Method for calculating and evaluating dynamic response of surrounding rock under blasting excavation of hard rock tunnel

Abstract

The invention discloses a surrounding rock dynamic response calculation and evaluation method under hard rock tunnel blasting excavation. The calculation method comprises the following steps: S1, obtaining tunnel design data and geological section information; s2, acquiring physical and mechanical parameters; s3, blasting parameters are obtained; s4, constructing a three-dimensional hard rock tunnel blasting excavation grid model according to the tunnel design data and the geological section information obtained in the step S1; s5, importing the three-dimensional tunnel blasting excavation grid model, blasting parameters and physical and mechanical parameters into finite difference software; s6, analyzing and calculating the three-dimensional tunnel blasting excavation grid model through a dynamic calculation module built in finite difference software to obtain surrounding rock dynamic response data under blasting excavation; and S7, comparing and analyzing the dynamic response data of the surrounding rock under blasting excavation with a safety evaluation threshold value. According to the method, the comprehensiveness and the accuracy of tunnel surrounding rock dynamic response evaluation under blasting excavation are improved aiming at the defects of an existing method and actual application requirements.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel blasting, and in particular to a method for calculating and evaluating the dynamic response of surrounding rocks during blasting excavation of a hard rock tunnel. Background Art

[0002] Drilling and blasting is widely used in mining, quarrying and tunnel engineering. Compared with other mechanical methods using rock breakers, tunnel boring machines and roadheaders, drilling and blasting is economical, especially in tunnel excavation under different geological conditions. Compared with other excavation methods, it has the advantages of low cost, easy operation, high adaptability and high speed, which make drilling and blasting the preferred method for rock excavation and has been widely used in mountain tunnel excavation. However, blasting excavation will inevitably induce surrounding rock damage due to the impact of the explosion, thereby reducing the stability of the surrounding rock. Scholars have achieved many results in the stability assessment of tunnel surrounding rock. Different methods are used in combination with engineering practice to assess the damage caused by blasting excavation to the surrounding rock mass. However, most methods are based on only a few cases, and these methods have the limitations of being too subjective, consuming a lot of manpower and time, and difficult to accurately obtain parameters. There is still room for further optimization of applicability. Therefore, a method for evaluating the dynamic response of surrounding rock under blasting excavation of hard rock tunnels is needed, which will help to better ensure the safety of on-site blasting construction and guide the optimization of subsequent blasting construction plans. Summary of the invention

[0003] The purpose of the present invention is to provide a method for calculating and evaluating the dynamic response of surrounding rock of a hard rock tunnel under blasting excavation, which aims at the shortcomings of existing methods and the needs of practical applications, and improves the comprehensiveness and accuracy of the evaluation of the dynamic response of surrounding rock of a tunnel under blasting excavation.

[0004] In one aspect of the present invention, a method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel is provided. According to an embodiment of the present invention, the method comprises the following steps:

[0005] S1. Obtain tunnel design data and geological section information;

[0006] S2. Obtain the physical and mechanical parameters of the hard rock tunnel;

[0007] S3, obtaining blasting parameters;

[0008] S4, constructing a three-dimensional hard rock tunnel blasting excavation grid model based on the tunnel design data and geological section information obtained in step S1;

[0009] S5, importing the three-dimensional tunnel blasting excavation grid model, blasting parameters, and physical and mechanical parameters into the finite difference software;

[0010] S6. Analyze and calculate the three-dimensional tunnel blasting excavation grid model through the dynamic calculation module built into the finite difference software to obtain the dynamic response data of the surrounding rock under blasting excavation;

[0011] S7. Compare and analyze the surrounding rock dynamic response data under the blasting excavation with the safety assessment threshold.

[0012] In addition, the method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to the above embodiment of the present invention may also have the following additional technical features:

[0013] In some embodiments of the present invention, in step S1, the tunnel design data and geological section information include tunnel section design information, tunnel construction process information, geological survey information, and stratum section information; in step S2, the physical and mechanical parameters include elastic modulus, Poisson's ratio, cohesion, friction angle, tensile strength, and density; in step S3, the blasting parameters include the vibration frequency of the hard rock tunnel.

[0014] In some embodiments of the present invention, step S4 is specifically as follows: importing tunnel design data and geological section information into the raino modeling software, and constructing a three-dimensional hard rock tunnel blasting excavation grid model through the raino stretch entity command combined with the griddle meshing plug-in.

[0015] In some embodiments of the present invention, in step S6, the finite difference software is FLAC 3D, and using the finite difference software to analyze and calculate the dynamic response data of the surrounding rock under blasting excavation includes the following steps:

[0016] S601, select the dynamic calculation mode, define the constitutive model and material physical parameters;

[0017] S602, defining boundary conditions and initial conditions required for calculation;

[0018] S603, performing initialization calculation to obtain the original rock stress state before excavation;

[0019] S604, setting dynamic calculation boundary conditions and required damping;

[0020] S605, applying blasting parameters, performing blasting excavation calculation and analysis, and obtaining surrounding rock dynamic response data after blasting excavation.

[0021] In some embodiments of the present invention, in step S7, the safety evaluation threshold includes safety thresholds of tensile stress and displacement deformation.

[0022] In some embodiments of the present invention, the tensile stress safety threshold comparison analysis method is as follows: the vibration velocity is converted into tensile stress by the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress, X is the vibration velocity, and the maximum tensile stress is used as the safety threshold of stress. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1.

[0023] In some embodiments of the present invention, the displacement deformation safety threshold comparison and analysis method is as follows: according to the reserved deformation amount required by the design, the designed reserved deformation amount is used as the safety threshold of the displacement deformation. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1.

[0024] The present invention constructs a three-dimensional tunnel blasting excavation grid model, utilizes the vibration monitoring data of the tunnel construction site and performs noise reduction processing and physical and mechanical tests to obtain blasting parameters and rock parameters, thereby solving the problems of difficult blasting parameter selection and distorted calculation results in numerical simulation software, and improving the accuracy of numerical simulation of the dynamic response of the tunnel surrounding rock under blasting excavation.

[0025] In another aspect of the present invention, a method for evaluating the dynamic response of surrounding rock under blasting excavation of hard rock tunnels is proposed. According to an embodiment of the present invention, the dynamic response calculation method of surrounding rock under blasting excavation of hard rock tunnels is used for evaluation, that is, the dynamic response data (vibration velocity, displacement deformation) of the surrounding rock under blasting excavation is obtained through the physical and mechanical parameters (elastic modulus, Poisson's ratio, cohesion, friction angle, density), and on this basis, the dynamic response data of surrounding rock under blasting excavation is compared with the safety threshold, and according to the comparison result, the safety of the surrounding rock of the tunnel under blasting excavation is evaluated. Specifically, the following steps are included:

[0026] Step 01, obtaining first information: the first information includes tunnel design information, geological section information, and physical and mechanical parameters;

[0027] Step 02, outputting second information: outputting second information according to the first information, the second information including vibration velocity and displacement deformation of the hard rock tunnel;

[0028] Step 03, outputting third information: outputting third information according to the second information, the third information including the safety evaluation result;

[0029] Step 04: Comprehensive evaluation: Output the third information for security assessment.

[0030] In addition, the method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to the above embodiment of the present invention may also have the following additional technical features:

[0031] In some embodiments of the present invention, the evaluation method is implemented by training a Gaussian process machine learning evaluation model.

[0032] In some embodiments of the present invention, the construction of the Gaussian process machine learning evaluation model includes the following steps:

[0033] S11. Data preparation

[0034] Define X variables: including physical and mechanical parameters, tunnel design parameters, and blasting parameters;

[0035] Define the Y variable: it contains the target data, that is, the two predicted values ​​corresponding to each set of features: vibration velocity and displacement deformation;

[0036] S12. Define the kernel

[0037] Two kernels are used to define the scale and smoothness of the prediction function. The constant kernel is used to define the scale of the function value and adjust the overall amplitude of the prediction result. The radial basis function kernel is used to define the smoothness of the function.

[0038] S13. Model training

[0039] Two Gaussian process regression models were created, each predicting a target variable Y;

[0040] The model training process includes: optimizing kernel parameters and fitting data;

[0041] S14. Dynamic response data prediction

[0042] Input a new set of X variable data for prediction, and obtain two predicted values ​​of Y variable and the corresponding standard deviation; calculate the predicted data of surrounding rock dynamic response under blasting excavation according to different weights of physical and mechanical parameters and blasting parameters;

[0043] S15. Evaluation and classification

[0044] Tensile stress safety evaluation: The vibration velocity is converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, and b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress; the maximum tensile stress is taken as the safety threshold of stress. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1, and the blasting construction plan needs to be improved and the support needs to be strengthened;

[0045] Safety evaluation of displacement deformation: According to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of displacement deformation. If it does not exceed, it is considered safe and recorded as 0; if it exceeds, it is considered unsafe and recorded as 1, and the blasting construction plan needs to be improved and the support needs to be strengthened;

[0046] The evaluation function is used with the formula: Z=A1+A2, where A1 and A2 correspond to the evaluation results of tensile stress and displacement deformation respectively. If the evaluation index exceeds the limit value, a warning message is output and unsafe: 1 is output; if all predicted values ​​are within the safe range, safe: 0 is output, thereby realizing a rapid evaluation of the dynamic response of the surrounding rock under tunnel blasting excavation.

[0047] The present invention associates physical and mechanical parameters, blasting parameters, and surrounding rock dynamic response data under blasting excavation with tunnel surrounding rock safety thresholds through a Gaussian process machine learning model. The safety assessment process is simplified, and the safety assessment of surrounding rock under blasting excavation can be output by simply inputting design information and physical and mechanical parameters into the program, thereby improving the efficiency of safety assessment of tunnel surrounding rock dynamic response under blasting excavation.

[0048] In another aspect of the present invention, a terminal is provided. According to an embodiment of the present invention, the terminal includes a memory, a processor, and a surrounding rock dynamic response evaluation program under blasting excavation of a hard rock tunnel stored in the memory and executable on the processor, and when the processor executes the surrounding rock dynamic response evaluation program under blasting excavation of a hard rock tunnel, the steps of the surrounding rock dynamic response evaluation method under blasting excavation of a hard rock tunnel are implemented.

[0049] In another aspect of the present invention, a computer-readable storage medium is provided. According to an embodiment of the present invention, a program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel is stored on the computer-readable storage medium, and when the program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel is executed by a processor, the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel are implemented.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. The present invention constructs a three-dimensional tunnel blasting excavation grid model based on the tunnel design cross-section diagram and the terrain cross-section, which has higher accuracy than the simplified model and the simple tunnel cross-section diagram model.

[0052] 2. The three-dimensional tunnel blasting excavation grid model is divided into groups, the analysis areas are determined, and parameters are assigned respectively, which has higher authenticity than homogeneous or single material models.

[0053] 3. The present invention can use a pre-trained evaluation model to intelligently analyze the deformation data of the surrounding rock response to blasting and excavation of three-dimensional tunnels, and automatically output the safety assessment results. Based on the results, it is possible to predict the safety of the dynamic response of the surrounding rock to blasting and excavation of large tunnels, and quickly predict whether the tunnel construction is safe, thereby ensuring the safety of tunnel construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1This is a flow chart of a method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel in Example 1 of the present invention;

[0055] Figure 2 This is a flow chart of a method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel in Example 2 of the present invention;

[0056] Figure 3 This is a flow chart of a method for constructing a Gaussian process machine learning evaluation model in Example 3 of the present invention;

[0057] Figure 4 Schematic diagram of a system for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel in Example 4 of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Example 1

[0060] See also Figure 1 A method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel comprises the following steps:

[0061] S1. Obtain tunnel design data and geological section information.

[0062] Tunnel design data and geological section information include tunnel section design, tunnel construction process information, geological survey information, and stratigraphic section information. It should be noted that since the cross-sectional shape and stratum distribution in underground tunnel blasting will have a great impact on the blasting shock wave, it is necessary to accurately model the tunnel according to the tunnel design data and geological section information. Otherwise, the constructed three-dimensional tunnel blasting excavation grid model will be distorted.

[0063] S2. Obtain the physical and mechanical parameters of the hard rock tunnel.

[0064] The physical and mechanical parameters include: elastic modulus, unit: GPa; Poisson's ratio; cohesion, unit: MPa; friction angle, unit: degree; tensile strength, unit: MPa; density, unit: kg·m. It should be noted that the physical and mechanical parameters: elastic modulus, Poisson's ratio, cohesion, friction angle, are obtained through triaxial compression test, and are calculated by processing the triaxial compression test data.

[0065] The triaxial compression test data is processed through the stress-strain curve, and the tangent slope of the stress-strain curve of the compressive strength value at 50% stress is taken as the elastic modulus. Calculate the Poisson's ratio, ε h — is the transverse strain, ε d — is the axial strain.

[0066] The calculation of the cohesion and internal friction angle is done by drawing a fitting curve with the triaxial test confining pressure as the horizontal axis value and the triaxial compressive strength as the vertical axis value. Calculate the cohesion and friction angle. m and b are the slope and intercept of the fitting curve respectively. C is the cohesion and friction angle. is the friction angle. Density is calculated by the product method based on mass and volume. It is calculated that m z is the mass of the surrounding rock sample, and V is the volume of the surrounding rock sample.

[0067] S3. Obtain blasting parameters.

[0068] The blasting parameters include the vibration frequency of the tunnel structure, and the blasting vibration data of the tunnel structure is obtained by monitoring the on-site blasting vibration. The blasting vibration monitoring adopts a blasting vibrometer, which consists of three parts: a three-dimensional sensor, a recording unit, and a software processing system. The sampling frequency of the blasting vibrometer is 1-50kHz, the frequency response range is 0-10kHz, and it can trigger recording continuously with a recording accuracy of 0.01cm / s. The vibration sensor used is a three-dimensional vibration velocity sensor, which can simultaneously monitor the axial, vertical, and radial vibration velocities of the tunnel structure at the measuring point. After the blasting occurs, the sensor can collect the signal of the blasting vibration, and the recording unit can store the signal in an electrical signal. The blasting vibration monitoring data is subjected to noise reduction processing using the BVAnalysis software, and the blasting parameters (vibration frequency) are finally obtained. Provide data for the numerical simulation of blasting excavation. The present invention can more accurately reflect the blasting parameters under the actual blasting excavation by denoising the blasting vibration monitoring data, and improve the evaluation accuracy of subsequent steps.

[0069] S4. Construct a three-dimensional tunnel blasting excavation grid model.

[0070] According to the tunnel design information and geological survey data, the tunnel design section design drawing and geological section drawing are imported into the raino modeling software, and the three-dimensional tunnel excavation entity model is quickly constructed through the raino stretch entity command combined with the griddle meshing plug-in. The three-dimensional tunnel blasting excavation grid model established by the present invention based on the tunnel design section and geological section has a high degree of conformity with the actual situation, can meet the calculation accuracy, reflect the actual macroscopic properties, and further ensure the final simulation quality.

[0071] S5. Import physical and mechanical parameters and blasting parameters.

[0072] The three-dimensional tunnel blasting excavation grid model, blasting parameters and physical and mechanical parameters are imported into the finite difference software FLAC3D. The three-dimensional tunnel blasting excavation grid model constructed by raino is imported into FLAC3D using the grid command, and then grouped according to the construction plan and surrounding rock properties. According to the different groups, the physical and mechanical parameters are assigned to the corresponding groups.

[0073] S6. Calculate the surrounding rock response results under blasting excavation.

[0074] The three-dimensional tunnel blasting excavation grid model is used for analysis and calculation. The calculation of FLAC 3D simulated tunnel blasting excavation can be divided into the following steps:

[0075] (1) Select the dynamic calculation mode and define the constitutive model and material physical parameters;

[0076] (2) Define the boundary conditions and initial conditions required for the calculation;

[0077] (3) Perform initialization calculations to obtain the initial equilibrium state, i.e., the original rock stress state before excavation;

[0078] (4) Set the boundary conditions for dynamic calculation and the required damping;

[0079] (5) Blasting parameters are applied, blasting excavation calculation and analysis are performed, and the dynamic response data of the surrounding rock after blasting excavation is obtained.

[0080] It should be noted that the blasting parameter application process is as follows: turn on the FLAC3D dynamic analysis switch, set the dynamic boundary conditions, use the fish language, nest the blasting parameters (vibration frequency) in each excavation cycle, activate the dynamic analysis and turn on the statics switch during blasting excavation, the rock and soil vibration generated by the blasting continuously propagates and reflects in the grid to achieve the application of blasting parameters (vibration frequency), and use the model null command to perform excavation. The surrounding rock dynamic response data is obtained by dynamic analysis and calculation through FLAC3D to obtain the surrounding rock dynamic response data under blasting excavation.

[0081] S7. Data processing.

[0082] The dynamic response data of the surrounding rock under blasting excavation are processed. The dynamic response data include vibration velocity, vibration frequency, displacement deformation, and the tensile stress, displacement deformation and safety threshold are compared and analyzed. The safety evaluation threshold includes the safety threshold of tensile stress and displacement deformation. Tensile stress safety threshold: combined with the maximum tensile stress theory, when the maximum tensile stress exceeds the allowable tensile stress of the tunnel structure, it is considered unsafe. The vibration velocity can be converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress, and X is vibration velocity. The maximum tensile stress is used as the safety threshold of stress. If it does not exceed, it is judged to be safe and recorded as 0. If it exceeds, it is judged to be unsafe and recorded as 1. It is necessary to improve the blasting construction plan and strengthen support.

[0083] Safety threshold of displacement deformation: According to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of displacement deformation. If it does not exceed the limit, it is judged to be safe and recorded as 0. If it exceeds the limit, it is judged to be unsafe and recorded as 1, and the blasting construction plan needs to be improved and the support needs to be strengthened.

[0084] Example 2

[0085] See also Figure 2 , a method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel, comprising the following steps:

[0086] Step 01: Obtain first information.

[0087] The first information includes tunnel design information, geological section information, and physical and mechanical parameters (elastic modulus, Poisson's ratio, cohesion, friction angle, density).

[0088] Step 02: Output the second information.

[0089] According to the first information, the second information is output, and the second information includes vibration velocity and displacement deformation.

[0090] Step 03: Output the third information.

[0091] According to the second information, the third information is output, and the third information includes safety evaluation results 0 and 1.

[0092] Step 04: Comprehensive evaluation.

[0093] The third information output result is evaluated for safety. A1 safety evaluation: combined with the maximum tensile stress theory, when the maximum tensile stress exceeds the allowable tensile stress of the tunnel structure, it is considered unsafe. The vibration velocity can be converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, and b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress. The maximum tensile stress is used as the safety threshold of stress. If it does not exceed, it is considered safe and recorded as 0. If it exceeds, it is considered unsafe and recorded as 1. It is necessary to improve the blasting construction plan and strengthen the support.

[0094] A2 Safety evaluation: According to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of displacement deformation. If it does not exceed the limit, it is judged to be safe and recorded as 0. If it exceeds the limit, it is judged to be unsafe and recorded as 1. It is necessary to improve the blasting construction plan and strengthen the support.

[0095] The evaluation function is used, and the formula: Z = A1 + A2 is used, where A1 and A2 correspond to the evaluation results of stress and displacement deformation respectively. The safety assessment result is output, and tensile stress and displacement deformation are used as evaluation indicators. If the evaluation indicator exceeds the limit value, a warning message is output, and unsafe: 1 is output. If all predicted values ​​are within the safety range, safe: 0 is output, thereby realizing a rapid evaluation of the dynamic response of the surrounding rock under tunnel blasting excavation.

[0096] Example 3

[0097] A Gaussian process machine learning evaluation model, the method for evaluating the dynamic response of surrounding rock of a tunnel under blasting excavation in Example 2 is implemented by training a Gaussian process machine learning evaluation model. Gaussian process regression is a non-parametric Bayesian regression method. Its core idea is to model data through Gaussian processes to provide prediction values ​​and their uncertainties. Gaussian processes are used to define a function distributed in the input space. What the model learns is the probability distribution relationship between input data and output data. Figure 3 As shown, the construction of the Gaussian process machine learning evaluation model includes the following steps:

[0098] S11. Data preparation

[0099] The dynamic response data of surrounding rock under blasting excavation are used to train the model.

[0100] Define X variables: including physical and mechanical parameters (elastic modulus, Poisson's ratio, cohesion, friction angle, density), tunnel design parameters (design section, geological section), and blasting parameters (vibration frequency).

[0101] Define the Y variable: Contains the target data, that is, the two predicted values ​​corresponding to each set of features: vibration velocity and displacement deformation.

[0102] S12. Define the kernel

[0103] Two kernels are used to define the scale and smoothness of the prediction function. ConstantKernel: used to define the scale of the function values ​​and adjust the overall magnitude of the prediction results. RBF (Radial Basis Function Kernel): used to define the smoothness of the function. It measures the similarity between data points and controls the smoothness of the prediction.

[0104] S13. Model training

[0105] Create two Gaussian process regression models, each predicting a target variable (vibration velocity, displacement deformation). The model training process includes: Optimizing kernel parameters: Optimizing kernel parameters by maximizing the marginal log-likelihood function p(x) = ∫p(x,z)dz to better fit the training data. Fitting data: Input the X variable and Y variable data into the model for training.

[0106] S14. Dynamic response data prediction

[0107] Input a new set of X variable data for prediction, and obtain 2 predicted values ​​of Y variable and the corresponding standard deviation (uncertainty). More accurately predict the dynamic response data of surrounding rock under blasting excavation. The predicted data of dynamic response of surrounding rock under blasting excavation: calculate the predicted data of dynamic response of surrounding rock under blasting excavation according to different weights of physical and mechanical parameters and blasting parameters. This calculation matrix is ​​used to achieve:

[0108]

[0109] The x1 corresponds to the elastic modulus, x2 corresponds to the Poisson's ratio, x3 corresponds to the internal friction angle, x4 corresponds to the density, and x5 corresponds to the vibration frequency. y1 corresponds to the vibration velocity, and y2 corresponds to the displacement deformation; λ 11 is the weight calculation parameter of elastic modulus and vibration velocity, λ 12 is the weight calculation parameter of Poisson's ratio and vibration velocity, λ 13 is the weight calculation parameter of internal friction angle and vibration velocity, λ 14 is the weight calculation parameter of density and vibration speed, λ 15 is the weight calculation parameter of vibration frequency and vibration speed, λ 21 is the weight calculation parameter of elastic modulus and displacement deformation, λ 22 is the weight calculation parameter of Poisson's ratio and displacement deformation, λ 23 is the weight calculation parameter of internal friction angle and displacement deformation, λ 24 is the weight calculation parameter of density and displacement deformation, λ 25 Calculate the weight parameters for vibration frequency and displacement deformation.

[0110] The calculation matrix is ​​introduced into the Gaussian training model, and the prediction of the dynamic response of the surrounding rock under blasting excavation is achieved by training the Gaussian process machine learning model.

[0111] S15. Evaluation and classification

[0112] A1 Safety evaluation: Combined with the maximum tensile stress theory, when the maximum tensile stress exceeds the allowable tensile stress of the tunnel structure, it is considered unsafe. The vibration velocity can be converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, and b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress. The maximum tensile stress is used as the safety threshold of stress. If it does not exceed, it is considered safe and recorded as 0. If it exceeds, it is considered unsafe and recorded as 1, and the blasting construction plan needs to be improved to strengthen support.

[0113] A2 Safety evaluation: According to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of displacement deformation. If it does not exceed the limit, it is judged to be safe and recorded as 0. If it exceeds the limit, it is judged to be unsafe and recorded as 1. It is necessary to improve the blasting construction plan and strengthen the support.

[0114] Using the evaluation function, the formula: Z = A1 + A2, where A1 and A2 correspond to the evaluation results of tensile stress and displacement deformation respectively: tensile stress and displacement deformation are used as evaluation indicators. If the evaluation indicators exceed the limit value, a warning message is output and unsafe: 1 is output. If all predicted values ​​are within the safe range, safe: 0 is output, thereby realizing a rapid evaluation of the dynamic response of the surrounding rock under tunnel blasting excavation.

[0115] Example 4

[0116] like Figure 4 As shown, a system for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel comprises: an input unit, an output unit, a processor, and a memory. The input unit, the output unit, the processor, and the memory are interconnected, and the memory contains program instructions, and the program instructions are used to execute the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel in China in Example 2.

[0117] The input unit is used to execute: inputting the first information including tunnel design information, geological section information, and physical and mechanical parameters (elastic modulus, Poisson's ratio, cohesion, friction angle, density).

[0118] The output unit is used to execute: output second information according to the first information, the second information including vibration speed and displacement deformation.

[0119] Processor: Performing evaluation according to the second information.

[0120] Memory: used to store the output second information and third information.

[0121] The system for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel of the present invention has a compact structure and stable performance, and can stably execute the method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel of the present invention, further improving the overall applicability and practical application capability of the present invention.

[0122] Example 5

[0123] A terminal includes a memory, a processor, and a program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel, which is stored in the memory and can be run on the processor. When the processor executes the program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel, the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel described in Example 2 are implemented.

[0124] Example 6

[0125] A computer-readable storage medium stores a program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel. When the program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel is executed by a processor, the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel described in Example 2 are implemented.

[0126] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel, characterized in that: The following steps are involved: S1. Obtain tunnel design data and geological section information; S2. Obtain the physical and mechanical parameters of the hard rock tunnel; S3, obtaining blasting parameters; S4, constructing a three-dimensional hard rock tunnel blasting excavation grid model based on the tunnel design data and geological section information obtained in step S1; S5, importing the three-dimensional tunnel blasting excavation grid model, blasting parameters, and physical and mechanical parameters into the finite difference software; S6. Analyze and calculate the three-dimensional tunnel blasting excavation grid model through the dynamic calculation module built into the finite difference software to obtain the dynamic response data of the surrounding rock under blasting excavation; S7. Compare and analyze the surrounding rock dynamic response data under the blasting excavation with the safety assessment threshold.

2. The method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 1, characterized in that: In step S1, the tunnel design data and geological section information include tunnel section design information, tunnel construction process information, geological survey information, and stratum section information; In step S2, the physical and mechanical parameters include elastic modulus, Poisson's ratio, cohesion, friction angle, tensile strength, and density; In step S3, the blasting parameters include the vibration frequency of the hard rock tunnel.

3. The method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 1 is characterized in that: Step S4 is as follows: import the tunnel design data and geological section information into the raino modeling software, and construct a three-dimensional hard rock tunnel blasting excavation grid model through the raino stretch entity command combined with the griddle meshing plug-in.

4. The method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 1 is characterized in that: In step S6, the finite difference software is FLAC 3D, and the analysis and calculation of the dynamic response data of the surrounding rock under blasting excavation using the finite difference software includes the following steps: S601, select the dynamic calculation mode, define the constitutive model and material physical parameters; S602, defining boundary conditions and initial conditions required for calculation; S603, performing initialization calculation to obtain the original rock stress state before excavation; S604, setting dynamic calculation boundary conditions and required damping; S605, applying blasting parameters, performing blasting excavation calculation and analysis, and obtaining surrounding rock dynamic response data after blasting excavation.

5. The method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 1, characterized in that: In step S7, the safety evaluation threshold includes the safety threshold of tensile stress and displacement deformation; The comparative analysis method of tensile stress safety threshold is as follows: the vibration velocity is converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress, X is vibration velocity, and the maximum tensile stress is used as the safety threshold of stress. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1; The comparative analysis method of the displacement deformation safety threshold is as follows: according to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of the displacement deformation. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1.

6. A method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel, characterized in that: The method for calculating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to any one of claims 1 to 5 is used for evaluation, and specifically comprises the following steps: Step 01, obtaining first information: the first information includes tunnel design information, geological section information, and physical and mechanical parameters; Step 02, outputting second information: outputting second information according to the first information, the second information including vibration velocity and displacement deformation of the hard rock tunnel; Step 03, outputting third information: outputting third information according to the second information, the third information including the safety evaluation result; Step 04: Comprehensive evaluation: Output the third information for security assessment.

7. The method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 6, characterized in that: The evaluation method is implemented through Gaussian process machine learning evaluation model training.

8. The method for evaluating the dynamic response of surrounding rock during blasting excavation of a hard rock tunnel according to claim 7, characterized in that: The construction of the Gaussian process machine learning evaluation model includes the following steps: S11. Data preparation Define X variables: including physical and mechanical parameters, tunnel design parameters, and blasting parameters; Define the Y variable: it contains the target data, that is, the two predicted values ​​corresponding to each set of features: vibration velocity and displacement deformation; S12. Define the kernel Two kernels are used to define the scale and smoothness of the prediction function. The constant kernel is used to define the scale of the function value and adjust the overall amplitude of the prediction result. The radial basis function kernel is used to define the smoothness of the function. S13. Model training Two Gaussian process regression models were created, each predicting a target variable Y; The model training process includes: optimizing kernel parameters and fitting data; S14. Dynamic response data prediction Input a new set of X variable data for prediction, and obtain two predicted values ​​of Y variable and the corresponding standard deviation; calculate the predicted data of surrounding rock dynamic response under blasting excavation according to different weights of physical and mechanical parameters and blasting parameters; S15. Evaluation and classification Tensile stress safety evaluation: The vibration velocity is converted into tensile stress through the formula σ=aX+b, where σ is tensile stress, a is the fitting slope of vibration velocity and tensile stress, and b is the fitting intercept parameter in the relationship between vibration velocity and tensile stress; the maximum tensile stress is taken as the safety threshold of stress. If it does not exceed, it is judged to be safe and recorded as 0; if it exceeds, it is judged to be unsafe and recorded as 1, and it is necessary to improve the blasting construction plan and strengthen the support; Safety evaluation of displacement deformation: According to the reserved deformation required by the design, the designed reserved deformation is used as the safety threshold of displacement deformation. If it does not exceed, it is considered safe and recorded as 0; if it exceeds, it is considered unsafe and recorded as 1, and the blasting construction plan needs to be improved and the support needs to be strengthened; The evaluation function is used with the formula: Z=A1+A2, where A1 and A2 correspond to the evaluation results of tensile stress and displacement deformation respectively. If the evaluation index exceeds the limit value, a warning message is output and unsafe: 1 is output; if all predicted values ​​are within the safe range, safe: 0 is output, thereby realizing a rapid evaluation of the dynamic response of the surrounding rock under tunnel blasting excavation.

9. A terminal, characterized in that: The method comprises a memory, a processor and a program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel, which is stored in the memory and can be run on the processor. When the processor executes the program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel, the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel described in claim 6 are implemented.

10. A computer-readable storage medium, characterized in that: A computer-readable storage medium stores a program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel. When the program for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel is executed by a processor, the steps of the method for evaluating the dynamic response of surrounding rock under blasting excavation of a hard rock tunnel described in claim 6 are implemented.

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