A blasting simulation method suitable for fractured and broken surrounding rock tunnel

Abstract

The present application relates to the technical field of blasting simulation, in particular to a blasting simulation method suitable for a tunnel with fractured and broken surrounding rock, comprising: obtaining tunnel geometric characteristics and generating a tunnel three-dimensional model; obtaining surrounding rock fracture characteristic data and basic physical and mechanical parameters and inputting them into a numerical simulation software; according to blast hole arrangement parameters, marking blast hole positions in the tunnel three-dimensional model and associating the blast hole arrangement parameters with the basic physical and mechanical parameters in the numerical simulation software to obtain key feature combinations; based on the key feature combinations, simulating dynamic response characteristics of the surrounding rock under the action of blasting load in the blasting process in the numerical simulation software; and obtaining surrounding rock dynamic response simulation results according to the dynamic response characteristics. The present application realizes accurate simulation of the tunnel blasting process, helps to optimize the blasting design, improves construction safety and efficiency, and provides reliable technical support for tunnel engineering.

Description

Technical Field

[0001] The invention relates to the technical field of blasting simulation, in particular to a blasting simulation method suitable for a tunnel with fractured and broken surrounding rock. Background Art

[0002] A fractured rock tunnel is one excavated within a fractured zone (a region of broken rock). The surrounding rock, defined as the rock mass within a certain range surrounding the tunnel, plays a crucial supporting role in tunnel stability. Blasting simulations for fractured rock tunnels can predict blasting effects and optimize blasting parameters (such as hole diameter, hole spacing, charge, and detonation sequence), thereby improving blasting efficiency and minimizing excessive rock fragmentation and impact on surrounding structures.

[0003] The surrounding rock of a tunnel constructed in fractured or crushed rock has the following characteristics: Poor rock integrity: The surrounding rock is often located within fault or fracture zones, dissected by multiple joints and fissures, severely damaging its integrity and presenting a fragmented and loose state. Uneven block size: The rock blocks in the surrounding rock vary in size, ranging from a few centimeters to several meters, and the contact relationships between the blocks are complex, potentially forming point, line, or surface contacts. Well-developed fractures: The surrounding rock has numerous fractures and an uneven distribution, with large variations in strike, dip, and spacing. These fractures may interconnect, forming a complex fracture network. Low strength: Due to the fractured rock mass, its overall strength is significantly reduced, with mechanical properties such as compressive strength and shear strength far lower than those of intact rock. Complex deformation characteristics: Under load, the deformation characteristics of fractured surrounding rock are complex, exhibiting nonlinear deformation and a low deformation modulus, making it susceptible to plastic deformation. Poor stability: Fractured surrounding rock exhibits poor stability and is prone to local or global instability under external loads (such as blasting loads and in-situ stresses). In summary, tunnels with fractured and broken surrounding rock are relatively complex and have poor stability. Therefore, how to ensure that the simulation results can truly reflect the dynamic response of the surrounding rock during the actual blasting process is a problem that needs to be solved. Summary of the Invention

[0004] The purpose of the present invention is to provide a blasting simulation method suitable for tunnels with fractured surrounding rock, which realizes accurate simulation of the tunnel blasting process, helps to optimize blasting design, improve construction safety and efficiency, and provide reliable technical support for tunnel engineering.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A blasting simulation method applicable to a tunnel with fractured surrounding rock, comprising:

[0007] Obtain tunnel geometric features and generate a three-dimensional tunnel model;

[0008] Obtaining surrounding rock fracture characteristic data and basic physical and mechanical parameters, and inputting them into numerical simulation software, wherein the surrounding rock fracture characteristic data includes crack distribution, fragmentation degree, and rock mass structure information, and the basic physical and mechanical parameters include dynamic elastic modulus, dynamic Poisson's ratio, and damping characteristic data;

[0009] Marking blasthole positions in the three-dimensional tunnel model according to blasthole arrangement parameters, and correlating the blasthole arrangement parameters with basic physical and mechanical parameters in the numerical simulation software to obtain a key feature combination;

[0010] Based on the key feature combination, the dynamic response characteristics of the surrounding rock under the blasting load during the blasting process are simulated in the numerical simulation software;

[0011] According to the dynamic response characteristics, a surrounding rock dynamic response simulation result is obtained.

[0012] Optionally, obtaining tunnel geometric features and generating a 3D tunnel model includes:

[0013] According to the tunnel design drawings, obtain tunnel section type data and positioning point coordinate information;

[0014] Preprocessing the positioning point coordinate information to remove noise and incomplete data, and matching the tunnel section type data with the preprocessed positioning point coordinate information;

[0015] Generate a continuous tunnel centerline between the coordinate information of the positioning points through a spatial interpolation algorithm;

[0016] According to the matched tunnel section type data and the pre-processed positioning point coordinate information, the tunnel section type data is staked out with the center line as the reference to construct a tunnel surface grid;

[0017] A three-dimensional reconstruction algorithm is used to convert the tunnel surface mesh into a solid model to generate the three-dimensional model of the tunnel.

[0018] Optionally, the rock mass structure information includes rock bedding surface inclination data and thickness data.

[0019] Optionally, associating the blasthole arrangement parameters with basic physical and mechanical parameters in the numerical simulation software to obtain a key feature combination includes:

[0020] Using a data association algorithm to match the blasthole arrangement parameters with the basic physical and mechanical parameters in the numerical simulation software to establish a parameter mapping relationship;

[0021] generating a correlation data set of blasthole arrangement and mechanical parameters according to the parameter mapping relationship;

[0022] Converting the associated data set into a format suitable for input into the numerical simulation software to generate a simulation input file;

[0023] A machine learning algorithm is used to extract features from the associated data set in the simulation input file to obtain the key feature combination.

[0024] Optionally, the dynamic response characteristics of the surrounding rock under the blasting load during the blasting process simulated in the numerical simulation software include:

[0025] generating simulation data of blasting load distribution and detonation wave propagation path in the numerical simulation software according to the key feature combination;

[0026] Determine whether the simulation data of the blasting load distribution and the blast wave propagation path are consistent with expectations. If so, continue to simulate the dynamic response characteristics of the surrounding rock under the action of the blasting load. If not, optimize the simulation data of the blasting load distribution and the blast wave propagation path.

[0027] Optionally, the simulation data for optimizing the blast load distribution and the detonation wave propagation path includes:

[0028] According to the key feature combination, the mapping relationship between the blasthole arrangement and the mechanical parameters is loaded into the numerical simulation software to generate initial simulation data of the blasting load distribution and the detonation wave propagation path;

[0029] Using a machine learning algorithm, feature extraction is performed on the initial simulation data to obtain relevant features of the blasting load distribution and the detonation wave propagation path;

[0030] According to the relevant characteristics, the input parameters of the numerical simulation software are adjusted to optimize the simulation data of the blasting load distribution and the detonation wave propagation path.

[0031] Optionally, obtaining surrounding rock dynamic response simulation results according to the dynamic response characteristics includes:

[0032] Obtaining stress distribution data under the action of blasting load, calculating the deformation of the surrounding rock during the blasting process based on the stress distribution data, and generating a deformation distribution result;

[0033] Using machine learning algorithms, we extract features from the deformation distribution results and obtain quantitative indicators of the degree of fragmentation.

[0034] If the quantitative index of the degree of fragmentation exceeds a preset threshold, the blasting load parameters are adjusted, the stress distribution and deformation are re-obtained, and the surrounding rock dynamic response simulation results are updated.

[0035] Optionally, generating the three-dimensional tunnel model includes dividing the three-dimensional tunnel model into a plurality of small units according to the tunnel section type data.

[0036] The beneficial effects of the present invention are as follows: the present invention discloses a blasting simulation method suitable for tunnels with fractured and broken surrounding rocks. The method first constructs a three-dimensional model based on tunnel design drawings and geological survey data, and integrates the mechanical parameters of the surrounding rock. Then, the blast hole positions are marked in the model according to the blasting design plan and associated with the surrounding rock parameters. The load distribution and blast wave propagation path during the blasting process are simulated by numerical simulation software to obtain the dynamic response characteristics of the surrounding rock, including stress distribution, deformation and degree of fragmentation. Finally, the simulation results are compared with the measured data to verify the accuracy. The present invention realizes the accurate simulation of the tunnel blasting process, which helps to optimize the blasting design, improve construction safety and efficiency, and provide reliable technical support for tunnel engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 The present invention is a flowchart of a blasting simulation method suitable for a tunnel with fractured and broken surrounding rock. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] When simulating blasting in a tunnel with fractured surrounding rock, the primary task is to establish an accurate three-dimensional numerical model. This model must fully consider the tunnel's geometric characteristics, including cross-sectional shape, dimensions, and orientation. Furthermore, the fracture and fragmentation characteristics of the surrounding rock are crucial factors in the model, requiring a detailed description of the distribution of cracks, degree of fragmentation, and rock mass structure. The arrangement of blastholes and charging parameters are also crucial. The spacing, depth, charge, and charging method of the blastholes must all be accurately reflected in the model.

[0042] Next, determining the mechanical parameters of the surrounding rock is a crucial step in the simulation process. These parameters, including dynamic elastic modulus, dynamic Poisson's ratio, and damping, are typically obtained through laboratory or field testing. Laboratory testing may involve dynamic loading tests on rock samples to determine their dynamic response characteristics under blasting loads. Field testing may include seismic and acoustic wave testing to determine the dynamic parameters of the surrounding rock in actual environments. The accuracy of these parameters directly impacts the reliability of the numerical simulation results.

[0043] After the model is established and its parameters determined, the blasting parameters are loaded into the numerical model to perform a numerical simulation of the blasting process. This process requires incorporating factors such as the blasting load, the blast wave propagation path, and the dynamic response of the surrounding rock into the model to simulate the stress distribution, deformation, and fragmentation of the surrounding rock during the blasting process. The complexity of this step lies in accurately describing the spatiotemporal distribution of the blasting load and its interaction with the surrounding rock, ensuring that the simulation results truly reflect the dynamic response of the surrounding rock during the actual blasting process.

[0044] like Figure 1 As shown, this embodiment provides a blasting simulation method applicable to a tunnel with fractured surrounding rock, including:

[0045] Obtain tunnel geometric features and generate a three-dimensional tunnel model;

[0046] Obtain surrounding rock fracture characteristic data and basic physical and mechanical parameters and input them into numerical simulation software. The surrounding rock fracture characteristic data includes crack distribution, fragmentation degree and rock mass structure information, and the basic physical and mechanical parameters include dynamic elastic modulus, dynamic Poisson's ratio and damping characteristic data.

[0047] Based on the blasthole layout parameters, the blasthole locations are marked in the 3D tunnel model. The blasthole layout parameters are then correlated with the basic physical and mechanical parameters in the numerical simulation software to obtain key feature combinations.

[0048] Based on the combination of key features, the dynamic response characteristics of the surrounding rock under the blasting load during the blasting process are simulated in numerical simulation software;

[0049] According to the dynamic response characteristics, the dynamic response simulation results of the surrounding rock are obtained.

[0050] In this embodiment, the LS-DYNA numerical simulation method is adopted.

[0051] Furthermore, obtaining the geometric features of the tunnel and generating a 3D model of the tunnel include:

[0052] According to the tunnel design drawings, obtain tunnel section type data and positioning point coordinate information;

[0053] Preprocess the positioning point coordinate information to remove noise and incomplete data, and match the tunnel section type data with the preprocessed positioning point coordinate information;

[0054] Generate a continuous tunnel centerline between the positioning point coordinates using a spatial interpolation algorithm;

[0055] Based on the matched tunnel section type data and the pre-processed positioning point coordinate information, the tunnel section type data is staked out with the center line as the reference to construct the tunnel surface grid;

[0056] The 3D reconstruction algorithm is used to transform the tunnel surface mesh into a solid model to generate a 3D tunnel model.

[0057] Specifically, modeling software can read design drawings in a variety of formats, such as scanned vector graphics and 3D laser point clouds. For example, in a tunnel project, the point cloud data captured by a scanner contains geometric information about the tunnel wall surface. Software processing can extract cross-sectional contours. Cross-sectional shapes can be classified based on typical features such as arches, circles, and horseshoes. For example, in a mountain tunnel project, control points are set every 50 meters, and their 3D coordinates are collected to obtain the coordinate information of the positioning points. Data preprocessing eliminates points with deviations due to measurement errors and estimates missing points. Matching tunnel cross-sectional data with spatial locations requires establishing a unified coordinate system. For example, in a highway tunnel, pile numbers are used as longitudinal positioning datums. The shape parameters of each cross-section are mapped to their location, forming a complete spatial data set. Spline interpolation can be used to generate centerlines. For example, in a railway tunnel project, discrete control points are interpolated using cubic spline functions to generate a smooth spatial curve, ensuring continuity and gentle curvature changes. Section lofting is a key step in converting a two-dimensional outline into a three-dimensional entity. The standard section is rotated and translated along the center line, and a section outline is generated every one meter to form a dense spatial skeleton. The construction of the grid model needs to consider the size and shape of the grid unit. The surface grid is generated by connecting adjacent section contour points, which must ensure the regularity of the grid and reflect the actual form of the structure. In the process of reconstructing the solid model, the topological relationship of the surface grid needs to be processed. Taking the three-dimensional reconstruction of a highway tunnel as an example, a grid filling algorithm is used to generate a volume grid to ensure that the tunnel wall thickness meets the design requirements, and local encryption processing is performed on special parts such as portals and cross passages to improve the accuracy of the model.

[0058] Furthermore, the rock mass structure information includes rock layer inclination data and thickness data.

[0059] Specifically, the surrounding rock fracture characteristic data, including crack distribution, degree of fragmentation and rock structure information, were extracted from the on-site geological survey report. Combined with the dynamic elastic modulus, dynamic Poisson's ratio and damping characteristic data obtained from the laboratory dynamic loading test, the data were organized into mechanical parameters and input into the numerical simulation software.

[0060] The distribution of surrounding rock fractures in geological survey reports typically includes information such as joint strike and dip, while the degree of fragmentation is related to the rock integrity index and fracture zone width. For example, in a tunnel project, where the surrounding rock is primarily granite, image processing techniques were used to extract fracture characteristics from project photographs. The results revealed a primary joint strike of 45 degrees northeast, a dip of 60 degrees, and a rock integrity index of 0.65. Laboratory dynamic loading tests employed stress-strain control, obtaining dynamic parameters through cyclic loading. Rock samples from a tunnel project were tested at a loading frequency of 1 Hz and a stress amplitude of 10 MPa. After data cleaning and removal of outliers and noise, the collected stress-strain curves yielded a dynamic modulus of 35 GPa and a dynamic Poisson's ratio of 0.25.

[0061] Furthermore, the blasthole arrangement parameters are associated with the basic physical and mechanical parameters in the numerical simulation software to obtain the key feature combinations including:

[0062] The data association algorithm is used to match the blasthole arrangement parameters with the basic physical and mechanical parameters in the numerical simulation software to establish a parameter mapping relationship;

[0063] Generate a data set of correlation between blasthole arrangement and mechanical parameters based on parameter mapping relationship;

[0064] Convert the associated data set into the format for input into numerical simulation software to generate simulation input files;

[0065] Machine learning algorithms are used to extract features from the associated data sets in the simulation input files to obtain key feature combinations.

[0066] Specifically, according to the blasting design plan, blasthole layout parameters, including blasthole spacing, depth, charge, and charging method, are loaded. The blasthole locations are then marked in the 3D tunnel model. For typical tunnel projects, blasthole spacing is typically 0.8 to 1.2 meters. The blasthole depth is determined based on the surrounding rock grade and the excavation cycle footage, generally ranging from 1.8 to 2.4 meters. The charge per hole is approximately 1.2 to 1.8 kilograms, and the charging method is either continuous or intermittent. The spatial distribution of all blastholes is then marked in the 3D tunnel model based on the designed blasthole location coordinates. A data association algorithm is used to establish a mapping between the blasthole layout parameters and the surrounding rock mechanical parameters.

[0067] Converting linked datasets to a format recognizable by simulation software requires processing different types of data. For example, converting blasthole spatial coordinates to grid node coordinates, discretizing continuous charge structures into unit charge parameters, and assigning surrounding rock mechanical parameters to corresponding computational units. Typical conversion results include: grid unit numbering for blasthole locations, charge density distribution, and unit material parameters. Feature extraction algorithms analyze key characteristics of blasthole layout and surrounding rock parameters, including the spatial distribution of blasthole clusters, the energy distribution of charge structures, and the strength and deformation characteristics of the surrounding rock.

[0068] Furthermore, the dynamic response characteristics of the surrounding rock under the blasting load during the blasting process simulated in the numerical simulation software include:

[0069] Based on the combination of key features, simulation data of blasting load distribution and detonation wave propagation path are generated in numerical simulation software;

[0070] Determine whether the simulation data of blasting load distribution and blast wave propagation path are consistent with expectations. If so, continue to simulate the dynamic response characteristics of the surrounding rock under the action of blasting load. If not, optimize the simulation data of blasting load distribution and blast wave propagation path.

[0071] Furthermore, simulation data for optimizing blast load distribution and detonation wave propagation path include:

[0072] Based on the key feature combination, the mapping relationship between blasthole arrangement and mechanical parameters is loaded into the numerical simulation software to generate the initial simulation data of blasting load distribution and detonation wave propagation path;

[0073] Using machine learning algorithms, we extract features from the initial simulation data to obtain relevant characteristics of the blast load distribution and detonation wave propagation path.

[0074] According to the relevant characteristics, the input parameters of the numerical simulation software are adjusted to optimize the simulation data of the blasting load distribution and the detonation wave propagation path.

[0075] Specifically, when validating simulation data for blast load distribution and detonation wave propagation paths, the expected range is typically set at 200 to 500 MPa for explosive detonation pressure and 4,000 to 6,000 km / s for wave propagation velocity. If the actual simulated values ​​are 350 MPa and 5,000 km / s, the data is considered within the expected range.

[0076] Furthermore, according to the dynamic response characteristics, the dynamic response simulation results of the surrounding rock are obtained, including:

[0077] Obtain stress distribution data under blasting load, calculate the deformation of surrounding rock during blasting based on the stress distribution data, and generate deformation distribution results;

[0078] Using machine learning algorithms, we extract features from the deformation distribution results and obtain quantitative indicators of the degree of fragmentation.

[0079] If the quantitative index of the degree of fragmentation exceeds the preset threshold, the blasting load parameters are adjusted, the stress distribution and deformation are re-obtained, and the dynamic response simulation results of the surrounding rock are updated.

[0080] Specifically, the surrounding rock fragmentation is divided into five levels. When the quantitative indicator of the fragmentation of a certain area reaches the fourth level, that is, exceeds the preset threshold, a new blasting plan is generated by adjusting parameters such as the charge amount and loosening coefficient. For example, if a certain area is found to be excessively fragmented, the charge amount is reduced by 20%, and the blasting spacing is adjusted to achieve a more uniform fragmentation effect. During the numerical analysis and verification process, the stress-strain relationship curve comparison method is used. The measured data is compared with the theoretical calculation results. When the error is less than 5%, the simulation results are considered reliable.

[0081] Furthermore, after generating the three-dimensional tunnel model, the method includes dividing the three-dimensional tunnel model into a plurality of small units according to the tunnel section type data, so as to facilitate targeted analysis of different tunnel section areas.

[0082] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A blasting simulation method suitable for tunnels with fractured surrounding rock, characterized in that: include: Obtain tunnel geometric features and generate a three-dimensional tunnel model; Obtaining surrounding rock fracture characteristic data and basic physical and mechanical parameters, and inputting them into numerical simulation software, wherein the surrounding rock fracture characteristic data includes crack distribution, fragmentation degree, and rock mass structure information, and the basic physical and mechanical parameters include dynamic elastic modulus, dynamic Poisson's ratio, and damping characteristic data; Marking blasthole positions in the three-dimensional tunnel model according to blasthole arrangement parameters, and correlating the blasthole arrangement parameters with basic physical and mechanical parameters in the numerical simulation software to obtain a key feature combination; Correlating the blasthole arrangement parameters with the basic physical and mechanical parameters in the numerical simulation software to obtain a key feature combination includes: Using a data association algorithm to match the blasthole arrangement parameters with the basic physical and mechanical parameters in the numerical simulation software to establish a parameter mapping relationship; generating a correlation data set of blasthole arrangement and mechanical parameters according to the parameter mapping relationship; Converting the associated data set into a format suitable for input into the numerical simulation software to generate a simulation input file; Using a machine learning algorithm to perform feature extraction on the associated data set in the simulation input file to obtain the key feature combination; based on the key feature combination, simulating the dynamic response characteristics of the surrounding rock under the blasting load during the blasting process in the numerical simulation software; The dynamic response characteristics of the surrounding rock under the blasting load during the blasting process simulated in the numerical simulation software include: generating simulation data of blasting load distribution and detonation wave propagation path in the numerical simulation software according to the key feature combination; determining whether the simulation data of the blasting load distribution and the blast wave propagation path are consistent with expectations; if so, continuing to simulate the dynamic response characteristics of the surrounding rock under the blasting load; if not, optimizing the simulation data of the blasting load distribution and the blast wave propagation path; The simulation data for optimizing the blast load distribution and detonation wave propagation path include: According to the key feature combination, the mapping relationship between the blasthole arrangement and the mechanical parameters is loaded into the numerical simulation software to generate initial simulation data of the blasting load distribution and the detonation wave propagation path; Using a machine learning algorithm, feature extraction is performed on the initial simulation data to obtain relevant features of the blasting load distribution and the detonation wave propagation path; According to the relevant characteristics, adjusting the input parameters of the numerical simulation software to optimize the simulation data of the blasting load distribution and the detonation wave propagation path; According to the dynamic response characteristics, a surrounding rock dynamic response simulation result is obtained.

2. The blasting simulation method for a tunnel with fractured surrounding rock according to claim 1 is characterized in that: Obtaining tunnel geometric features and generating a 3D tunnel model includes: According to the tunnel design drawings, obtain tunnel section type data and positioning point coordinate information; Preprocessing the positioning point coordinate information to remove noise and incomplete data, and matching the tunnel section type data with the preprocessed positioning point coordinate information; Generate a continuous tunnel centerline between the coordinate information of the positioning points through a spatial interpolation algorithm; According to the matched tunnel section type data and the pre-processed positioning point coordinate information, the tunnel section type data is staked out with the center line as the reference to construct a tunnel surface grid; A three-dimensional reconstruction algorithm is used to convert the tunnel surface mesh into a solid model to generate the three-dimensional model of the tunnel.

3. The blasting simulation method for a tunnel with fractured surrounding rock according to claim 1, characterized in that: The rock mass structure information includes rock layer inclination angle data and thickness data.

4. The blasting simulation method for a tunnel with fractured surrounding rock according to claim 1, characterized in that: According to the dynamic response characteristics, obtaining the surrounding rock dynamic response simulation results includes: Obtaining stress distribution data under the action of blasting load, calculating the deformation of the surrounding rock during the blasting process based on the stress distribution data, and generating a deformation distribution result; Using machine learning algorithms, we extract features from the deformation distribution results and obtain quantitative indicators of the degree of fragmentation. If the quantitative index of the degree of fragmentation exceeds a preset threshold, the blasting load parameters are adjusted, the stress distribution and deformation are re-obtained, and the surrounding rock dynamic response simulation results are updated.

5. The blasting simulation method for a tunnel with fractured surrounding rock according to claim 2, characterized in that: After generating the three-dimensional tunnel model, the method includes dividing the three-dimensional tunnel model into a plurality of small units according to the tunnel section type data.

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