Method and apparatus for simulating seismic response and damage evolution of a tunnel lining in a ground fissure zone

Abstract

The application discloses a kind of ground fissure zone tunnel lining earthquake response and damage evolution simulation method and equipment, it is related to the field of earthquake engineering.The present application is based on the constructed shaking table model, and a numerical simulation model is established by using the modified lattice spring-discrete crack network coupling numerical method, then, MLSM-DFN model of the ground fissure zone tunnel structure profile is constructed based on the numerical simulation model, and the earthquake response and damage simulation of the ground fissure zone tunnel lining are completed based on this model, the expansion and propagation law of the ground fissure can be completely and truly simulated, the activity development trend of the ground fissure can be accurately predicted and quantitatively characterized, meanwhile, the influencing factors and action mechanism of the coupled dynamics response induced tunnel structure failure can be accurately judged, to better, targetedly carry out tunnel structure seismic design provide more explicit theoretical basis and technical support.

Description

Technical Field

[0001] This invention relates to the field of earthquake engineering, and in particular to a method and equipment for simulating the seismic response and damage evolution of tunnel linings in ground fissure zones. Background Technology

[0002] With the increasing scale of urban rail transit construction, the environmental conditions encountered during construction are becoming increasingly complex. Given the growing prominence of ground fissure disasters, tunnel lining, as a key component in seismic design, necessitates research into the seismic response and damage evolution of tunnel linings in ground fissure zones. Numerical simulation is an effective approach to this research, but existing studies still face the following challenges:

[0003] (1) Numerical models are mostly based on the theory of continuum mechanics, which oversimplifies the high heterogeneity and discrete nature of the actual complex strata. They are difficult to fully and realistically simulate the expansion and propagation of ground fissures, resulting in the inability to accurately predict and quantify the development trend of ground fissures.

[0004] (2) Response analysis is mostly based on traditional mechanical methods. The dynamic response characteristics analysis when seismic load and ground fissure activity are coupled is still insufficient. It is difficult to accurately determine the influencing factors and mechanisms of tunnel structure failure induced by coupled dynamic response, which makes it impossible to carry out tunnel structure seismic design in a more targeted manner. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a method and equipment for simulating the seismic response and damage evolution of tunnel linings in ground fissure zones.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for simulating the seismic response and damage evolution of tunnel lining in a ground fissure zone includes:

[0008] A shaking table model was built, and seismic load simulation tests were conducted using the shaking table model to obtain test data;

[0009] Based on the vibration table model, a numerical simulation model was established using the modified lattice spring-discrete crack network coupled numerical method.

[0010] Based on the numerical simulation model, an MLSM-DFN model of the tunnel structure profile in the ground fissure zone was constructed.

[0011] Based on the MLSM-DFN model of the tunnel structure profile in the ground fissure zone, the seismic response and damage simulation of the tunnel lining in the ground fissure zone were completed.

[0012] Optionally, a shaking table model is constructed, and seismic load simulation tests are conducted using the shaking table model to obtain test data, specifically including:

[0013] Obtain research data; the research data includes basic geological data, hydrogeological data, engineering geological data, environmental geological data, geological hazard assessment data, seismic geological data, and engineering survey data of the study area and adjacent areas;

[0014] Based on the research data and the scale and performance of the shaking table used in the experiment, a shaking table model was constructed based on dimensional analysis and similarity theory.

[0015] The shaking table model was used to conduct seismic load simulation tests and obtain test data.

[0016] Optionally, an MLSM-DFN model of the tunnel structure profile in the ground fissure zone is constructed based on the numerical simulation model, specifically including:

[0017] Set the optimal input parameter dataset for the numerical simulation model;

[0018] The input parameters in the optimal input parameter dataset are input into the numerical simulation model to obtain local mechanical characteristics and damage generation methods, so as to obtain local contact force vector distribution characteristics;

[0019] The experimental data were processed using the moment tensor inversion method to obtain the processing results;

[0020] The processing results and the local contact force vector distribution characteristics are compared and analyzed to obtain the comparison and analysis results;

[0021] When the comparative analysis results are consistent, an MLSM-DFN model of the tunnel structure profile in the ground fissure zone is constructed based on the numerical simulation model.

[0022] When the comparative analysis results are inconsistent, the optimal input parameter dataset of the numerical simulation model is reset, and the process returns to the step of "inputting the input parameters in the optimal input parameter dataset into the numerical simulation model to obtain local mechanical characteristics and damage generation methods, so as to obtain local contact force vector distribution characteristics" until the comparative analysis results are consistent.

[0023] Optionally, the optimal input parameter dataset for the numerical simulation model is set, specifically including:

[0024] Establish the quantitative relationship between the input parameters of the MLSM lattice nodes of the numerical simulation model and the elastic modulus and scale characteristic parameters of the equivalent lattice unit cell material;

[0025] The objective function for the residuals between the experimental data and simulation results is established based on the least squares method.

[0026] Based on the quantization relationship, a discrete Newton multiple iteration calibration method is used to minimize the value of the objective function;

[0027] The optimal input parameter dataset is obtained by taking the input data that minimizes the objective function as the optimal input parameter of the numerical simulation model.

[0028] Optionally, based on the MLSM-DFN model of the tunnel structure profile in the ground fissure zone, the seismic response and damage simulation of the tunnel lining in the ground fissure zone is completed, specifically including:

[0029] Using El Centro and Taft waves as loading loads, computational mechanics simulation experiments were conducted on the MLSM-DFN model of the tunnel structure profile in the ground fissure zone, and the local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the ground fissure zone were collected.

[0030] The local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the ground fissure zone were analyzed to simulate the seismic response and damage of the tunnel lining in the ground fissure zone.

[0031] Optionally, the seismic response and damage simulation of tunnel lining in ground fissure zones includes: conducting research on the characteristics of seismic input signals and structural damage evolution, and exploring the mechanism by which coupled dynamic response induces damage and failure of tunnel lining structures.

[0032] An electronic device, comprising:

[0033] Memory, used to store computer programs;

[0034] A processor, connected to the memory, is used to retrieve and execute the computer program to implement the above-described method for simulating the seismic response and damage evolution of tunnel lining in ground fissure zones.

[0035] Optionally, the memory is a computer-readable storage medium.

[0036] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0037] This invention is based on a constructed shaking table model and uses a modified lattice spring-discrete crack network coupled numerical method to establish a numerical simulation model. Then, based on the numerical simulation model, an MLSM-DFN model of the tunnel structure profile in the ground fissure zone is constructed. Based on this model, the seismic response and damage simulation of the tunnel lining in the ground fissure zone is completed. It can completely and realistically simulate the expansion and propagation law of ground fissures, accurately predict and quantify the activity and development trend of ground fissures. At the same time, it can accurately determine the influencing factors and mechanisms of the failure of the tunnel structure induced by the coupled dynamic response, providing a clearer theoretical basis and technical support for better and more targeted seismic design of tunnel structures. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating the seismic response and damage evolution simulation method for tunnel lining in ground fissure zones provided by this invention;

[0040] Figure 2 This is an implementation architecture diagram of the method for simulating seismic response and damage evolution of tunnel lining in ground fissure zones provided in this invention.

[0041] Figure 3 This is a schematic diagram of the lattice spring model unit and corresponding lattice unit cell of the MLSM model used in the embodiments of the present invention; wherein, Figure 3 (a) is a schematic diagram of a triangular lattice unit cell. Figure 3 (b) is a schematic diagram of a square lattice unit cell. Figure 3 (c) is a schematic diagram of a hexagonal lattice unit cell;

[0042] Figure 4 A schematic diagram of the MLSM-DFN model of the tunnel structure profile in the ground fissure zone provided in an embodiment of the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] The purpose of this invention is to provide a method and equipment for simulating the seismic response and damage evolution of tunnel linings in ground fissure zones. This method can completely and realistically simulate the expansion and propagation of ground fissures, accurately predict and quantify the activity and development trend of ground fissures, and accurately determine the influencing factors and mechanisms of coupled dynamic response-induced tunnel structure failure. This provides a clearer theoretical basis and technical support for better and more targeted seismic design of tunnel structures.

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] like Figure 1 As shown, the seismic response and damage simulation method for tunnel lining in ground fissure zones provided by this invention includes:

[0047] Step 100: Construct a shaking table model and conduct seismic load simulation tests using the shaking table model to obtain test data. The implementation process for this step can be as follows:

[0048] Step 1001: Obtain research data. This research data mainly refers to basic geological data, hydrogeological data, engineering geological data, environmental geological data, geological hazard assessment data, seismic geological data, and engineering survey data of the study area and adjacent areas (i.e., surrounding areas).

[0049] Step 1002: Based on the research data and the scale and performance of the shaking table used in the experiment, design and construct the shaking table model based on dimensional analysis and similarity theory.

[0050] Step 1003: Conduct seismic load simulation tests using a shaking table model and obtain test data. Specifically, the implementation process of this step is as follows:

[0051] Step 10031: Based on the research data collected in Step 1001, select the seismic response signal of the prepared shaking table model to realistically simulate seismic loads. The seismic response signal here includes, but is not limited to, widely used seismic wave signals such as El Centro waves and Taft waves.

[0052] Step 10032: Set up data measurement points. Set up sensing devices on the constructed shaking table model to obtain seismic response characteristics, namely stress, strain, displacement, acceleration, etc.

[0053] Step 10033: Collect experimental data. Apply the simulated seismic response signal from step 10031, and based on the dynamic signal acquisition system, use sensors to pick up the mechanical characteristic parameter signals of the shaking table model, convert them into electrical signals, and then sample them after conditioning. The sampled signals are processed and sent to the computer to obtain the measurement results of parameters such as test stress, strain, displacement, and acceleration of the shaking table model.

[0054] Step 10034: Calculate seismic parameters. In the dynamic analysis of earthquake engineering, the peak ground acceleration (PGA), duration, and frequency characteristics of seismic waves are the three main analytical parameters. Among them, PGA and PHR are the most fundamental physical quantities. The parameter measurement results obtained in Step 10033 are then processed to conduct a study on seismic response characteristics, specifically including the peak acceleration response and amplification factor on both sides of the ground fissure, the attenuation law of the acceleration response on both sides of the ground fissure, and the effects of the hanging wall and footwall on the ground fissure acceleration response.

[0055] Step 101: Based on the shaking table model, a numerical simulation model (MLSM-DFN model) is established using the modified lattice spring-discrete crack network coupled numerical method. In this step, the lattice arrangement of the numerical simulation model is determined by simulating the anisotropy of the original soil medium, thereby generating the position coordinates of the lattice nodes with reasonable mesh accuracy.

[0056] Step 102: Construct an MLSM-DFN model of the tunnel structure profile in the ground fissure zone based on the numerical simulation model.

[0057] Step 1021: Set the optimal input parameter dataset for the numerical simulation model.

[0058] The input parameters of the MLSM lattice nodes in the numerical simulation model (such as spring stiffness, particle density, bond length, micro-rotational inertia, etc.) and the equivalent lattice unit cell (such as...) are used to establish the numerical simulation model. Figure 3 (As shown) The quantitative relationship between the elastic modulus and dimensional characteristic parameters of the material.

[0059] An objective function for the residuals between experimental data and simulation results is established based on the least squares method.

[0060] Based on the quantization relationship, a discrete Newton multiple iteration calibration method is used to minimize the value of the objective function.

[0061] The optimal input parameter dataset is obtained by taking the input data that minimizes the objective function as the optimal input parameters for the numerical simulation model.

[0062] Step 1022: Input the input parameters from the optimal input parameter dataset into the numerical simulation model to obtain local mechanical characteristics and damage generation methods, thereby acquiring the local contact force (couple) vector distribution characteristics. Local mechanical characteristics include, but are not limited to, the forces acting on individual lattice nodes and the number and type of force couples (tension / compression or shear). Damage generation methods include, but are not limited to, opening, sliding, and tearing types.

[0063] Step 1023: Process the experimental data using the moment tensor inversion method to obtain the processing results.

[0064] Step 1024: Compare and analyze the processing results and the local contact force vector distribution characteristics to obtain the comparison and analysis results.

[0065] Step 1025: When the comparative analysis results are consistent, construct an MLSM-DFN model of the tunnel structure profile in the ground fissure zone based on the numerical simulation model. In this step, based on the numerical simulation model, obtain parameter data of typical tunnel structures (such as horseshoe-shaped, circular, etc.) according to survey data. By removing the lattice nodes representing the tunnel structure and assigning given input parameters (such as cohesion, internal friction angle, expansion angle, damping coefficient, etc.) to the lattice nodes representing the lining structure, an MLSM-DFN model of the ground fissure zone containing the tunnel lining structure is established. The specific structure of this MLSM-DFN model is as follows: Figure 4 As shown. Figure 4 In the diagram, lattice nodes of different materials are represented by different colors, with white and black representing ground fissures and strata bonds, respectively.

[0066] Step 1026: When the comparative analysis results are inconsistent, reset the optimal input parameter dataset of the numerical simulation model and return to step 1022 until the comparative analysis results are consistent.

[0067] Step 103: Based on the MLSM-DFN model of the tunnel structure profile in the ground fissure zone, complete the seismic response and damage simulation of the tunnel lining in the ground fissure zone.

[0068] Step 1031: Using El Centro and Taft waves as loading loads, conduct computational mechanics simulation experiments on the MLSM-DFN model of the tunnel structure profile in the ground fissure zone, and collect the local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the ground fissure zone.

[0069] Step 1032: Analyze the local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the ground fissure zone to complete the seismic response and damage simulation of the tunnel lining in the ground fissure zone. This simulation includes: studying the characteristics of seismic input signals and structural damage evolution, and exploring the mechanism by which coupled dynamic response induces damage and failure in the tunnel lining structure.

[0070] Based on the above description, the seismic response and damage evolution simulation method for tunnel lining in ground fissure zones provided by this invention can be divided into three main parts: (1) shaking table model test study of seismic response in ground fissure sites; (2) calculation and dynamic simulation of seismic response in ground fissure sites; and (3) calculation and dynamic simulation of seismic response in ground fissure sites. The processing flow between these three parts is as follows: Figure 2 As shown, specifically:

[0071] (1) Seismic response shaking table model test study of ground fissure sites: Based on similarity theory and exploration data, a seismic response shaking table test model of a typical ground fissure zone site was designed and fabricated. Test data was collected by rationally arranging the shaking table test boundary, load application method, and measuring point locations, and key characteristic parameters were obtained through theoretical formulas. The collected test data includes, but is not limited to, the time-domain information of displacement, velocity, and acceleration of the measuring points. The obtained key characteristic parameters include, but are not limited to, the peak ground acceleration, duration, and frequency characteristics of the measuring points, the peak ground acceleration response and amplification factor of the measuring points on both sides of the ground fissure, the attenuation law of the acceleration response of the measuring points on both sides of the ground fissure, and the effects of the hanging wall and footwall on the ground fissure acceleration response.

[0072] Specifically, the process of the earthquake response shaking table model test study of the ground fissure site in this step is as follows:

[0073] (11) Research data survey: collect research data on basic geology, hydrogeology, engineering geology, environmental geology, geological hazard assessment, seismic geology, engineering exploration and other related data of the study area and its surrounding areas.

[0074] (12) Model Design and Fabrication: Based on (11) and the scale and performance of the shaking table used in the experiment, and using dimensional analysis and similarity theory, a shaking table model test is designed and fabricated. For example, a layered shear deformation soil box is used, and the original soil sample and the model soil of the ground fissure zone in the study area are designed and fabricated according to the similarity theorem. The basic ideas of similarity theory and shaking table model test design are as follows:

[0075] Similarity theory connects engineering practice with model experiments, revealing practical problems in specific engineering projects, and is therefore widely used in experimental theory. Theoretically, model experiment design must be based on similarity theory, satisfying the three similarity theorems: the positive similarity theorem (first similarity theorem), the π theorem (second similarity theorem), and the inverse similarity theorem (third similarity theorem). Specifically, similarity theory states that for two similar systems with identical single-valued conditions, their similarity criteria also have identical numerical values. When a phenomenon is represented by a functional relationship of n physical quantities, and these physical quantities contain m fundamental dimensions, then (nm) similarity criteria can be obtained. For phenomena with the same characteristics, if their single-valued conditions (the geometric properties of the system, the physical properties of the medium, initial conditions, and boundary conditions, etc.) are similar, and the similarity criteria composed of the physical quantities of the single-valued conditions are numerically equal, then these phenomena must be similar.

[0076] Based on this, the static similarity relationship of the shaking table model must be satisfied as follows:

[0077]

[0078] In the formula, F is the force (N), and g is the acceleration due to gravity (m / s²). 2E is the elastic modulus (Pa). ρ is the density (kg / m³). 3 L is length (m). ν is Poisson's ratio. c is cohesion (Pa). σ is stress (Pa). Let f be the angle of internal friction (°). f() is the function value.

[0079] Based on the second similarity theorem and dimensional analysis, taking length L, elastic modulus E, and density ρ as the basic dimensions, the similarity criterion can be derived as follows:

[0080]

[0081] Therefore, the similarity index can be obtained as follows:

[0082]

[0083] In the formula, π1, π2, π3, π4, and π5 are all similarity criteria, and C F C is the force similarity constant. E C is the similarity constant for the elastic modulus. g C is the similarity constant for gravitational acceleration. ν Let C be the similarity constant for Poisson's ratio. L C is a dimensional similarity constant. ρ C is the density similarity constant. c C is the cohesive similarity constant. σ Let be the stress similarity constant. is the similarity constant for the internal friction angle.

[0084] (13) Simulate seismic response: Based on the seismic data information surveyed in step (11), select the seismic response signal for the shaking table model prepared in step (12) to realistically simulate seismic load.

[0085] (14) Arrange data measurement points: On the original soil sample of the representative study area on both sides of the ground fissure model prepared in step (12), soil stress gauges, micro soil pressure sensors, soil strain gauges, inductive displacement sensors, wire displacement gauges, piezoelectric ceramic micro inductively coupled plasma acceleration sensors, etc. are reasonably arranged to obtain seismic response characteristics, namely stress, strain, displacement, acceleration, etc.

[0086] (15) Collect experimental data: Apply the simulated earthquake response set in step (13), and based on the dynamic signal acquisition system, the mechanical characteristic parameter signal of the shaking table is picked up by the sensor, converted into an electrical signal output, conditioned and sent to the sampling module for sampling, and the sampled signal is sent to the computer after processing, so as to obtain the measurement results of parameters such as stress, strain, displacement and acceleration of the shaking table model test.

[0087] (16) Calculate earthquake parameters: In the dynamic analysis of earthquake engineering, the peak ground acceleration, duration, and frequency characteristics of seismic waves are the three main analytical parameters. Among them, peak ground acceleration and peak ground velocity are the most fundamental physical quantities. The experimental data obtained in step (15) are further processed to carry out research on earthquake response characteristics, specifically including the peak acceleration response and amplification factor on both sides of the ground fissure, the attenuation law of the acceleration response on both sides of the ground fissure, and the effects of the hanging wall and footwall on the ground fissure acceleration response. The formulas involved are as follows:

[0088]

[0089] In the formula, K i,j Let represent the acceleration amplification factor, where i represents the i-th working condition and j represents the j-th measuring point. A i0 This represents the peak excitation acceleration under the i-th operating condition. A i,jmax It represents the peak value of the excitation acceleration at the j-th measuring point under the i-th working condition.

[0090]

[0091] In the formula, W represents the upper and lower plate effect coefficients, and A u,max and A d,max These represent the maximum response accelerations of the upper and lower plates, respectively.

[0092] (2) Seismic response calculation and dynamic simulation of ground fissure sites: Based on the MLSM-DFN model, the corresponding numerical simulation model in step (1) is established. According to the experimental data collected in step (1), the objective function is established using, but not limited to, the discrete Newton method. After multiple iterations and calibrations, the microscopic input parameters of the discrete numerical model are obtained. The local mechanical characteristics and damage generation methods of the numerical model are numerically calculated and collected. The local contact force (couple) vector distribution characteristics are obtained, etc., and compared with the damage generation methods of the given area obtained by the moment tensor inversion method in step (1). This further verifies the correctness and effectiveness of the MLSM-DFN model for the seismic response study of typical ground fissure zones. Among them, the microscopic input parameters include, but are not limited to, the input parameter set of lattice nodes (such as cohesion, internal friction angle, expansion angle, damping coefficient, etc.), and the numerical damping coefficient of the system. The local mechanical characteristics include, but are not limited to, the forces acting on a single lattice node and the number and type of force couples (tension and compression, or shear). The damage generation methods include, but are not limited to, opening type, sliding type, tearing type, etc.

[0093] In this step, the specific process of calculating the seismic response dynamics of the ground fissure site is as follows:

[0094] (21) Establish a numerical model: Based on the shaking table model in step (1), a corresponding numerical simulation model (MLSM-DFN model) is established by using the modified lattice spring-discrete crack network coupled numerical method. The lattice arrangement of the numerical model is determined by simulating the anisotropy of the original soil medium, and then the position coordinates of the lattice nodes with reasonable grid accuracy are generated.

[0095] In the field of exploration geophysics, based on the unique multi-scale mechanical behavior of unconventional oil and gas reservoirs, (Liu and Fu 2020b; 2021) proposed a modified lattice spring-discrete fracture network coupled model, abbreviated as MLSM-DFN model, to simulate and predict the static and dynamic response characteristics of multi-mineral component media in complex fracture systems. This model uses the MLSM method to simulate the rock skeleton at different sample scales, and DFN to simulate the complex fracture network. MLSM, proposed by (Liu et al. 2020) based on the fundamental idea of ​​general couple stress theory in generalized continuum mechanics, is a numerical method based on discrete thinking, which modifies the traditional non-central shear-type LSM by introducing independent micro-rotational inertia.

[0096] Specifically, ① the MLSM model includes lattice nodes of different shapes, specifically triangular lattices, square lattices, and hexagonal lattices. These lattice nodes are connected by tension / compression and shear springs. Taking a linear elastic constitutive model as an example, the normal and tangential forces and moments of lattice nodes i and j are... With M ij They are respectively:

[0097]

[0098]

[0099]

[0100] In the formula, d is the crystal bond length, and K is the crystal bond length. n and K s It refers to the stiffness of tension, compression, and shear springs. and These are the normal and tangential displacements, and the formulas are as follows:

[0101]

[0102]

[0103]

[0104] In the formula, the subscripts i and j represent the lattice node numbers, respectively, and u i Let u be the displacement vector of lattice node i. j Let be the displacement vector of lattice node j. Let be the normal vector of the bonding interaction between lattice node i and lattice node j. Let θ be the tangential vector of the bonding interaction between lattice node i and lattice node j. i Let θ be the angular displacement vector of lattice node i. j Let be the angular displacement vector of lattice node j. for and The cross product vector.

[0105] This method solves the equations of motion based on the central difference algorithm, and the specific formula is as follows:

[0106]

[0107]

[0108]

[0109]

[0110] Among them, the superscript t, Representing t, respectively At that moment, F i and M i It is the resultant force and resultant torque acting on lattice node i. ω represents the velocity vector of lattice node i. i is the angular velocity vector of lattice node i, and I is the given micro-moment of inertia.

[0111] ② Discrete Fracture Networks (DFN) are extracted based on the actual fracture morphology using image processing methods (Liu and Fu 2020b; Liu et al. 2021).

[0112] ③ The DFN extracted in step ② is then embedded into the rock framework represented by MLSM in step ① (in the shape of...) Figure 4 As shown in (a), but without the lining structure, the direction of the crystal bond action or the spring stiffness through which the DFN passes is adjusted to simulate the physical properties and slip trend of the crack, thereby establishing an MLSM-DFN model for complex crack media.

[0113] (22) Set input parameters: Establish the quantitative relationship between the input parameters of the MLSM lattice nodes in the model in step (21) (such as spring stiffness, particle density, bond length, micro-rotational inertia, etc.) and the elastic modulus and scale characteristic parameters of the equivalent lattice unit cell material (i.e., scale effect characterization parameters). The specific formula is as follows:

[0114] U cell =Ucontinuum .

[0115]

[0116]

[0117] In the formula, U cell U continuum These are the equivalent unit cell of the MLSM model and the elastic energy of the corresponding continuum mechanics theory, respectively. ε is the strain tensor, and C is the elastic stiffness matrix.

[0118] Based on the least squares method, an objective function f(x) is established for the residuals between the test data and the simulation data of the motion states such as displacement, velocity, and acceleration obtained in the shaking table test in step (15), as shown in the following formula:

[0119]

[0120] In the formula, x is the set of input parameters for the lattice node to be calibrated (such as cohesion, internal friction angle, expansion angle, damping coefficient, etc.), the numerical damping of the system, etc., N is the number of existing experimental data used for calibration, and d i It is the i-th data point (containing the key feature parameters obtained in step (1)), w i It is the weight factor corresponding to the i-th data point, s i (x) is the simulation result obtained by using the dataset x as input parameter, r i This represents the residual between the simulation results and the experimental data. Multiple iterative calibrations using the discrete Newton method are employed to minimize the value of the objective function, thereby obtaining the optimal input parameter dataset x for the MLSM model.

[0121] (23) Collect simulation data: Run the numerical model in steps (21) and (22), calculate and collect the local mechanical characteristics and damage generation mode of the numerical model, and obtain the local contact force (couple) vector distribution characteristics, etc.

[0122] (24) Comparison and model correction: Conduct a comparative study on the damage generation mode in a given area. Process the stress, strain, displacement, acceleration and other data in step (15) based on the moment tensor inversion method. Compare and analyze the results with those obtained in step (23). If the results are consistent, further verify the correctness and effectiveness of the MLSM-DFN model for the seismic response study of typical ground fissure zones. If the results are inconsistent, repeat steps (22)-(24) to correct the model until numerical simulation data that matches the results in step (1) are obtained.

[0123] The basic idea of ​​the moment tensor inversion method is based on the damage equivalent load theory, transforming the inversion of damage parameters into the identification of the damage equivalent load (moment tensor), which can be used to distinguish different source types. Moment tensor inversion is generally based on direct P-waves, and the general inversion formula is as follows:

[0124]

[0125] In the formula, n represents the number of the orthogonal coordinate axis, a n M represents the n-direction component of the amplitude of the dynamic response received at the measuring point. pq (p,q=1,2,3) represents 9 unknown moment tensor elements, γ n Let be the component of the direction cosine of the line connecting the source and the measuring point in the n-direction, R represent the distance from the source to the measuring point, and ρ be the density of the medium. For the three components of the spatial force and the three possible radius vector directions, there are nine generalized couples. The moment tensor is a linear combination of these nine couples, and based on the symmetry of the moment tensor, it has six independent components. After diagonalization, the moment tensor can be represented as eigenvalues ​​in the principal axis coordinate system.

[0126]

[0127] In the formula, M1, M2, and M3 are the three eigenvalues ​​of the moment tensor, which can be decomposed into a linear superposition of the moment tensors corresponding to several basic sources. The weight factor of each basic form in the current moment tensor can be used to determine the damage mechanism type. Currently, the most commonly used basic source forms are isotropic (ISO), double-couple (DC), and complementary linear vector dipole (CLVD) sources, with corresponding moment tensors being the isotropic source moment tensor E, respectively. ISO Shear double couple source moment tensor E DC Supplementing the linear vector dipole source moment tensor E CLVD The format is as follows:

[0128]

[0129]

[0130]

[0131]

[0132] Therefore, we can further conclude that:

[0133] M = M ISO E ISO +MDC E DC +M CLVD E CLVD .

[0134] When M1+M3-2M2≥0 on the contrary, The weighting factors are calculated as follows:

[0135]

[0136] In the formula, C ISO C DC C CLVD These are, respectively, the isotropic source weighting factor, the shear double-couple source weighting factor, and the supplementary linear vector dipole source weighting factor; M ISO M DC M CLVD These are the proportion coefficients of isotropic sources, shear double-couple sources, and supplementary linear vector dipole sources, respectively, which are used to determine the damage mechanism type.

[0137] (3) Seismic response and damage mechanism analysis of tunnel lining in fissure zone: Based on the MLSM-DFN model constructed in step (2), parameter data of typical tunnel structures (such as horseshoe-shaped, circular, etc.) are obtained according to the survey data. By removing the lattice nodes representing the tunnel structure and assigning given input parameters (such as cohesion, internal friction angle, expansion angle, damping coefficient, etc.) to the lattice nodes representing the lining structure, an MLSM-DFN model of tunnel lining structure in fissure zone is established. The local mechanical characteristics and damage generation mode of the numerical model are numerically calculated and collected, and the local contact force (couple) vector distribution characteristics are obtained, etc., so as to quantitatively analyze the mechanism of damage and failure of tunnel lining structure induced by coupled dynamic response.

[0138] The specific process of analyzing the seismic response and damage mechanism of the tunnel lining with cracks in this step is as follows:

[0139] (31) Constructing the lining model: Based on the MLSM-DFN model in step (2), obtain parameter data of typical tunnel structures (such as horseshoe-shaped, circular, etc.) according to the survey data. By removing the lattice nodes representing the tunnel structure and assigning given input parameters (such as cohesion, internal friction angle, expansion angle, damping coefficient, etc.) to the lattice nodes representing the lining structure, an MLSM-DFN model of the ground fissure zone containing the tunnel lining structure is established.

[0140] (32) Data collection: The El Centro wave and Taft wave, which are mainly used in the seismic design code, are used as loading loads. Based on the MLSM-DFN model of the ground fissure zone with tunnel lining constructed in step (31), computational mechanics simulation experiments are carried out. The local mechanical characteristics and damage generation mode of the MLSM-DFN model of the ground fissure zone with tunnel lining are collected, and the local contact force (couple) vector distribution characteristics are obtained.

[0141] (33) Damage Mechanism Analysis: The local mechanical characteristics, damage generation methods, and local contact force (couple) vector distribution characteristics of the numerical model are analyzed. Based on this, the correlation between seismic input signals and structural damage evolution characteristics is studied. By integrating signal processing, moment tensor inversion, and other analytical methods, the mechanism of coupled dynamic response-induced damage and failure of tunnel lining structures is further explored.

[0142] Based on the above description, this invention, by adopting the above technical solutions, has the following advantages: This invention designs a shaking table physical model of typical ground fissure site characteristics based on similarity theory, and conducts related seismic response shaking table model test studies. A novel cross-scale numerical calculation method is introduced to realize numerical simulation of the seismic response of ground fissure sites. On this basis, a refined numerical model of ground fissure sites with lining structures, considering damage evolution characteristics, is constructed. Based on computational mechanics experimental results and the moment tensor inversion method, a method for studying the seismic response and damage mechanism of tunnel linings in ground fissure zones is proposed. This method can obtain the evolution law of mesoscopic local mechanical characteristic parameters with respect to time and spatial scales, quantitatively analyze the seismic response characteristics of tunnel lining structures in ground fissure zones, and is used to conduct research on the correlation between seismic input signals and damage evolution characteristics. It has significant scientific importance for elucidating the mechanism of damage and failure of tunnel lining structures induced by coupled dynamic response, and is expected to provide a clearer theoretical basis and technical support for the seismic design of tunnel structures in ground fissure zones.

[0143] Furthermore, the present invention also provides an electronic device comprising:

[0144] Memory is used to store computer programs.

[0145] The processor, connected to the memory, is used to retrieve and execute computer programs to implement the above-described simulation method for seismic response and damage evolution of tunnel lining in ground fissure zones.

[0146] Furthermore, when the computer program in the aforementioned memory is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0147] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the electronic devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0148] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for simulating the seismic response and damage evolution of tunnel lining in a ground fissure zone, characterized in that, include: A shaking table model was built, and seismic load simulation tests were conducted using the shaking table model to obtain test data; Based on the vibration table model, a numerical simulation model was established using the modified lattice spring-discrete crack network coupled numerical method. The construction of an MLSM-DFN model of the tunnel structure profile in the ground fissure zone based on the numerical simulation model includes: setting the optimal input parameter dataset of the numerical simulation model; inputting the input parameters in the optimal input parameter dataset into the numerical simulation model to obtain local mechanical characteristics and damage generation methods, thereby obtaining local contact force vector distribution characteristics; processing the experimental data based on the moment tensor inversion method to obtain processing results; comparing and analyzing the processing results and the local contact force vector distribution characteristics to obtain comparison analysis results; when the comparison analysis results are consistent, constructing an MLSM-DFN model of the tunnel structure profile in the ground fissure zone based on the numerical simulation model; when the comparison analysis results are inconsistent, resetting the optimal input parameter dataset of the numerical simulation model and returning to the step of "inputting the input parameters in the optimal input parameter dataset into the numerical simulation model to obtain local mechanical characteristics and damage generation methods, thereby obtaining local contact force vector distribution characteristics", until the comparison analysis results are consistent; Based on the MLSM-DFN model of the tunnel structure profile in the fissure zone, the seismic response and damage simulation of the tunnel lining in the fissure zone was completed. This included: using El Centro and Taft waves as loading loads, conducting computational mechanics simulation experiments on the MLSM-DFN model of the tunnel structure profile in the fissure zone, and collecting the local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the fissure zone; analyzing the local mechanical characteristics of the MLSM-DFN model of the tunnel structure profile in the fissure zone to complete the seismic response and damage simulation of the tunnel lining in the fissure zone; the seismic response and damage simulation of the tunnel lining in the fissure zone included: conducting research on the evolution characteristics of seismic input signals and structural damage, and exploring the mechanism by which coupled dynamic response induces damage and failure of the tunnel lining structure. The optimal input parameter dataset for the numerical simulation model includes: Establish the quantitative relationship between the input parameters of the MLSM lattice nodes of the numerical simulation model and the elastic modulus and scale characteristic parameters of the equivalent lattice unit cell material; The objective function for the residuals between the experimental data and simulation results is established based on the least squares method. Based on the quantization relationship, a discrete Newton multiple iteration calibration method is used to minimize the value of the objective function; The optimal input parameter dataset is obtained by taking the input data that minimizes the objective function as the optimal input parameter of the numerical simulation model.

2. The method for simulating seismic response and damage evolution of tunnel lining in ground fissure zones according to claim 1, characterized in that, A shaking table model was constructed, and seismic load simulation tests were conducted using the shaking table model to obtain test data, specifically including: Obtain research data; the research data includes basic geological data, hydrogeological data, engineering geological data, environmental geological data, geological hazard assessment data, seismic geological data, and engineering survey data of the study area and adjacent areas; Based on the research data and the scale and performance of the shaking table used in the experiment, a shaking table model was constructed based on dimensional analysis and similarity theory. The shaking table model was used to conduct seismic load simulation tests and obtain test data.

3. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, connected to the memory, is used to retrieve and execute the computer program to implement the seismic response and damage evolution simulation method for tunnel lining in ground fissure zones as described in any one of claims 1 and 2.

4. The electronic device according to claim 3, characterized in that, The memory is a computer-readable storage medium.

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