic damage threshold and multi-index criteria ensure structural safety.

[0017] Efficient resource allocation: Probabilistic optimization reduces redundant design, improves optimization efficiency, and saves costs.

[0018] Enhanced engineering adaptability: rapid response under complex geological conditions and improved construction reliability.

[0019] This technology can be widely used in similar engineering scenarios (such as mining tunnels) and has significant promotion value.

[0020] Third, the present invention significantly improves the accuracy and safety of shield tunnel roof thickness design by constructing a dynamic response analysis framework and a multi-parameter uncertainty quantification method, which can effectively reduce construction risks, reduce material waste and later maintenance costs, and improve the economy and construction efficiency of subway projects. Its technical achievements can be directly applied to urban rail transit construction, and have broad market prospects and industrialization potential.

[0021] The present invention combines the JWL detonation model, the CSCM damage model, the ALE fluid-structure coupling, and the Kriging meta-model to construct a full-process technical system covering dynamic response, failure probability analysis, and optimization design, filling the gap in structural safety assessment and thickness optimization under complex working conditions in this field.

[0022] Fourthly, traditional design methods are difficult to accurately predict the dynamic damage effect of blasting vibration on shield segments during synchronous construction and cannot take into account the comprehensive impact of multi-parameter uncertainties on the safety of the roof slab. Through dynamic simulation and probability analysis, the present invention for the first time realizes the quantitative correlation modeling of the roof slab thickness and the failure probability, solves the core problem that the coupling relationship among "dynamic disturbance - structural response - safety threshold" is difficult to quantify for a long time, and provides reliable technical support for the design of shield tunnels under complex geological conditions.

[0023] Fifthly, the present invention combines the JWL detonation model, the CSCM damage model, the ALE fluid-structure coupling, and the Kriging meta-model to establish a new technical path of "dynamic - probability - optimization", providing a certain reference for the design of the roof slab thickness of shield tunnels under the condition of synchronous construction of tunnels and stations. Brief Description of the Drawings

[0024] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure; Figure 1 It is a flow chart of the method for optimizing the roof slab thickness of a shield tunnel under synchronous construction of a subway tunnel and a station provided by an embodiment of the present invention. Detailed Embodiments

[0025] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention will be given with reference to the drawings. Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0026] The innovation of the present invention lies in: by constructing a dynamic response model integrating the JWL detonation model, the CSCM damage model, and the ALE fluid-structure coupling, and combining the uncertainty quantification method of the Latin hypercube - Kriging meta-model, the present invention realizes the accurate prediction of the failure probability of the roof slab under the coupling action of multi-parameters (such as elastic modulus, distance from the explosion center, segment thickness, etc.); based on sensitivity analysis and the failure probability curve, a multi-objective optimization design method for the roof slab thickness is proposed, taking into account both structural safety and construction economy, and effectively solving the complexity and uncertainty problems in the design of the roof slab thickness of shield tunnels under synchronous construction disturbances.

[0027] Example 1, as Figure 1 shown, the method for optimizing the thickness of the shield tunnel roof slab under the synchronous construction of the subway tunnel and station provided by the embodiment of the present invention includes the following steps: S1. Establish a three-dimensional numerical model according to the tunnel geological parameters, blasting parameters and shield segment parameters; S2. Based on the established three-dimensional numerical model, perform multi-field coupling analysis using the explosive detonation JWL model, the ALE method for rock mass dynamic response and the CSCM model for segment damage; S3. According to the results of multi-field coupling analysis, extract the vibration velocity, maximum tensile stress and joint deformation indexes of the segments under different roof slab thicknesses; S4. According to the vibration velocity, maximum tensile stress and joint deformation indexes of the segments under different roof slab thicknesses extracted, perform iterative optimization of the roof slab thickness; according to the iterative optimization results, verify and feedback in combination with the on-site monitoring data.

[0028] Exemplarily, in step S1, the specific steps for establishing the three-dimensional numerical model are as follows: Through on-site investigation and the design and planning drawings of the tunnel and the station, clarify the geological parameters, blasting parameters and segment parameters; According to the positions of the station excavation area, shield tunnel, surrounding rock mass and explosion source, construct a geometric model of the dynamic response of the segments under the synchronous construction conditions of the tunnel and the station by the drill-and-blast method.

[0029] Exemplarily, in step S2, the specific steps for performing multi-field coupling analysis using the explosive detonation JWL model, the ALE method for rock mass dynamic response and the CSCM model for segment damage are as follows: In the synchronous construction of the subway tunnel and the station, optimizing the thickness of the shield tunnel roof slab requires comprehensive consideration of the dynamic load of explosive blasting, the dynamic response of the rock mass and the damage evolution of the segment structure. The ALE method for rock mass dynamic response uses the fluid-structure coupling model ALE. By combining the explosive detonation JWL model, the fluid-structure coupling model ALE and the CSCM model for segment damage, multi-physical field coupling analysis can be realized to accurately predict the rock mass-segment interaction under blasting impact; The explosive detonation JWL model uses the MAT-HIGH-EXPLOSIVE-BURN material model and calculates the detonation pressure using the JWL equation of state. The JWL equation of state is as follows: ; In the formula, is the detonation pressure, are all material parameters, is the relative volume, is the internal energy per unit volume, is a constant; The air model adopts the MAT-NULL material model and describes the state using the linear polynomial equation of EOS-LINEAR-POLYNOMIAL: ; In the formula, is the air constant, , is a dimensionless parameter, , is the density, is the density under standard conditions, is the internal energy of the material; The segments of the shield tunnel adopt the MAT_CSCM_CONCRETE model, which is a concrete constitutive model based on the Continuous Surface Cap Model (CSCM), specifically used to simulate the complex mechanical behavior of concrete under dynamic loads, including compressive damage, tensile cracking, and strain rate effects. The MAT_PLASTIC_KINEMATIC is used to simulate the steel bars, which are connected to the segments through co-nodes or CONTACT_TIE to ensure stress transfer.

[0030] Tensile damage evolution: ; In the formula, is the tensile damage variable, is the tensile strain, is the tensile damage threshold, are all damage parameters; Compressive damage evolution: ; In the formula, is the tensile damage variable, is the tensile strain, is the tensile damage threshold, is the damage parameter; Strain rate effect correction: ; In the formula, is the strain rate correction factor, is the reference strain rate, is the strain rate parameter.

[0031] The rock mass adopts the JH-2 model. The core idea is to describe the progressive failure process of the material through damage accumulation and strain rate effects, which is especially suitable for simulating the fragmentation behavior of brittle rock masses such as granite under dynamic loads.

[0032] The ALE fluid model (explosion products, air) uses Eulerian grids, and the structural model (segment lining, rock mass) uses Lagrangian grids. The two are coupled by the CONSTRAINED_LAGRANGE_IN_SOLID method; Meshes are jointly divided for the station, tunnel, rock mass, and air, and the mesh density at the fluid-solid interface is increased; Initial ground stress, non-reflective boundary conditions, and solution controls are set; Exemplarily, in step S3, indices such as the vibration velocity, maximum tensile stress, and joint deformation of the segment lining under different roof thicknesses are extracted. The specific steps are as follows. Perform spectral analysis on the vibration velocity at key positions (such as the crown, haunch, and springing) to identify the dominant frequency components, and analyze whether the dominant vibration frequency is close to the natural frequency of the segment lining to avoid resonance risks; Arrange monitoring points at vulnerable parts such as the crown, haunch, and springing. Use *DATABASE_NODOUT to define the output of nodal velocity and output the vibration velocity data. Extract the velocity time-domain data through LS-PrePost, and then convert the time-domain data to the frequency domain through the fast Fourier transform in MATLAB to identify the dominant frequency.

[0033] Output the principal stress nephogram of the segment lining through the CSCM model of segment lining damage, and use LS-PrePost to identify the maximum tensile stress area and the stress peak values under each working condition; Monitor the normal displacement difference between the nodes on both sides of the segment lining joint to obtain the joint opening amount, and monitor the tangential displacement difference between the nodes on both sides of the segment lining joint to obtain the joint dislocation amount. (First, use CONTACT_SURFACE_TO_SURFACE in the model to define the contact surfaces on both sides of the joint, then configure the output control in the input file to record the displacement data of the nodes on both sides of the joint, and finally use the LS-PrePost post-processing tool to extract the nodal displacement data and calculate the difference.) Exemplarily, in step S4, the optimization iteration of the roof thickness is as follows. Input parameters; Select the uncertain parameters as random variables (elastic modulus , internal friction angle , single-hole explosive , distance from the explosion center , segment lining thickness ); Use the Latin hypercube sampling method to extract groups of samples, evenly covering the random variable space ( ). The sampling process is as follows. For each parameter (such as etc.), and its value range is divided into 𝑛 equally probable intervals. A sample point is randomly selected from each interval, and it is ensured that the sample points of each parameter do not form repeated combinations: ; In the formula, is the inverse function of the cumulative distribution function CDF of parameter , is the permutation serial number of the th sample in the th parameter dimension, is the random offset within the interval.

[0034] Construct a Kriging meta-model, input its response based on the sample points , and output a surrogate model, including: The Kriging model assumes that the response is a Gaussian process: ; In the formula, is the global mean, is a zero-mean Gaussian process; The covariance function is: ; In the formula, is the covariance function, is a zero-mean Gaussian process, is the variance of the Gaussian process, is the correlation function, and are input points, are hyperparameters, optimized by maximum likelihood estimation MLE; The correlation function of is: In the formula, is the dimension of the input space, is the dimension index, is the th scaling parameter of the th dimension, is the th value of the th point in the th dimension, is the

[0035] Use the Kriging meta-model to calculate the Sobol' index for sensitivity analysis to obtain the contribution degree of each parameter to the response. The process is as follows: Total variance decomposition: ; In the formula, is the main effect variance of the -th parameter, is the interaction effect variance of the -th and 𝑗-th parameters, and are the indices of the input parameters, is the variance of the high-order interaction effects of all parameters; The total effect Sobol' index is: ; In the formula, is the variance after excluding the parameter .

[0036] The process of extracting m groups by the Monte Carlo sampling method and inputting them into the Kriging meta-model to calculate the tunnel failure probability is as follows: Define the failure function: ; In the formula, is the allowable stress, is the maximum stress; Then the failure probability: ; In the formula, is the number of Monte Carlo samples, is 1 when , otherwise 0.

[0037] Draw the relationship curve between the safety roof thickness and the failure probability to determine the critical safety roof thickness; Considering the construction uncertainty, multiply the critical thickness by the safety factor to obtain the final design thickness.

[0038] Exemplarily, in step S4, the verification and feedback in combination with the on-site monitoring data include: Install piezoelectric accelerometers at the crown and haunches of the segment to measure the vibration velocity; (Correctly install the sensors, cooperate with the data acquisition system to collect the acceleration signal, and convert the acceleration signal into the velocity signal through integral operation: ; In the formula, is the velocity, is the acceleration.

[0039] Install vibrating wire strain gauges at the inner side of the crown and haunches of the segment to measure the actual strain and convert it into stress; (Record the initial frequency of the strain gauge in the unloaded state , read the real-time frequency through the strain gauge reading instrument , calculate the strain : ; In the formula, is strain, is the initial frequency, is the calibration coefficient; According to Hooke's law, the stress ; Linear displacement transducers (LVDTs) and wire-pull displacement transducers are installed at the circumferential joints and longitudinal joints of the segment to measure the joint opening and joint staggering; (LVDTs are installed in the vertical direction of the circumferential joints and longitudinal joints, and the initial voltage of the LVDT is recorded under the unloaded state. The voltage signal of the LVDT is read in real time through the data acquisition system and converted into a displacement value: ; In the formula, is the displacement, is the real-time voltage, is the initial voltage, is the sensitivity.

[0040] Wire-pull displacement transducers are installed in the horizontal direction of the circumferential joints and longitudinal joints. The initial length of the wire is recorded under the unloaded state. The change in the wire length is read through the data acquisition system to calculate the staggering: ; In the formula, is the staggering, is the real-time wire-pull amount, is the initial wire-pull amount.

[0041] If the error between the measured data and the simulation results is large, the parameters are optimized and recalculated according to the contribution degree of each parameter calculated by the Sobol' index to the response value.

[0042] Example 2. The shield tunnel roof thickness optimization system provided by the embodiment of the present invention includes: A three-dimensional numerical model establishment module, which is used to establish a three-dimensional numerical model according to the tunnel geological parameters, blasting parameters and shield segment parameters, and the tunnel is constructed synchronously with the tunnel station; A multi-field coupling analysis module, which is used to perform multi-field coupling analysis based on the established three-dimensional numerical model, using the explosive detonation JWL model, the ALE method for rock mass dynamic response and the CSCM model for segment damage; An index extraction module, which is used to extract the vibration velocity, maximum tensile stress and joint deformation indexes of the segment under different roof thicknesses according to the multi-field coupling analysis results; The top plate thickness iterative optimization module is used to perform iterative optimization of the top plate thickness according to the vibration velocity, maximum tensile stress, and joint deformation index of the segment under different top plate thicknesses extracted; verify and provide feedback by combining the iterative optimization results with on-site monitoring data.

[0043] The present invention has been successfully applied to a certain under-construction subway in Qingdao. By integrating the JWL detonation model, CSCM damage model, and ALE fluid-structure coupling, it can accurately simulate the dynamic damage effect of blasting vibration on the shield segment during synchronous construction; adopt the Latin hypercube-Kriging meta-model to systematically analyze the coupling effects of parameters such as elastic modulus, distance from the blast center, and segment thickness, significantly reducing the risk of structural failure caused by parameter randomness and improving design reliability; based on the failure probability curve and sensitivity analysis, achieve multi-objective optimization of the top plate thickness, avoid over-design or under-design, and shorten the design period by 5%-10%.

[0044] The above is only a relatively preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention by those skilled in the art within the technical scope disclosed by the present invention shall be covered by the protection scope of the present invention.

Claims

1. An optimization method for the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations, characterized in that, The method includes the following steps: S1. Establish a three-dimensional numerical model based on tunnel geological parameters, blasting parameters, and shield segment parameters; S2. Based on the established three-dimensional numerical model, conduct multi-field coupling analysis using the explosive detonation JWL model, the ALE method for rock mass dynamic response, and the CSCM model for segment damage; S3. According to the results of the multi-field coupling analysis, extract the vibration velocity, maximum tensile stress, and joint deformation index of the segments under different roof thicknesses; S4. Perform iterative optimization of the roof thickness based on the extracted vibration velocity, maximum tensile stress, and joint deformation index of the segments under different roof thicknesses; according to the results of the iterative optimization, verify and feedback in combination with on-site monitoring data.

2. The optimized method for the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations according to claim 1, characterized in that In step S1, when establishing the three-dimensional numerical model, it includes: Through on-site investigation and the design and planning drawings of the tunnel and the station, clarify the geological parameters, blasting parameters, and segment parameters; According to the positions of the station excavation area, shield tunnel, surrounding rock mass, and explosion source, construct a geometric model of the dynamic response of the segments during drill-and-blast excavation under the condition of synchronous construction of the tunnel and the station.

3. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of the subway tunnel and the station according to claim 1, characterized in that, In step S2, the explosive detonation JWL model uses the MAT-HIGH-EXPLOSIVE-BURN material model, and the JWL equation of state is used to calculate the detonation pressure. The JWL equation of state is as follows: ； In the formula, is the detonation pressure, are all material parameters, is the relative volume, is the internal energy per unit volume, is a constant; The air model uses the MAT-NULL material model, and the state is described by the linear polynomial equation of EOS-LINEAR-POLYNOMIAL. The expression is: ； In the formula, is the air constant, , is a dimensionless parameter, , is the density, is the density under standard conditions, is the internal energy of the material; Simplified to the ideal gas model as: ； In the formula, is the specific heat ratio, ; The explosive detonation JWL model provides the energy release law of the explosion source, and the air model simulates the propagation dynamics of the shock wave in the air. The explosive detonation JWL model and the air model achieve the interaction of energy and momentum through the fluid-structure coupling method; The CSCM model for segment damage includes compression damage, tensile cracking, strain rate effect, and stiffness degradation; the MAT_PLASTIC_KINEMATIC is used to simulate the steel bars, which are connected to the segments through co-nodes or CONTACT_TIE to ensure stress transfer; The JH-2 model is used for the rock mass, and the progressive failure process of the material is described through damage accumulation and strain rate effect; the ALE fluid model uses Eulerian grids, and the structural model uses Lagrangian grids, and the two are coupled by CONSTRAINED_LAGRANGE_IN_SOLID; Mesh the station, tunnel, rock mass, and air together, and increase the mesh density at the fluid-structure interface; Set the initial ground stress, non-reflective boundary conditions, and solution control.

4. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations according to claim 1, characterized in that, In step S3, when extracting the vibration velocity, maximum tensile stress, and joint deformation index of the segments under different roof thicknesses, it includes: Conduct spectral analysis on the vibration velocity at key positions to identify the main frequency components and analyze whether the vibration main frequency is close to the natural frequency of the segments; Output the principal stress nephogram of the segments through the CSCM model for segment damage, and use LS-PrePost to identify the maximum tensile stress area and the stress peak values under each working condition; Monitor the normal displacement difference between the nodes on both sides of the segment joint to obtain the joint opening amount, and monitor the tangential displacement difference between the nodes on both sides of the segment joint to obtain the joint dislocation amount.

5. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of the subway tunnel and station according to claim 1, characterized in that, In step S4, when performing iterative optimization of the roof thickness, it includes: Input parameters; Select the uncertain parameters as random variables, including the elastic modulus , the internal friction angle , the single-hole explosive charge , the distance from the explosion center , the segment thickness ; Extract using the Latin hypercube sampling method groups of samples, evenly distributed to cover the random variable space; Construct a Kriging metamodel, based on the sample points Input its response , and output the surrogate model; Use the Kriging metamodel to calculate the Sobol' index for sensitivity analysis to obtain the contribution of each parameter to the response; Extract using the Monte Carlo sampling method groups, and input the Kriging meta-model to calculate the tunnel failure probability; Plot the relationship curve between the safety roof thickness and the failure probability to determine the critical safety roof thickness; multiply the critical thickness by the safety factor to obtain the final design thickness.

6. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations according to claim 5, wherein, Extract using the Latin hypercube sampling method groups of samples, evenly distributed to cover the random variable space, including: For each parameter , its value range is divided into equi-probability intervals, a sample point is randomly selected within each interval, and it is ensured that the sample points of each parameter do not form repeated combinations: ； In the formula, is the inverse function of the cumulative distribution function CDF of parameter , is the permutation serial number of the th sample in the th parameter dimension, and is the random offset within the interval.​​ 7. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations according to claim 5, characterized in that Construct a Kriging meta-model based on sample points Input its response , and output a surrogate model, including: The Kriging model assumes that the response is a Gaussian process: ； wherein, is the global mean value, is a zero-mean Gaussian process; The covariance function is: ； In the formula, is the covariance function, is a zero-mean Gaussian process, is the variance of the Gaussian process, is the correlation function, and are input points, are hyperparameters, optimized by maximum likelihood estimation (MLE); The relevant functions are as follows: ； In the formula, is the dimension of the input space, is the dimension index, is the scaling parameter for the th dimension, is the th value of the th dimension of the th point, is the th value of the th dimension of the th point.

8. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of the subway tunnel and station according to claim 5, characterized in that, Use the Kriging metamodel to calculate the Sobol' index for sensitivity analysis to obtain the contribution of each parameter to the response, including: Total variance decomposition: ； In the formula, is the main effect variance of the th parameter, is the interaction effect variance of the th and th parameters, and are the indices of the input parameters, is the high-order interaction effect variance of all parameters; The total effect Sobol' index is: ； In the formula, is the variance after excluding the parameter .

9. The method for optimizing the thickness of the shield tunnel roof slab during the synchronous construction of subway tunnels and stations according to claim 5, characterized in that, Extract using the Monte Carlo sampling method groups, input the Kriging meta-model to calculate the tunnel failure probability, including: Define the failure function: ； Wherein, is the allowable stress, is the maximum stress; Then the failure probability: ； In the formula, is the number of Monte Carlo samples, is 1 when it is , otherwise 0.

10. A shield tunnel roof thickness optimization system under synchronous construction of subway tunnels and stations, characterized in that, The system implements the shield tunnel roof thickness optimization method under the simultaneous construction of subway tunnels and stations as described in any one of claims 1-9. The system includes: A three-dimensional numerical model establishment module for establishing a three-dimensional numerical model according to tunnel geological parameters, blasting parameters, and shield segment parameters; A multi-field coupling analysis module for performing multi-field coupling analysis based on the established three-dimensional numerical model, using the explosive detonation JWL model, the ALE method for rock mass dynamic response, and the CSCM model for segment damage; An index extraction module for extracting the vibration velocity, maximum tensile stress, and joint deformation indexes of the segments under different roof thicknesses according to the multi-field coupling analysis results; A roof thickness iterative optimization module for performing roof thickness iterative optimization according to the vibration velocity, maximum tensile stress, and joint deformation indexes of the segments under different roof thicknesses extracted; verify and feedback in combination with on-site monitoring data according to the iterative optimization results.

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