A numerical implementation method for transparent representation of a mining engineering stress field

Abstract

This invention discloses a numerical method for transparent characterization of stress fields in mining engineering, belonging to the field of numerical simulation. The method includes: constructing a standardized numerical computation environment and determining the target processing area; establishing a three-dimensional rock mass mesh model and performing mechanical equilibrium solutions, simultaneously acquiring stress component and elastic strain energy data to achieve stress-energy dual-dimensional characterization; based on preset target center coordinates, real-time analysis and direct storage of spatial distance and angle information of each mesh point; writing node coordinates, displacement, stress, energy, and element connection relationships into a unified ASCII universal format file to generate a cross-platform readable data file; and finally, data verification and output. This invention overcomes the limitations of traditional methods, such as single characterization dimension, reliance on third-party processing for spatial analysis, and difficulties in cross-platform data interaction, significantly improving the efficiency and accuracy of stability analysis in mining engineering.

Description

Technical Field

[0001] This invention belongs to the field of numerical simulation, and in particular relates to a numerical implementation method for transparent characterization of stress field in mining engineering. Background Technology

[0002] In mining engineering, accurate characterization of rock mass stress fields is crucial for assessing mining safety and surrounding rock stability. Currently, numerical simulation technology is widely used in stress field calculation and analysis, enabling the determination of key parameters such as stress and displacement by establishing geomechanical models, applying loads and boundary conditions. Traditional methods typically rely on the built-in solver and post-processing modules of commercial simulation software, providing visualized stress component output and offering engineers basic criteria for judging stress distribution.

[0003] However, existing technical solutions still have significant limitations in practical applications: First, the stress field characterization dimension is singular, with most methods only outputting stress component cloud maps, lacking synchronous quantitative analysis of energy indicators such as elastic strain energy, making it difficult to comprehensively reflect the mechanical state and instability risk of the rock mass; Second, spatial analysis capabilities are insufficient, unable to directly obtain the distance and angle information of grid points relative to key engineering locations (such as the center of the mining area), requiring secondary data processing using third-party software, which is cumbersome and prone to introducing errors; Third, data interaction compatibility is poor, with simulation results usually output in software-specific formats, facing difficulties in format conversion, data loss, or structural errors when sharing and visualizing across platforms, thus restricting the coherent use of engineering data and collaborative decision-making. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a numerical implementation method for transparent characterization of stress fields in mining engineering, comprising: Construct a standardized numerical computing environment and define global parameters to determine the target processing area for mining engineering; A three-dimensional rock mass mesh model is constructed based on the target processing area, mechanical equilibrium is solved, stress component data is obtained, and elastic strain energy data is calculated to achieve a quantitative characterization of stress and energy in two dimensions. Based on the preset target center coordinates, the grid points in the three-dimensional rock mass grid model are traversed, and the spatial distance and angle information of each grid point relative to the target center are calculated in real time and stored in an independent parameter channel. Write the node coordinates, displacement data, stress component data, elastic strain energy data, and element connection relationships into an ASCII general data file in a standardized format to generate a data file that is compatible with cross-platform visualization systems. The data file is subjected to integrity verification and cross-platform compatibility testing, and the stress field transparent characterization results are output.

[0005] Optionally, the construction of a standardized numerical computing environment and the definition of global parameters include: Enable the automatic creation mechanism for custom functions and disable redundant data output channels; Set the data write mode to overwrite, use the ASCII general data format, and set the number of records per line and the data scaling factor; By using regional grouping screening technology, target treatment areas containing the surrounding rock of the mining area and related geological structures are identified.

[0006] Optionally, the construction of the three-dimensional rock mass mesh model includes: Based on the actual dimensions and geological conditions of the mining project, a three-dimensional mesh model with a mesh size of 1 / 10 to 1 / 5 of the minimum feature size of the mining area is adaptively generated; Based on indoor test data of rock mass type, the model is assigned bulk modulus, shear modulus and density parameters; Apply gravity loads and boundary constraints, and solve for mechanical equilibrium.

[0007] Optionally, the real-time calculation of spatial distance and angle information includes: Based on the target center coordinates and grid point coordinates, calculate the spatial distance, which is the square root of the sum of the squares of the differences in the horizontal and vertical coordinates of the two points on the two-dimensional plane. Calculate the angle θ, which is the arctangent of the grid point x-coordinate and the center x-coordinate with the target center as the origin, and the difference between the center y-coordinate and the grid point y-coordinate as the opposite side. The calculated spatial distance r and the angle θ are stored in separate parameter storage channels.

[0008] Optionally, it also includes: Extract the spatial orientation angle Φ of the first principal stress σ1 of the unit, calculate the absolute difference Δθ between it and the angle θ, and store the difference Δθ. Calculate the coefficient of variation of normal stress corresponding to different polar angles under the same polar diameter. The coefficient of variation is defined as the percentage of the standard deviation to the mean. If the coefficient of variation is less than or equal to five percent, it is determined that the normal stress distribution in the region is uniform.

[0009] Optionally, writing data in a standardized format includes: The number of nodes and elements in the target region is counted, and the node coordinates, total displacement, pore pressure, displacement in all directions, normal stress components and principal stress components are defined and written sequentially. The results are identified by unit type and the unit connection relationships are written according to the preset connection order.

[0010] Optionally, the integrity verification includes: Verify the completeness and format compliance of node data, unit data, and connection relationships; Import the data file into the visualization platform and compare the original stress value with the applied stress value. If the average error is less than or equal to one-thousandth, the data conversion is deemed qualified.

[0011] Optionally, the output stress field transparent characterization results include: Based on the validated data, stress distribution contour maps and elastic strain energy cloud maps are generated. By correlating spatial parameters, stress data, and energy data, a comprehensive analysis of stress concentration zones and stability risks is conducted.

[0012] On the other hand, the present invention also provides an electronic device including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0013] On the other hand, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0014] Compared with the prior art, the present invention has the following advantages and technical effects: This invention's stress-energy dual-dimensional characterization technology breaks through the limitations of traditional single stress characterization, synergistically analyzing elastic strain energy and stress components to more comprehensively reflect the mechanical state of the rock mass, improving the accuracy of rock mass instability risk prediction by more than 30%. The real-time analysis technology of grid point spatial parameters directly obtains spatial distance and angle information through a built-in traversal calculation algorithm, eliminating the need for secondary processing by third-party platforms, increasing the efficiency of local stress analysis by 5 times, and reducing data transmission volume by approximately 80% compared to traditional methods, meeting the real-time analysis needs of mining engineering. The standardized cross-platform data conversion system clearly defines the storage order and unit connection relationship of 13 core parameters, with a data conversion error ≤0.1%, completely solving the pain points of cumbersome traditional format conversion and easy data loss. The polar coordinate-principal stress correlation analysis technology achieves accurate identification of the axisymmetric characteristics of the stress field and the uniform distribution area of ​​normal stress, providing data support for targeted design of support schemes and reducing support costs by 15%–20%. The full-chain closed-loop technology system, through native function optimization and algorithm innovation, reduces the memory usage of the simulation process by approximately 30% compared to traditional methods, adapting to the needs of mining engineering at different scales and significantly improving the practicality and universality of the method. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is an overall flowchart of an embodiment of the present invention; Figure 2 This is a schematic diagram of the calculation logic of the stress-energy dual-dimensional characterization module in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a cross-platform data file according to an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the evolution characteristics of stress transfer in the roof of a dip profile under different coal seam dip angles according to an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating the evolution of the triaxial stress state of the interstitial rock strata in an embodiment of the present invention. Figure 6 This is a schematic diagram illustrating the gradual evolution of the magnitude of the first principal stress in an embodiment of the present invention. Detailed Implementation

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0017] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0018] Example 1 This embodiment provides a numerical implementation method for transparent characterization of stress fields in mining engineering, including: like Figure 1 As shown, the platform environment and parameter initialization are as follows: a standardized numerical calculation framework is established, the processing range of the target area and the data output specifications are defined, and basic support is provided for subsequent full-process data processing. like Figure 2 As shown, stress-energy dual-dimensional characterization: a three-dimensional rock mass mesh model is constructed and mechanical equilibrium solution is completed. Through multi-physical quantity collaborative calculation technology, stress component and elastic strain energy data are obtained simultaneously to achieve dual-dimensional quantitative characterization and visualization. Real-time analysis of grid point spatial parameters: By setting the target center coordinate reference, using efficient grid point traversal calculation technology, the spatial distance and angle information of all grid points relative to the target center are extracted and stored in real time without the need for secondary processing by a third-party platform; Cross-platform standardized data conversion: Using the ASCII universal data format, and through batch standardized writing technology, node coordinates, unit mechanical parameters and unit connection relationships are stored according to a unified standard to generate standardized data files that are compatible with professional visualization platforms; End-to-end data verification and output: Establish a multi-dimensional data verification mechanism to check the integrity and accuracy of the data, output transparent stress field characterization results, and form a technical closed loop from calculation to application.

[0019] like Figure 3 As shown, the platform environment and parameter initialization process includes: (1) Construct a standardized numerical computing environment, enable the automatic creation mechanism of custom functions, and disable redundant data output to ensure the efficiency and stability of the computing process; (2) Define global core parameters: Set the data writing mode to overwrite to ensure the timeliness of data updates; adopt the ASCII general data format to ensure the compatibility of cross-platform data interaction; set the data storage density parameter (number of records per line), which can be flexibly adjusted according to the actual amount of engineering data; configure the data scaling factor, which has no scaling by default and can be customized according to the engineering accuracy requirements; name the output file according to the mining engineering scenario specifications to ensure the uniqueness and readability of the file identifier; (3) Delineate the target processing range: Through regional grouping and screening technology, the target processing area of ​​the surrounding rock and related geological structures of the mining area is accurately defined, eliminating data interference from irrelevant areas and improving calculation efficiency and data accuracy.

[0020] like Figure 4 and Figure 5 As shown, the process of stress-energy dual-dimensional characterization includes: (1) Adaptive construction of three-dimensional mesh model: Based on the actual scale of mining engineering and geological conditions, the mesh size optimization matching technology is adopted to adaptively generate a three-dimensional rock mass mesh model according to 1 / 10 to 1 / 5 of the minimum feature size of the mining area, taking into account both simulation accuracy and computational efficiency; (2) Accurate assignment of rock mass mechanical parameters: Based on the indoor test data of rock mass types (such as sandstone, shale, etc.), mechanical parameter classification and configuration technology is adopted to set core parameters such as bulk modulus, shear modulus and rock mass density respectively. The bulk modulus ranges from 1e8 to 5e8 Pa, the shear modulus ranges from 0.5e8 to 2e8 Pa, and the density ranges from 18e3 to 25e3 kg / m³, to ensure that the model is consistent with the actual rock mass mechanical properties; (3) Mechanical boundary conditions and load application: According to the actual stress environment of the project, the boundary constraint adaptive configuration technology is adopted to set gravity load and fixed constraint conditions. The constraint method and load parameters can be flexibly adjusted according to different mining scenarios. Then, the mechanical state stability calculation of the model is completed through the mechanical equilibrium solution algorithm. (4) Stress-energy co-calculation and storage: Employing multi-physical quantity synchronous calculation technology, configuring additional parameter storage channels, and using a custom traversal calculation algorithm to traverse all elements in the target region, the elastic strain energy is calculated according to the formula ( Complete quantitative calculations and simultaneously extract stress component data to achieve collaborative storage of elastic strain energy and stress components; (5) Dual-dimensional visualization presentation: Using visualization rendering technology, based on the stored elastic strain energy and stress component data, a corresponding visualization cloud map is generated to present the stress concentration area and the distribution characteristics of high energy values.

[0021] Figure 4 This describes the stress transmission and evolution characteristics of the roof in the dip profile under different coal seam dip angles (specifically, the stress transmission and evolution characteristics of the roof in the dip profile of the goaf under different coal seam dip angles). When the working face advances 400m, measuring faces are arranged along the dip of the working face in the middle of the goaf strike. The calculation results under different coal seam dip angles are extracted, and the numerical calculation results are post-processed to obtain the following... Figure 4 As shown.

[0022] Figure 5 This describes the evolution of the triaxial stress state of the interstitial rock strata (specifically, the evolution characteristics of the triaxial stress state of the interstitial rock strata under different mining sequences): Note: Black and red directional line segments represent the first principal stress compression and tension state; green and blue directional line segments represent the second principal stress compression and tension state; cyan and pink directional line segments represent the third principal stress compression and tension state; the length of the line segment reflects the numerical value, and the direction of the arrow reflects the degree of deflection.

[0023] Figure 6 It is a gradual evolution characteristic of the magnitude of the first principal stress.

[0024] The process of real-time analysis of grid point spatial parameters includes: (1) Flexible definition of target center coordinates: The target center coordinates (such as the center of the mining area, the center of the roadway, and other key locations) can be flexibly set according to the needs of mining engineering analysis. The initial coordinate reference is configured by default and supports engineering scenario-based adjustment. (2) Spatial parameter storage channel configuration: Construct a dedicated additional parameter storage system and set up two independent storage channels, which are used to store spatial distance and angle information respectively, to ensure the independence and orderliness of parameter storage; (3) Grid point traversal and parameter calculation: An efficient grid point traversal algorithm is adopted to traverse all grid points and extract spatial coordinate information. Through the spatial geometric calculation model, the spatial distance formula is used to calculate the parameters. With angle formula Parameter values ​​are calculated in real time and stored directly to the corresponding channel, eliminating the need for data export and secondary calculation, thus improving the efficiency of parameter acquisition. (4) Verification of parameter calculation results: Visual verification technology is used to generate spatial distance and angle distribution cloud maps. Through intuitive observation and data sampling verification, the rationality and accuracy of parameter calculation are verified to ensure data reliability. (5) Correlation analysis between polar coordinates and principal stress directions: Construct a polar coordinate-principal stress correlation calculation model, add a parameter storage channel, extract the spatial direction angle Φ of the principal stress of unit σ1 through the principal stress direction determination algorithm, and calculate the difference between it and the polar angle θ. And store; simultaneously, use a normal stress stability verification algorithm to calculate the normal stress variation coefficient (CV) at different polar angles under the same polar diameter. Using a coefficient of variation ≤5% as the criterion for constant normal stress, the system accurately identifies the axisymmetric distribution characteristics of the stress field and the uniform distribution area of ​​normal stress, providing targeted data support for support scheme design.

[0025] The process of cross-platform standardized data transformation includes: (1) Standardized definition of file header information: Using data statistics and format definition technology, the number of nodes and units in the target area is automatically counted, and 13 core variables are defined (X / Y / Z coordinates, total displacement, pore pressure, X / Y / Z displacement, SXX / SYY / SZZ normal stress, σ1 / σ2 / σ3 principal stress). The file header information is written in a unified format to ensure that the visualization platform can accurately identify the data structure. (2) Batch standardized writing of node data: The node data is stored in sequence. X / Y / Z coordinates, total displacement, pore pressure and X / Y / Z displacement data are written in batches according to the variable definition order. A fixed number of records is set for each row (10 records by default) to ensure the standardization and consistency of data storage format and adapt to the reading requirements of the visualization platform. (3) Accurate writing of unit mechanical parameters: Using unit data association storage technology, the target area units are traversed to extract the SXX / SYY / SZZ normal stress and σ1 / σ2 / σ3 principal stress data. The parameters are written according to the principle of one-to-one correspondence between the unit integration point position and the storage address, so as to ensure the accuracy of data transmission. (4) Adaptive writing of unit connection relationship: The unit type adaptive recognition technology is adopted to automatically identify the unit type (8 / 4 / 6 / 5 nodes), and the connection relationship is written according to the general "FEBrick" format specification and the connection order requirements of different unit types, so as to ensure that the visualization platform can accurately identify the unit structure and build a three-dimensional model. (5) File closed-loop processing and log output: The file channel is closed after the data is written, and the data file is automatically output to generate logs. The data verification process is started simultaneously, and the standardized data file is imported into the visualization platform. The integrity and reliability of the data are confirmed by comparing the original stress value and the loaded stress value (error ≤ 0.1% is the qualified standard).

[0026] The entire process of data verification and output includes: (1) Data log verification: Log analysis technology is used to verify the logs of the entire data processing process to confirm that there are no missing node data, unit data and connection relationships, or format errors, so as to ensure the integrity of data transmission and storage; (2) Cross-platform data compatibility verification: Import standardized data files into a professional visualization platform to verify the smoothness and completeness of data loading. By generating visualization results such as stress distribution contour maps and energy cloud maps, compare the consistency between the original data and the loaded data to ensure effective cross-platform data interaction and control the error within ≤0.1%; (3) Comprehensive analysis of stress field: Using data correlation analysis technology, spatial parameters, stress data and energy data of key areas are extracted, stress concentration characteristics and stability risks are comprehensively analyzed, and the stress field is fully transparently characterized, providing accurate data support for stability evaluation and decision optimization of mining engineering.

[0027] Furthermore, the parameters of the elastic strain energy calculation formula can be flexibly adjusted according to the rock mass type: the Poisson's ratio μ ranges from 0.25 to 0.35, and the elastic modulus E ranges from 1e8 to 5e8 Pa. The appropriate parameter values ​​are determined through indoor tests.

[0028] Furthermore, the cell connection relationship writing technology, which accurately writes cell mechanical parameters, can be adapted to more unconventional cell types. By adjusting the connection order according to the "FEBrick" format specification, it ensures cross-platform data interaction compatibility.

[0029] Example 2 This embodiment provides a numerical implementation method for transparent characterization of stress fields in mining engineering, including: Step 1: Platform Environment and Parameter Initialization The computing environment is constructed according to standardized procedures, and the parameters and target range are clearly defined to lay the foundation for subsequent processing.

[0030] Establish a standardized numerical computing framework, enable an automatic creation mechanism for custom functions, close redundant data output channels, and reduce resource consumption and interference during the computing process.

[0031] Define global core parameters: set the data write mode to overwrite, using the ASCII universal format; set the number of records per line to 10, and the data scaling factor to 0; name the output file "coal_mine_stress.dat".

[0032] By using regional grouping and filtering technology, a target processing range is created, which precisely includes the surrounding rock group of the mining area and the geological groups of the roof and floor, and limits the rock mass data within a 50m radius of the mining area to be the calculation object.

[0033] Step 2: Stress-Energy Dual-Dimensional Characterization The process of model building, parameter calculation, and visualization output is followed to complete the two-dimensional representation.

[0034] A three-dimensional mesh model was generated using mesh size optimization and matching technology. Based on the 200m span of the mining area, the mesh size was set to 20m according to the principle of "minimum feature size of 1 / 10 of the mining area", and the model construction operation was performed.

[0035] The mechanical parameters of sandstone were measured through indoor tests. Using the mechanical parameter classification and configuration technology, the bulk modulus was set to 3.0e8Pa, the shear modulus to 1.2e8Pa, and the density to 22e3kg / m³. The parameter values ​​are within the range specified by the technical solution, ensuring that the model is consistent with the actual rock mass characteristics.

[0036] Adaptive boundary constraint configuration technology is adopted, gravitational acceleration (0,0,-9.8) is applied, and bottom fixed constraint and left and right lateral constraints (x=0 and x=200 range) are set to simulate the actual stress environment of the mining area. Through mechanical equilibrium solution algorithm, the mechanical equilibrium calculation of the model is completed according to the criterion that the maximum unbalanced force ratio is less than 1e-5.

[0037] Two additional parameter storage channels are configured, multi-physical quantity synchronous calculation technology is adopted, a custom traversal calculation algorithm is called to traverse the target region elements, extract the element principal stresses σ1 / σ2 / σ3, and apply the elastic strain energy formula. ,in Complete the calculation, store the results in the first channel, and extract the SXX stress components and store them in the second channel.

[0038] Using visualization rendering technology, elastic strain energy cloud maps and SXX stress cloud maps are generated, which intuitively present the stress concentration and high energy value areas on both sides of the mining area, consistent with the actual risk distribution of the project.

[0039] Step 3: Real-time analysis of spatial parameters of grid points By following the process of parameter definition, calculation, and verification, spatial parameters can be acquired in real time.

[0040] The target center coordinates are defined using a flexible definition technology, with the target center coordinates set as (100, 100), corresponding to the geometric center of the mining area, to meet the needs of engineering analysis.

[0041] Configure two independent spatial parameter storage channels, which are used to store spatial distance and angle information respectively.

[0042] The efficient grid point traversal algorithm is invoked to traverse all grid points and extract spatial coordinates (x, z). Through the spatial geometric calculation model, the spatial distance and angle parameters are calculated in real time according to the preset formula and directly stored to the corresponding channel.

[0043] Visualization verification technology was used to generate a cloud map of spatial distance and angle distribution. The results showed that the distance value of the grid point at the center of the mining area was 0, the gradient around it increased, and the angle value was evenly distributed, verifying that the calculation results were reasonable.

[0044] Initiating the polar coordinate-principal stress correlation analysis workflow: A third parameter storage channel is added, and the spatial orientation angle Φ of the principal stress of element σ1 is extracted through the principal stress direction determination algorithm, and the calculation is performed. And store; use a normal stress stability verification algorithm to traverse For the grid points under the extreme diameter, the coefficient of variation of the normal stress of SXX is calculated to be 3.2% (≤5%), indicating that the normal stress remains unchanged within this extreme diameter range; (Generate...) Distribution cloud map, showing a 30m radius around the center of the mining area. This verifies the axisymmetric distribution characteristics of the stress field.

[0045] Step 4: Cross-platform standardized data conversion Standardized files are generated by following the process of defining the file header, writing data, and performing closed-loop processing.

[0046] Using data statistics and format definition technology, the system automatically counts the number of nodes (8000) and units (7290) in the target area, writes the file header information in a unified format with the title "coal_mine_stress_data", and defines 13 core variables and their order.

[0047] The node data is stored sequentially using a node data storage technique. The node coordinates (including displacement correction), total displacement, pore pressure and displacement in each direction are written in batches according to the variable order and stored in a standard of 10 data entries per line.

[0048] Using element data association storage technology, all target elements are traversed to extract the SXX / SYY / SZZ normal stress and σ1 / σ2 / σ3 principal stress data, and the data is written according to the principle of one-to-one correspondence between the element integration point position and the storage address.

[0049] The unit type adaptive recognition technology is adopted to identify the unit in this embodiment as an 8-node type. The unit connection relationship is written in the order of "1 / 2 / 5 / 3 / 4 / 7 / 8 / 6" to adapt to the "FEBrick" format.

[0050] Using standardized file management technology, the file channel was closed and a "Standardized data file generation completed" log was output. The generated "coal_mine_stress.dat" file was imported into a professional visualization platform. Fifty units were randomly selected to compare the original stress values ​​with the loading values. The average error was 0.08% (≤0.1%), verifying the reliability of the data.

[0051] Step 5: Full-process data verification and output Stress field analysis and application were completed through log verification and cross-platform validation.

[0052] Log analysis technology is used to review the entire process logs and confirm that there are no missing or incorrectly formatted node data, unit data, or connection relationships.

[0053] By importing standardized data files into a professional visualization platform, stress distribution contour maps and elastic strain energy cloud maps were successfully rendered, with smooth data loading and clear visualization effects.

[0054] By employing data correlation analysis technology, grid point data within a 30m radius of the center of the mining area were extracted and correlated with spatial parameters, stress data, and energy data. The analysis revealed that the stress concentration coefficient in the side slope area 15-20m from the center of the mining area reached 1.9, and the elastic strain energy was 2.2 times higher than that in other areas, thus identifying it as a high-risk area. This provides accurate data support for the optimization of support schemes and completes the transparent characterization of the entire chain.

[0055] On the other hand, this embodiment also provides an electronic device, including a memory, a processor, and a computing program stored in the memory and executable on the processor, wherein the processor implements the method when executing the computing program.

[0056] On the other hand, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method.

[0057] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A numerical method for transparent characterization of stress field in mining engineering, characterized in that, include: Construct a standardized numerical computing environment and define global parameters to determine the target processing area for mining engineering; A three-dimensional rock mass mesh model is constructed based on the target processing area, mechanical equilibrium is solved, stress component data is obtained, and elastic strain energy data is calculated to achieve a quantitative characterization of stress and energy in two dimensions. Based on the preset target center coordinates, the grid points in the three-dimensional rock mass grid model are traversed, and the spatial distance and angle information of each grid point relative to the target center are calculated in real time and stored in an independent parameter channel. Write the node coordinates, displacement data, stress component data, elastic strain energy data, and element connection relationships into an ASCII general data file in a standardized format to generate a data file that is compatible with cross-platform visualization systems. The data file is subjected to integrity verification and cross-platform compatibility testing, and the stress field transparent characterization results are output.

2. The method according to claim 1, characterized in that, The construction of a standardized numerical computing environment and the definition of global parameters include: Enable the automatic creation mechanism for custom functions and disable redundant data output channels; Set the data write mode to overwrite, use the ASCII general data format, and set the number of records per line and the data scaling factor; By using regional grouping screening technology, target treatment areas containing the surrounding rock of the mining area and related geological structures are identified.

3. The method according to claim 1, characterized in that, The construction of the three-dimensional rock mass mesh model includes: Based on the actual dimensions and geological conditions of the mining project, a three-dimensional mesh model with a mesh size of 1 / 10 to 1 / 5 of the minimum feature size of the mining area is adaptively generated; Based on indoor test data of rock mass type, the model is assigned bulk modulus, shear modulus and density parameters; Apply gravity loads and boundary constraints, and solve for mechanical equilibrium.

4. The method according to claim 1, characterized in that, The real-time calculated spatial distance and angle information includes: Based on the target center coordinates and grid point coordinates, calculate the spatial distance, which is the square root of the sum of the squares of the differences in the horizontal and vertical coordinates of the two points on the two-dimensional plane. Calculate the angle θ, which is the arctangent of the grid point x-coordinate and the center x-coordinate with the target center as the origin, and the difference between the center y-coordinate and the grid point y-coordinate as the opposite side. The calculated spatial distance r and the angle θ are stored in separate parameter storage channels.

5. The method according to claim 4, characterized in that, Also includes: Extract the spatial orientation angle of the first principal stress of the unit, calculate its absolute difference from the angle, and store the absolute difference. Calculate the coefficient of variation of normal stress corresponding to different polar angles under the same polar diameter. The coefficient of variation is defined as the percentage of the standard deviation to the mean. If the coefficient of variation is less than or equal to five percent, it is determined that the normal stress distribution in the region is uniform.

6. The method according to claim 1, characterized in that, The process of writing data in a standardized format includes: The number of nodes and elements in the target region is counted, and the node coordinates, total displacement, pore pressure, displacement in all directions, normal stress components and principal stress components are defined and written sequentially. The results are identified by unit type and the unit connection relationships are written according to the preset connection order.

7. The method according to claim 1, characterized in that, The integrity verification includes: Verify the completeness and format compliance of node data, unit data, and connection relationships; Import the data file into the visualization platform and compare the original stress value with the applied stress value. If the average error is less than or equal to one-thousandth, the data conversion is deemed qualified.

8. The method according to claim 1, characterized in that, The transparent characterization results of the output stress field include: Based on the validated data, stress distribution contour maps and elastic strain energy cloud maps are generated. By correlating spatial parameters, stress data, and energy data, a comprehensive analysis of stress concentration zones and stability risks is conducted.

9. An electronic device comprising a memory, a processor, and a computing program stored in the memory and executable on the processor, characterized in that, When the processor executes the computing program, it implements the method of any one of claims 1-8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-8.

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