Multivariable coupling control rock and composite material explosion impact characteristic testing method and system

Abstract

The invention discloses a multivariable coupling control rock and composite material explosion impact characteristic testing method and system, and relates to the technical field of rock explosion characteristic testing, and the method comprises the following steps: dividing a rock material gradient based on a gradient sensitive function, and generating an initial grid; encrypting explosion holes and crack path areas of the initial grid based on multi-physics field response characteristics to obtain an encrypted grid; based on the encrypted grid, the RHT model and the heat conduction equation, constructing a multi-field coupling model, and outputting a simulation result; and carrying out an explosion experiment, and inverting the dynamic strength and fracture toughness parameters of the material by comparing a simulation result with experimental data. The device and the method are used for solving the problem of inaccurate characteristic test simulation under explosion impact of rocks and composite materials.

Description

Technical Field

[0001] The present invention relates to the technical field of rock explosion characteristic testing, and more specifically, to a testing method and system for the explosion shock characteristics of rocks and composite materials with multi-variable coupling control. Background Art

[0002] Rocks and composite materials exhibit significant commonalities in explosion shock characteristic testing: both are typical inhomogeneous materials, showing non-linear mechanical responses and multi-mode failure behaviors under explosion shock loads, and the dynamic processes both involve energy transfer and force-thermal-damage coupling evolution from the mesoscopic structure to the macroscopic scale.

[0003] At the application level, national defense, military industry, energy development, and infrastructure have put forward stringent requirements for the safety and reliability of materials under extreme loads, promoting the expansion of testing from single loading conditions to complex environments such as high in-situ stress, high temperature, and multi-directional shock; at the technical level, traditional single testing methods are difficult to cover the cross-scale failure mechanisms and multi-field coupling effects of materials, prompting the evolution of the testing system towards "multi-dimensional loading (plane / three-dimensional stress state) - multi-scale characterization (from mineral grains / fiber filaments to structural components) - multi-technology integration (combining experimental testing, numerical simulation, and machine learning)". At the same time, the innovation of material design concepts forces the breakthrough of testing technology boundaries, and it is necessary to accurately quantify interface performance, component sensitivity, and failure thresholds under complex load paths to support the research and development of high-performance anti-explosion materials and the safety assessment of major projects.

[0004] For example, the testing method for the mechanical properties of rock-like materials announced in the invention patent announcement with the publication number: CN106546481B mainly includes the following steps: first, prepare rock-like material test specimens, conduct tensile tests and shear tests on specimens of different sizes respectively to obtain specimens with complete fracture surfaces, divide them into several scanning specimens according to the specifications of the scanning electron microscope, conduct electron microscopy scans on the scanning specimens to obtain the mesoscopic morphology maps of the fracture surfaces at different magnifications as the identification points of the tensile stress and shear stress of the fracture surfaces, and then conduct electron microscopy scans on specimens of the same material under any load conditions. By matching the identification points on the fracture surfaces, the stress distribution of the fracture surfaces under the corresponding stress conditions can be obtained. Compared with the prior art, in the process of specimen preparation of the present invention, multi-walled carbon nanotube materials are added, and the spraying of metal films can be avoided during electron microscopy scanning, thus avoiding the pollution of the specimen cross-section and making the testing more convenient and accurate.

[0005] For example, the performance test device and method for the kinetic characteristics of rapid-response flame arrestment / explosion suppression and collaborative suppression of combustible medium explosion under the influence of multiple parameters announced in the invention patent with the announcement number of CN117538377B include a visual explosion system, an explosion suppression system, a fire arrestment system, an ignition system, a gas supply system, a powder spraying system, a deflagration venting system, a pressure acquisition system, a temperature acquisition system, a high-speed infrared acquisition system, an image acquisition system, a schlieren acquisition system, an oil bath heating system, a synchronous control system, a program control and data acquisition system. A rapid-response flame arrestment / explosion suppression device is used to study the performance and kinetic characteristics of rapid-response fire arrestment and explosion suppression and collaborative suppression of gas / dust explosion under the influence of multiple parameters. The invention fills the gap in the test device and technology for rapid-response flame arrestment / explosion suppression and collaborative suppression of gas-dust explosion by studying the kinetic characteristics of rapid-response flame arrestment / explosion suppression and collaborative suppression of combustible medium explosion under the influence of multiple parameters and its explosion suppression performance test device.

[0006] In the above-mentioned disclosed technical solutions, there are at least the following technical problems: In the numerical simulation of the existing rock explosion characteristic test methods, the refinement of the simulation grid is generally ignored, especially the targeted grid refinement is not implemented for key positions such as the explosion action area and the rock fracture development zone, resulting in the model being difficult to accurately capture the meso-mechanical behaviors such as local stress concentration and material damage of the rock under the explosion load.

[0007] In addition, as an indispensable influencing factor in the explosion process, the thermal effect has not been fully considered. The high temperature generated by the explosion will significantly change the thermodynamic parameters of the rock, inducing a strong coupling effect between thermal stress and mechanical response. However, the existing methods often ignore the dynamic interaction process between the temperature field and the stress field, resulting in the inability to comprehensively reveal the crack initiation, propagation and energy dissipation mechanisms of the rock in the high-temperature and high-pressure coupling environment.

[0008] The above two deficiencies together cause a deviation between the simulation results and the actual explosion effect, making it difficult to accurately reflect the multi-field coupling dynamic response characteristics of rock materials under complex explosion loads.

[0009] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0010] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a test method and system for the explosion shock characteristics of rocks and composite materials with multi-variable coupling control. By encrypting and refining the analysis grid for the explosion characteristics of rock materials in a multi-dimensional and targeted manner and using the encrypted grid for simulation in a multi-field coupling model, the problem of inaccurate simulation of the characteristics test of rocks and composite materials under explosion shock is solved.

[0011] To achieve the above object, the present invention provides the following technical solutions: A test method for the explosion shock characteristics of rocks and composites with multivariable coupling control includes the following steps: dividing the rock material gradient based on the gradient sensitive function and generating an initial mesh; encrypting the explosion hole and crack path regions of the initial mesh based on the multi-physical field response characteristics to obtain an encrypted mesh; constructing a multi-field coupling model based on the encrypted mesh, the RHT model, and the heat conduction equation, and outputting the simulation results; and conducting an explosion experiment, and inversely calculating the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

[0012] In a preferred embodiment, the step of dividing the rock material gradient based on the gradient sensitive function and generating an initial mesh is specifically: obtaining the elastic modulus distribution field of the rock material, and calculating the mesh density control parameter based on the gradient sensitive function; generating the initial mesh according to the mesh density control parameter.

[0013] In a preferred embodiment, the step of encrypting the explosion hole and crack path regions of the initial mesh based on the multi-physical field response characteristics to obtain an encrypted mesh is specifically: based on the first mesh, encrypting the mesh in the explosion hole region through the analysis of the explosion shock wave propagation characteristics to obtain the second mesh, where the first mesh is based on the initial mesh and is obtained by encrypting the mesh in the heat affected zone through the analysis of the heat conduction characteristics; based on the second mesh, encrypting the mesh in the crack path region through the prediction of the rock material damage to obtain the encrypted mesh.

[0014] In a preferred embodiment, the step of constructing a multi-field coupling model based on the encrypted mesh, the RHT model, and the heat conduction equation, and outputting the simulation results is specifically: constructing a multi-field coupling model based on the coupling of the temperature field, stress field, and damage field, where the stress field and damage field are coupled based on the RHT model, and the temperature field and the coupled stress field are coupled through the heat conduction equation; inputting the encrypted mesh into the multi-field coupling model and outputting the multi-field simulation results, where the multi-field simulation results include the stress field simulation result, temperature field simulation result, and damage field simulation result.

[0015] In a preferred embodiment, the step of conducting an explosion experiment, and inversely calculating the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data is specifically: selecting a rock material sample for the explosion experiment to obtain the experimental data, where the experimental data includes the temperature field, stress field, and damage field obtained from the experiment; setting a group of dynamic strength and fracture toughness parameters of the material as a particle; randomly generating particles and conducting numerical simulations, calculating the simulated temperature field, stress field, and damage field, and comparing them with the experimental data; and iteratively solving the particles based on the particle swarm algorithm to obtain the dynamic strength and fracture toughness parameters of the material when the difference between the multi-field simulation results and the experimental data is the smallest.

[0016] In a preferred embodiment, the specific method for obtaining the first grid is as follows: obtain the thermal conductivity, specific heat capacity, and thermal expansion coefficient of the rock material; based on the thermal conductivity and specific heat capacity, obtain the range of the heat-affected zone according to the heat conduction equation; based on the thermal expansion coefficient, obtain the distribution of the thermal stress field according to the thermoelastic equation; according to the distribution of the thermal stress field, encrypt the heat-affected zone of the initial grid based on the adaptive finite element method to obtain the first grid.

[0017] In a preferred embodiment, the specific method for obtaining the second grid is as follows: obtain the explosive detonation energy, the density of the rock material, and the distribution field of the elastic modulus of the rock material; based on the explosive detonation energy and the elastic modulus of the rock material, obtain the shock wave propagation speed according to the Navier-Stokes equation and the wave equation; according to the shock wave propagation speed and the obtained highest frequency, obtain the shock wave wavelength; according to the shock wave wavelength, encrypt the explosion hole area of the first grid based on the hierarchical gradient grid model to obtain the second grid.

[0018] In a preferred embodiment, based on the second grid, by predicting the damage of the rock material, encrypt the grid in the crack path area to obtain the encrypted grid, specifically: obtain the CT scan data, static fracture toughness, and yield strength of the rock material; based on the Weibull statistical model, generate the initial damage distribution field of the rock material according to the CT scan data; according to the fracture mechanics criterion, combine the static fracture toughness and the yield strength to obtain the upper limit of the grid size at the crack tip; simulate the crack propagation process based on the extended finite element method to obtain the crack path area; encrypt the crack path area of the second grid to obtain the encrypted grid.

[0019] A test system for the explosion shock characteristics of rocks and composites with multivariable coupling control includes: an initial grid division module for dividing the rock material gradient based on the gradient sensitive function and generating an initial grid; a grid encryption module for encrypting the explosion hole and crack path areas of the initial grid based on the multi-physical field response characteristics to obtain an encrypted grid; an explosion characteristic simulation module for constructing a multi-field coupling model based on the encrypted grid, the RHT model, and the heat conduction equation and outputting simulation results; an experimental inversion module for conducting explosion experiments and inversely calculating the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

[0020] The technical effects and advantages of the test method and system for the explosion shock characteristics of rocks and composites with multivariable coupling control according to the present invention: The present invention refines the test analysis grid of the explosion characteristics of rock materials through multi-dimensional targeted encryption, which helps to accurately capture the local stress, heat conduction, and damage evolution characteristics of rocks and composite materials during the explosion process, thereby improving the simulation accuracy of key areas; and uses the encrypted grid for simulation in a multi-field coupling model. By integrating the RHT model with the heat conduction equation in the multi-field coupling model, it helps to comprehensively consider the interaction of multiple physical fields of temperature-stress-damage, so as to truly restore the dynamic response process of rocks and composite materials under explosion loads; through the comparison of explosion experiment results and simulation results, combined with the particle swarm optimization algorithm to invert the dynamic strength and fracture toughness parameters of the material, more realistic material characteristic data can be obtained. Thus, it effectively solves the problem of inaccurate test simulation of the characteristics of rocks and composite materials under explosion shock, and further improves the accuracy of material parameters obtained by the characteristic test method, providing reliable theoretical support and technical reference for rock engineering blasting design. Brief Description of the Drawings

[0021] Figure 1 It is a schematic flow chart of a test method for the explosion shock characteristics of rocks and composite materials with multi-variable coupling control provided by an embodiment of the present invention.

[0022] Figure 2 It is a schematic structural diagram of a test system for the explosion shock characteristics of rocks and composite materials with multi-variable coupling control provided by an embodiment of the present invention.

[0023] Figure 3 and Figure 4 It is an encrypted grid diagram provided by an embodiment of the present invention. Detailed Embodiments

[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] Embodiment 1 Figure 1 A test method for the explosion shock characteristics of rocks and composite materials with multi-variable coupling control of the present invention is given, including the following steps: S1, divide the gradient of the rock material based on the gradient sensitive function and generate an initial grid; S2, encrypt the explosion hole and crack path areas of the initial grid based on the multi-physical field response characteristics to obtain an encrypted grid; S3, construct a multi-field coupling model based on the encrypted grid, the RHT model, and the heat conduction equation, and output the simulation results; S4, and conduct explosion experiments. By comparing the simulation results with the experimental data, the dynamic strength and fracture toughness parameters of the material are inverted.

[0026] In this embodiment, by multi-dimensionally and specifically encrypting and refining the explosion characteristic test analysis grid of the rock material, it helps to accurately capture the local stress, heat conduction, and damage evolution characteristics of the rock and composite materials during the explosion process, thereby improving the simulation accuracy of the key area; and the encrypted grid is used for simulation in the multi-field coupling model. Combining the multi-field coupling model to integrate the RHT model and the heat conduction equation helps to comprehensively consider the interaction of multiple physical fields such as temperature-stress-damage, thereby truly restoring the dynamic response process of the rock and composite materials under the explosion load; through the comparison of the explosion experiment and the simulation results, combined with the particle swarm algorithm to invert the dynamic strength and fracture toughness parameters of the material, more realistic material property data can be obtained. Thus, it effectively solves the problem of inaccurate simulation of the characteristics of rock and composite materials under explosion impact, and further improves the accuracy of the material parameters obtained by the characteristic test method, providing reliable theoretical support and technical reference for the blasting design of rock engineering.

[0027] S1, divide the gradient of the rock material based on the gradient sensitive function and generate the initial grid.

[0028] In this embodiment, the method of dividing the gradient of the rock material based on the gradient sensitive function and generating the initial grid is specifically as follows: Obtain the elastic modulus distribution field of the rock material, and calculate the grid density control parameter based on the gradient sensitive function; Generate the initial grid according to the grid density control parameter.

[0029] In this embodiment, the method for obtaining the elastic modulus distribution field of the rock material is as follows: Obtain the three-dimensional gray-scale image of the rock material sample through CT scanning, and convert the three-dimensional gray-scale image into a density distribution field according to the empirical relationship between the gray-scale value and the density value; Convert the density distribution field into an elastic modulus distribution field based on the density-elastic modulus formula; In this embodiment, the density-elastic modulus formula, the specific calculation formula is:

[0030] In the formula, is the elastic modulus, is the local density, and are the empirical constants of the rock material.

[0031] In this embodiment, the grid density control parameter calculated based on the gradient sensitive function, the specific calculation formula is:

[0032] In the formula, is the grid density control parameter, is the Euclidean norm, is the gradient of the elastic modulus.

[0033] In this embodiment, an initial grid is generated according to the grid density control parameter, specifically: Construct a uniform grid for analyzing the characteristics of rock materials and preset a control threshold; The uniform grid in the area where the grid density control parameter is higher than the control threshold is encrypted to obtain the initial grid.

[0034] S2. Based on the multi-physical field response characteristics, the explosion hole and crack path areas of the initial grid are encrypted to obtain an encrypted grid.

[0035] In this embodiment, the method of encrypting the explosion hole and crack path areas of the initial grid based on the multi-physical field response characteristics to obtain an encrypted grid is specifically: Based on the initial grid, through the analysis of the heat conduction characteristics, the grid in the heat affected zone is encrypted to obtain the first grid; Based on the first grid, through the analysis of the explosion shock wave propagation characteristics, the grid in the explosion hole area is encrypted to obtain the second grid; Based on the second grid, through the prediction of rock material damage, the grid in the crack path area is encrypted to obtain the encrypted grid.

[0036] In this embodiment, the specific method for obtaining the first grid is: Obtain the thermal conductivity, specific heat capacity and thermal expansion coefficient of the rock material; Based on the thermal conductivity and specific heat capacity, obtain the range of the heat affected zone according to the heat conduction equation; Based on the thermal expansion coefficient, obtain the distribution of the thermal stress field according to the thermoelastic equation; Based on the distribution of the thermal stress field, the heat affected zone of the initial grid is encrypted by the adaptive finite element method to obtain the first grid.

[0037] In this embodiment, based on the distribution of the thermal stress field, the heat affected zone of the initial grid is encrypted by the adaptive finite element method to obtain the first grid, specifically: Based on the distribution of the thermal stress field, reconstruct the thermal stress field by the node averaging method to obtain a smooth thermal stress field; Based on Estimate the reconstruction error by comparing the thermal stress field and the smooth thermal stress field; Preset a reconstruction threshold, mark the area where the reconstruction error exceeds the reconstruction threshold as the area to be encrypted, and encrypt the grid in the area to be encrypted by the h-adaptive encryption method to obtain the first grid.

[0038] In this embodiment, the specific method for obtaining the second grid is as follows: Obtain the explosive detonation energy, the density of the rock material, and the distribution field of the elastic modulus of the rock material; Based on the explosive detonation energy and the elastic modulus of the rock material, and using the Navier-Stokes equation and the wave equation, obtain the shock wave propagation velocity; Based on the shock wave propagation velocity and the obtained highest frequency, obtain the shock wave wavelength; Based on the shock wave wavelength, encrypt the explosion hole area of the first grid based on the hierarchical gradient grid model to obtain the second grid.

[0039] In this embodiment, based on the explosive detonation energy and the elastic modulus of the rock material, and using the Navier-Stokes equation and the wave equation, obtaining the shock wave propagation velocity is specifically as follows: Based on the explosive detonation energy and the elastic modulus of the rock material, simulate the expansion process of the explosion products through the Navier-Stokes equation, and calculate the initial impact pressure of the high-pressure gas on the rock; Substitute the initial impact pressure as the boundary condition into the one-dimensional wave equation of the rock material, and solve the wave equation by combining the finite difference method to obtain the shock wave propagation velocity.

[0040] In this embodiment, the specific formula of the hierarchical gradient grid model is:

[0041] In the formula, is the grid size of the i-th layer, is the grid size of the first layer, is the gradient factor controlling the change of the grid size.

[0042] It should be noted that the explosion hole area refers to the area where the rock material deforms due to the explosion effect, including the explosion center area and the explosion wave propagation area.

[0043] In this embodiment, based on the second grid, through the prediction of the damage of the rock material, encrypt the grid in the crack path area to obtain the encrypted grid, specifically as follows: Obtain the CT scan data, the static fracture toughness, and the yield strength of the rock material; Based on the Weibull statistical model, generate the initial damage distribution field of the rock material according to the CT scan data; According to the fracture mechanics criterion, combine the static fracture toughness and the yield strength to obtain the upper limit of the grid size at the crack tip; Based on the extended finite element method, simulate the crack propagation process to obtain the crack path area; Encrypt the crack path area of the second grid to obtain the encrypted grid.

[0044] In this embodiment, the constraint condition of the grid size at the crack tip based on the fracture mechanics criterion is as follows:

[0045] In the formula, is the grid size at the crack tip, is the static fracture toughness, is the yield strength.

[0046] In this embodiment, the crack path region of the second grid is encrypted to obtain an encrypted grid, specifically: Dynamically encrypt the crack path region of the second grid according to the grid size at the crack tip; And track the crack path evolution through the level set function to ensure the grid matches the crack geometry.

[0047] S3. Based on the encrypted grid, the RHT model, and the heat conduction equation, construct a multi-field coupling model and output the simulation results.

[0048] In this embodiment, the construction of the multi-field coupling model based on the encrypted grid, the RHT model, and the heat conduction equation and the output of the simulation results are specifically as follows: Couple the stress field and the damage field based on the RHT model; Then couple the temperature field and the coupled stress field through the heat conduction equation to obtain a multi-field coupling model that couples the temperature field, the stress field, and the damage field; Input the encrypted grid into the multi-field coupling model and output the multi-field simulation results, where the multi-field simulation results include the stress field simulation result, the temperature field simulation result, and the damage field simulation result.

[0049] S4. Conduct an explosion experiment, and invert the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

[0050] In this embodiment, the conduct of the explosion experiment and the inversion of the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data are specifically as follows: Select a rock material sample to conduct an explosion experiment to obtain experimental data, where the experimental data includes the temperature field, the stress field, and the damage field obtained from the experiment; Set a group of dynamic strength and fracture toughness parameters of the material as a particle; Randomly generate particles and conduct numerical simulations, calculate the simulated temperature field, stress field, and damage field, and compare them with the experimental data; Based on the particle swarm algorithm, iteratively solve the particles to obtain the dynamic strength and fracture toughness parameters of the material when the difference between the multi-field simulation results and the experimental data is the smallest.

[0051] It should be noted that the dynamic strength of materials refers to the compressive strength of rock materials under high strain rates, which characterizes the ability of materials to resist dynamic load failure; the fracture toughness parameter refers to the dynamic fracture toughness.

[0052] Table 1 presents the comparison between the simulation results and experimental data of a certain experiment in this embodiment.

[0053] Table 1

[0054] The RHT model (Riedel-Hiermaier-Thoma constitutive model) is the core model for describing the mechanical behavior of quasi-brittle materials such as rocks and concretes under dynamic loads such as impact and explosion. This model is improved based on the HJC model, which can accurately characterize the correlation between the strain type and stress state of materials. At the same time, it couples the strain rate effect and the damage accumulation mechanism, and can effectively simulate the plastic deformation, crack propagation and failure process of materials under high strain rates. Its core advantage lies in considering the anisotropic damage evolution under complex stress paths, and it is especially good at simulating the rock response under extreme working conditions such as cyclic loads and blasting loads, such as the law of energy superposition of double-hole blasting, the optimization of the hole spacing of pre-splitting blasting, and the crack propagation mode of cyclic blasting.

[0055] The coefficient of thermal expansion is a physical quantity that characterizes the property of an object to change its volume or length due to temperature changes. The coefficient of thermal expansion is very crucial for the practical application of materials. Considering the coefficient of thermal expansion of materials helps to avoid problems such as structural deformation and damage caused by temperature changes. For example, in engine components working in high-temperature environments or building structures that generate thermal stress due to temperature changes, the coefficient of thermal expansion is a factor that needs to be considered key.

[0056] The thermoelastic equations are a set of mathematical equations that describe the coupled interaction between heat and elasticity. It comprehensively considers the relationship between the elastic deformation of an object and temperature changes. In thermoelastic theory, the elastic properties of an object are related to temperature. Temperature changes will cause thermal expansion or contraction of the object, thereby generating thermal stress. The thermoelastic equations quantitatively describe this coupled effect of heat and mechanical behavior. It plays a key role in understanding and predicting the mechanical response of materials in a thermal environment.

[0057] The adaptive finite element method is a numerical method used in the field of finite element analysis to improve the calculation accuracy and efficiency. It is based on the traditional finite element method. According to the characteristics of the problem to be solved and the error estimation of the calculation results, it dynamically adjusts the finite element mesh, that is, it refines the mesh in the area with larger calculation result errors and coarsens the area with smaller errors appropriately. The adaptive finite element method can, while ensuring the calculation accuracy, reasonably allocate calculation resources, avoid excessive calculation in unnecessary areas, thereby significantly improving the calculation efficiency, effectively solving complex engineering and scientific problems, and providing a more reliable analysis method when dealing with complex situations such as nonlinearity and large deformation.

[0058] The h - adaptive encryption method is an important technique in the adaptive finite element method. Based on finite element analysis, according to the error estimation of the calculation results, by refining or coarsening the finite element mesh, the parts with larger errors in the calculation area are encrypted, and the number of meshes in the areas with smaller errors is appropriately reduced to achieve the purpose of improving the calculation accuracy. In practical applications, it is especially suitable for solving problems with highly localized characteristics and is an effective means to improve the efficiency and accuracy of finite element calculations.

[0059] The Navier - Stokes equations. In the field of explosion analysis of rock materials, the Navier - Stokes equations are important tools for describing the motion of fluids (such as air) around rocks and pore fluids in rocks during an explosion. The equations consider factors such as the viscous force, pressure gradient, and inertial force of the fluid, and can effectively depict the propagation, reflection, and refraction of shock waves generated instantaneously during an explosion in a fluid medium, as well as the complex mechanical behaviors during the interaction between the fluid and the rock. For example, during the fragmentation process of rocks under explosion shock, the influence of the fluid on the fragmentation morphology and crack propagation of rocks. It provides a key theoretical basis and analysis means for studying explosion effects, evaluating the stability of rock engineering under explosion, and optimizing blasting schemes in the explosion analysis of rock materials.

[0060] The wave equation refers to the explosion shock wave wave equation. The explosion shock wave wave equation is a mathematical expression describing the propagation law of explosion shock waves in a medium. It comprehensively considers physical properties such as the density, elastic modulus, and wave velocity of the medium, and can accurately depict phenomena such as the propagation, reflection, refraction, and energy dissipation of shock waves. In the field of explosion engineering, this equation can be used to predict the action of shock waves on structures. By solving and analyzing the wave equation, it helps to study the dynamic response of materials under shock wave action, explore the damage, deformation, and failure mechanisms of materials, and is a key tool for understanding and mastering the physical process of explosion shock waves.

[0061] The Weibull statistical model. In the analysis of material strength distribution, the probability characteristics of material strength are characterized by a two - parameter probability distribution (the shape parameter is the Weibull modulus, and the scale parameter is the characteristic strength). Its probability density function can describe the occurrence probability of different strength values, and the survival function corresponds to the reliability (probability of non - failure) of the material under a specific stress. This model is suitable for modeling material strength data, can quantify the dispersion and average level of the strength distribution through parameter estimation, and then be used to predict the failure probability of materials under a given stress, evaluate structural reliability, or optimize material design. It is a core tool for analyzing strength distribution and reliability in materials science.

[0062] The extended finite element method (XFEM) is a numerical calculation method developed on the basis of the traditional finite element method. It breaks through the limitation of displacement continuity in the traditional finite element method. By introducing special shape functions to describe the singularity at the crack tip and the discontinuity of the crack surface, it can effectively simulate dynamic processes such as crack initiation and propagation without continuously re-meshing as the crack extends. The extended finite element method shows unique advantages and can more accurately predict the failure mode of structures, which is an important means to solve crack-related problems.

[0063] Error estimation (Zienkiewicz-Zhu) is an important error assessment method in finite element analysis. It constructs a more accurate reference solution based on the finite element solution and estimates the error by calculating the difference between the finite element solution and the reference solution. This method can effectively evaluate the accuracy of the finite element calculation results. Through the method of a posteriori error estimation, it can provide a basis for judging whether the finite element mesh needs to be refined and optimizing the mesh to improve the accuracy of the finite element solution, making the finite element analysis results more accurate and reliable, and providing a more valuable reference for solving problems.

[0064] Example 2 Figure 2 A test system for the explosion shock characteristics of rocks and composites with multivariable coupling control according to the present invention is given, including: An initial mesh generation module for dividing the rock material gradient based on the gradient sensitive function and generating an initial mesh; A mesh refinement module for refining the explosion hole and crack path regions of the initial mesh based on the multi-physical field response characteristics to obtain a refined mesh; An explosion characteristics simulation module for constructing a multi-field coupling model based on the refined mesh, the RHT model, and the heat conduction equation and outputting simulation results; An experimental inversion module for conducting explosion experiments and inversely calculating the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

[0065] Figure 3 and Figure 4 This is the refined mesh diagram provided by the embodiment of the present invention. In the figure, the red dots represent the refined mesh in the explosion hole region, the yellow dots represent the refined mesh in the heat affected zone, and the blue dots represent the refined mesh in the crack path region.

[0066] The above formulas are all dimensionless and take their numerical calculations. The formula is a formula obtained by collecting a large amount of data for software simulation to be closest to the real situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0067] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0068] Those of ordinary skill in the art will realize that the modules and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0069] In addition, each functional module in the various embodiments of the present application can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0070] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0071] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should all be included in the protection scope of the present invention.

Claims

1. A test method for the explosion shock characteristics of rocks and composites with multivariable coupling control, characterized in that, It includes the following steps: Divide the rock material gradient based on the gradient sensitivity function and generate an initial mesh; Refine the explosion hole and crack path regions of the initial mesh based on the multi-physical field response characteristics to obtain a refined mesh; Construct a multi-field coupling model based on the refined mesh, RHT model, and heat conduction equation, and output the simulation results; Conduct an explosion experiment, and invert the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

2. The method for testing the explosion shock characteristics of rocks and composite materials with multivariable coupling control according to claim 1, characterized in that The step of dividing the rock material gradient based on the gradient sensitivity function and generating an initial mesh is specifically as follows: Obtain the elastic modulus distribution field of the rock material, and calculate the mesh density control parameter based on the gradient sensitivity function; Generate an initial mesh according to the mesh density control parameter.

3. The method for testing the explosion shock characteristics of rocks and composite materials with multivariable coupling control according to claim 2, characterized in that, The step of refining the explosion hole and crack path regions of the initial mesh based on the multi-physical field response characteristics to obtain a refined mesh is specifically as follows: Based on the first mesh, analyze the propagation characteristics of the explosion shock wave to refine the mesh in the explosion hole region to obtain a second mesh. The first mesh is based on the initial mesh and is refined by analyzing the heat conduction characteristics of the heat-affected zone; Based on the second mesh, predict the damage of the rock material to refine the mesh in the crack path region to obtain a refined mesh.

4. The method for testing the explosion shock characteristics of rocks and composite materials with multivariable coupling control according to claim 3, characterized in that, The step of constructing a multi-field coupling model based on the refined mesh, RHT model, and heat conduction equation, and outputting the simulation results is specifically as follows: Construct a multi-field coupling model by coupling the temperature field, stress field, and damage field. The stress field and damage field are coupled based on the RHT model, and the temperature field and the coupled stress field are coupled through the heat conduction equation; Input the refined mesh into the multi-field coupling model and output the multi-field simulation results. The multi-field simulation results include the stress field simulation result, temperature field simulation result, and damage field simulation result.

5. The test method for explosion shock characteristics of rock and composite materials with multivariable coupling control according to claim 4, characterized in that, The step of conducting an explosion experiment and inverting the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data is specifically as follows: Select a rock material sample to conduct an explosion experiment and obtain experimental data. The experimental data includes the temperature field, stress field, and damage field obtained from the experiment; Set a group of dynamic strength and fracture toughness parameters of the material as a particle; Randomly generate particles and conduct numerical simulations, calculate the simulated temperature field, stress field, and damage field, and compare them with the experimental data; Based on the particle swarm algorithm, iteratively solve the particles to obtain the dynamic strength and fracture toughness parameters of the material when the difference between the multi-field simulation results and the experimental data is the smallest.

6. The method for testing the explosion shock characteristics of rocks and composites with multivariable coupling control according to claim 5, characterized in that, The specific method for obtaining the first mesh is as follows: Obtain the thermal conductivity, specific heat capacity, and coefficient of thermal expansion of the rock material; Based on the thermal conductivity and specific heat capacity, obtain the range of the heat-affected zone according to the heat conduction equation; Based on the coefficient of thermal expansion, obtain the distribution of the thermal stress field according to the thermoelastic equation; Based on the distribution of the thermal stress field, refine the heat-affected zone of the initial mesh by the adaptive finite element method to obtain the first mesh.

7. The method for testing the explosion shock characteristics of rocks and composites with multivariable coupling control according to claim 6, characterized in that, The specific method for obtaining the second mesh is as follows: Obtain the explosive detonation energy, density of the rock material, and elastic modulus distribution field of the rock material; Based on the explosive detonation energy and the elastic modulus of the rock material, obtain the shock wave propagation velocity according to the Navier-Stokes equation and the wave equation; The shock wave wavelength is obtained based on the shock wave propagation speed and the highest frequency acquired. Based on the shock wave wavelength, the explosion hole area of the first grid is encrypted according to the hierarchical gradient grid model to obtain the second grid.

8. The method for testing the explosion shock characteristics of rocks and composite materials with multivariable coupling control according to claim 7, characterized in that Based on the second grid, the grid of the crack path area is encrypted through rock material damage prediction to obtain the encrypted grid, specifically: Obtain the CT scan data, static fracture toughness, and yield strength of the rock material. Based on the Weibull statistical model, generate the initial damage distribution field of the rock material according to the CT scan data. According to the fracture mechanics criterion, combined with the static fracture toughness and yield strength, obtain the upper limit of the grid size at the crack tip. Based on the extended finite element method, simulate the crack propagation process to obtain the crack path area. Encrypt the crack path area of the second grid to obtain the encrypted grid.

9. A system for testing the explosion shock characteristics of rocks and composite materials using the multi-variable coupling control described in any one of claims 1-8, comprising: An initial grid division module for dividing the rock material gradient based on the gradient sensitive function and generating the initial grid. A grid encryption module for encrypting the explosion hole and crack path areas of the initial grid based on the multi-physical field response characteristics to obtain the encrypted grid. An explosion characteristic simulation module for constructing a multi-field coupling model based on the encrypted grid, the RHT model, and the heat conduction equation and outputting the simulation results. An experimental inversion module for conducting explosion experiments and inversely calculating the dynamic strength and fracture toughness parameters of the material by comparing the simulation results with the experimental data.

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