Stress distribution characteristic prediction method, electronic equipment, storage medium and device

Abstract

The invention discloses a stress distribution characteristic prediction method, electronic equipment, a storage medium and a device. The method comprises the following steps: constructing a geometric model according to physical property parameters of a seismic source holder and a seismic source, a seismic source holder structure and a rock sample; generating a numerical model according to the geometric model, and performing mesh generation on the numerical model; a control equation is loaded on the numerical model subjected to mesh generation; loading boundary conditions and axial stress to the numerical model completing the loading control equation; solving a control equation through a PARDISO method, and predicting the distribution characteristics of a displacement field, a stress field and an electric field at different times when the numerical model is in the quasi-static state of the low-frequency seismic source through time parameter scanning. Based on the multi-field coupling theory, the contact boundary condition is established, the real state of the low-frequency seismic source under high pressure is simulated, the stress distribution characteristics of the low-frequency seismic source holder under high pressure can be directly predicted, and a direct basis is provided for manufacturing the low-frequency seismic source holder capable of bearing high pressure.

Description

Technical Field

[0001] The present invention belongs to the technical field of seismic rock physics, and more specifically, relates to a method for predicting stress distribution characteristics, an electronic device, a storage medium, and a device. Background Art

[0002] The stress-strain method obtains the elastic modulus and attenuation of a rock sample by recording the amplitude and phase of stress and the axial and radial strains of the rock sample. The stress-strain experiment maintains a quasi-static state during the stress loading and unloading of the rock sample. When the working frequency of the seismic source is in the seismic frequency band and the strain amplitude is lower than 10 -6 , the stress-strain method can be used to obtain the elastic parameters of the rock in the seismic frequency band. Since the frequency band of these elastic parameters is much lower than the ultrasonic frequency band, they are often referred to as low-frequency measurements. In recent years, scholars such as Batzle (2006), Madonna and Tisato (2013), Mikhaltsevitch et al. (2014), and Tisato and Madonna (2012) have developed low-frequency rock physics equipment. However, due to the pressure-bearing upper limit of the piezoelectric seismic source (for example, 35 MPa), high-pressure measurements have become infeasible. This highlights the importance of developing a seismic source that can withstand high pressure and is suitable for low-frequency measurements. Given the pressure-bearing limitations of piezoelectric ceramics, it is particularly crucial to design a suitable holder that can protect the piezoelectric seismic source under high pressure. Although these tasks can be completed through conventional practices such as continuous experiments, the high cost of materials means that a single design mistake may lead to damage to the seismic source. In order to save materials and time and accurately design the piezoelectric seismic source holder, it is extremely important to use numerical simulation methods to obtain the pressure characteristics of the low-frequency seismic source holder.

[0003] The information disclosed in the background art section of the present invention is only intended to deepen the understanding of the general background art of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0004] The object of the present invention is to propose a method for predicting stress distribution characteristics, an electronic device, a storage medium, and a device, to realize a method that can accurately predict the pressure distribution characteristics of a low-frequency seismic source holder when working in a high-pressure environment, and solve the problem that the low-frequency seismic source device cannot test the stress distribution characteristics of different materials and structures in a high-pressure environment.

[0005] To achieve the above object, the present invention proposes a method for predicting stress distribution characteristics, an electronic device, a storage medium, and a device.

[0006] According to the first aspect of the present invention, a method for predicting stress distribution characteristics is proposed, including:

[0007] Construct a geometric model based on the physical properties of the seismic source holder and the seismic source, the structure of the seismic source holder, and the rock sample;

[0008] Generate a numerical model according to the geometric model and perform mesh generation on the numerical model;

[0009] Load the governing equations into the numerical model that has completed mesh generation;

[0010] Load the boundary conditions and axial stress into the numerical model that has completed loading the governing equations;

[0011] Solve the governing equations by the PARDISO method and predict the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in the quasi-static state of a low-frequency seismic source through time parameter scanning.

[0012] Optionally, perform high-quality mesh generation on the numerical model using hexahedral meshes and tetrahedral meshes.

[0013] Optionally, loading the governing equations includes:

[0014] Load the first governing equation into the numerical model:

[0015]

[0016] where σ is the stress tensor, C is the stiffness matrix, and C is composed of the Young's modulus E, Poisson's ratio υ, and shear modulus G of the solid material, is the gradient operator.

[0017] Optionally, loading the governing equations further includes:

[0018] Load the second governing equation into the seismic source:

[0019]

[0020] where u is the displacement, V is the voltage, e is the coupling matrix, ε 0 is the air dielectric constant, ε r is the relative dielectric parameter of the seismic source material, · is the dot product, is the divergence operator.

[0021] Optionally, loading the boundary conditions includes:

[0022] Use contact boundary conditions at the contact interface between the seismic source and the seismic source holder and at the contact interface between the seismic source holder and the rock sample:

[0023]

[0024] where pn is the penalty function factor, g n is the contact gap function, p 0 is the pressure when the contact gap is 0. If means if, else means otherwise, that is, if g n < p 0 / p n , T n = - p n g n + p 0 , otherwise, T n = 0.

[0025] Optionally, loading the axial prestress includes:

[0026] Loading axial stress at the upper end of the seismic source holder. For convenience of calculation, loading a fixed displacement along the axis at the top of the rock sample or the seismic source holder. Let u z = u 0 ;

[0027] Loading fixed constraint boundary conditions at the bottom of the seismic source holder, making the displacement u = 0;

[0028] wherein, u z is the component of the displacement vector u along the z direction, and u 0 is a specific displacement, generally in the order of millimeters.

[0029] Optionally, loading the boundary conditions further includes:

[0030] The seismic source is a piezoelectric material, and the seismic source is excited to deform by loading a periodically oscillating voltage; loading a voltage on the upper part of the seismic source:

[0031] A * sin(2 * pi * f0 * t);

[0032] Loading a voltage of 0 on the lower part of the seismic source;

[0033] wherein, A is the amplitude, f0 is the frequency, and t is the vibration time.

[0034] According to the second aspect of the present invention, a stress distribution characteristic prediction device is proposed, including:

[0035] A construction module, configured to construct a geometric model according to the physical property parameters of the seismic source holder and the seismic source, the seismic source holder structure, and the rock sample;

[0036] A generation and meshing module, configured to generate a numerical model according to the geometric model and perform mesh generation on the numerical model;

[0037] A first loading module, configured to load a control equation on the numerical model that has completed mesh generation;

[0038] A second loading module, configured to load boundary conditions and axial stress to the numerical model that has completed loading the control equation;

[0039] A solving and predicting module, configured to solve the control equation by the PARDISO method, and predict the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in a quasi-static state of a low-frequency vibration source through time parameter scanning.

[0040] According to a third aspect of the present invention, there is provided an electronic device, which includes:

[0041] At least one processor; and,

[0042] A memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute any of the stress distribution characteristic prediction methods in the first aspect.

[0044] According to a fourth aspect of the present invention, there is provided a non-transitory computer-readable storage medium, which stores computer instructions for causing a computer to execute any of the stress distribution characteristic prediction methods in the first aspect.

[0045] The beneficial effects of the present invention are as follows: Based on the multi-field coupling theory, the present invention establishes contact boundary conditions, loads the control equation, simulates the real state of a low-frequency vibration source under high pressure, and uses time parameter scanning to achieve the quasi-static working state of the low-frequency vibration source under high pressure, and predicts the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in a quasi-static state of a low-frequency vibration source; The traditional method can only predict the dynamic stress distribution state, uses continuous boundary conditions at each contact interface, and does not consider the multi-field coupling of piezoelectric materials; The present invention can avoid the drawback that it is necessary to conduct experiments to determine the quality of the design scheme when manufacturing a high-pressure-resistant vibration source, and greatly saves production materials and time; The present invention can directly predict the stress distribution characteristics of a low-frequency vibration source gripper under high pressure, providing a direct basis for manufacturing a low-frequency vibration source gripper that can bear high pressure; The present invention can accurately predict the pressure distribution characteristics when the low-frequency vibration source gripper works in a high-pressure environment, and solve the problem that the low-frequency vibration source device cannot test the stress distribution characteristics of different materials and structures in a high-pressure environment.

[0046] The system of the present invention has other characteristics and advantages, which will be apparent from the accompanying drawings incorporated herein and the subsequent detailed description, or will be described in detail in the accompanying drawings incorporated herein and the subsequent detailed description, and these accompanying drawings and detailed description are used together to explain the specific principles of the present invention. Description of the Drawings

[0047] By describing the exemplary embodiments of the present invention in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present invention will become more apparent. In the exemplary embodiments of the present invention, the same reference numerals generally represent the same components.

[0048] Figure 1 A flowchart showing the steps of a method for predicting stress distribution characteristics according to the present invention is shown.

[0049] Figure 2 A schematic diagram showing the geometric model and numerical model according to Embodiment 2 of the present invention is shown.

[0050] Figure 3 A schematic diagram showing the numerical model with the control equation loaded according to Embodiment 2 of the present invention is shown.

[0051] Figure 4 A schematic diagram showing the numerical model with boundary conditions and axial prestress loaded according to Embodiment 2 of the present invention is shown.

[0052] Figure 5 A stress distribution characteristic diagram selected along the axis direction of the numerical model according to Embodiment 2 of the present invention is shown.

[0053] Figure 6 A schematic diagram showing the stress distribution characteristics of the numerical model along the axis direction according to Embodiment 2 of the present invention is shown.

[0054] Figure 7 A distribution characteristic diagram of the electric field of the numerical model at different times according to Embodiment 2 of the present invention is shown.

[0055] Figure 8 An implementation effect diagram of the displacement caused by the piezoelectric material according to Embodiment 2 of the present invention is shown.

[0056] Figure 9 A schematic diagram showing a device for predicting stress distribution characteristics according to Embodiment 3 of the present invention is shown. Detailed Description

[0057] The present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0058] As Figure 1 shown, a method for predicting stress distribution characteristics according to the present invention includes:

[0059] Constructing a geometric model based on the physical property parameters of the seismic source holder and the seismic source, the structure of the seismic source holder, and the rock sample;

[0060] Generating a numerical model based on the geometric model and performing mesh generation on the numerical model;

[0061] Loading the control equation on the numerically modeled model that has completed mesh generation;

[0062] Loading the boundary conditions and axial stress on the numerically modeled model that has completed loading the control equation;

[0063] Solving the control equation by the PARDISO method and predicting the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in the quasi-static state of a low-frequency seismic source through time parameter scanning.

[0064] Specifically, the present invention first designs a seismic source holder with a specific structure and specific material, and establishes a geometric model of the seismic source holder, the seismic source, and the rock sample based on the physical property parameters of the material of the seismic source holder, the structure of the seismic source holder, the physical property parameters of the material of the seismic source, the structure and material of the rock sample. The material of the seismic source is a piezoelectric material, and the physical property parameters of the piezoelectric material and the material of the seismic source holder are obtained through experiments. Then, a numerical model is generated based on this geometric model, and high-quality mesh generation is performed on the numerical model by combining hexahedral meshes and tetrahedral meshes. The first control equation is loaded on all numerically modeled regions, and the second control equation is loaded on the piezoelectric material. Contact boundary conditions are loaded on the contact interfaces between the seismic source and the seismic source holder and between the seismic source holder and the rock sample. Axial stress is loaded on the upper end of the holder. For the convenience of calculation, a fixed displacement is loaded along the axis at the top of the rock sample or the seismic source holder, a fixed constraint boundary condition is loaded at the bottom of the seismic source holder, a periodically oscillating voltage is loaded on the upper part of the seismic source, and a grounded voltage is loaded on the lower part of the seismic source. The grounded voltage is zero. According to the meshed grid, the loaded control equation, boundary conditions, stress, and voltage, the PARDISO method is used for solving, and the time parameter is scanned to predict the distribution characteristics of the displacement field, stress field, and voltage field at different times.

[0065] In one example, high-quality mesh generation is performed on the numerical model by hexahedral meshes and tetrahedral meshes.

[0066] In one example, the loading control equation includes:

[0067] Loading the first control equation into the numerical model:

[0068]

[0069] where σ is the stress tensor, C is the stiffness matrix, and C is composed of the Young's modulus E, Poisson's ratio υ, and shear modulus G of the solid material, is the gradient operator.

[0070] In one example, the loading control equation further includes:

[0071] Loading the second control equation into the source:

[0072]

[0073] where u is the displacement, V is the voltage, e is the coupling matrix, ε 0 is the air dielectric coefficient, ε r is the relative dielectric parameter of the source material, · is the dot product, is the divergence operator.

[0074] Specifically, loading the second control equation into the piezoelectric material. Since the material of the source is the piezoelectric material, the second control equation is loaded into the source.

[0075] In one example, the loading boundary conditions include:

[0076] Using the contact boundary conditions at the contact interface between the source and the source holder and at the contact interface between the source holder and the rock sample:

[0077]

[0078] where p n is the penalty function factor, g n is the contact gap function, p 0 is the pressure when the contact gap is 0, If means if, else means otherwise, that is, if g n <p 0 / p n , T n =-p n g n +p 0 , otherwise, T n =0.

[0079] In one example, the loading axial prestress includes:

[0080] Axial stress is applied to the upper end of the seismic source clamp. For the convenience of calculation, a fixed displacement is applied axially at the top of the rock sample or the seismic source clamp, and let u z = u 0 ;

[0081] A fixed constraint boundary condition is applied to the bottom of the seismic source clamp, and let the displacement u = 0;

[0082] wherein, u z is the component of the displacement vector u along the z direction, and u 0 is a specific displacement, generally on the order of millimeters.

[0083] In one example, the loading boundary conditions further include:

[0084] The seismic source is a piezoelectric material, and the seismic source is excited to deform by applying a periodically oscillating voltage; a voltage is applied to the upper part of the seismic source:

[0085] A*sin(2*pi*f0*t);

[0086] A voltage of 0 is applied to the lower part of the seismic source;

[0087] wherein, A is the amplitude, f0 is the frequency, and t is the vibration time.

[0088] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but it is not a limitation of the present invention. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0089] Embodiment 1

[0090] This embodiment provides a method for predicting stress distribution characteristics, including:

[0091] First, a seismic source clamp with a specific structure and specific material is designed. A geometric model of the seismic source clamp, the seismic source, and the rock sample is established according to the physical property parameters of the material of the seismic source clamp, the structure of the seismic source clamp, the physical property parameters of the material of the seismic source, and the structure and material of the rock sample. The material of the seismic source is a piezoelectric material, and the physical property parameters of the piezoelectric material and the material of the seismic source clamp are obtained through experiments; then a numerical model is generated based on this geometric model, and high-quality mesh division is performed on the numerical model in combination with hexahedral meshes and tetrahedral meshes; a first control equation is applied to all numerical model regions, and the first control equation is: wherein, σ is the stress tensor, C is the stiffness matrix, and C is composed of the Young's modulus E, Poisson's ratio υ, and shear modulus G of the solid material, is the gradient operator. A second control equation is applied to the piezoelectric material, and the second control equation is: wherein, u is the displacement, V is the voltage, e is the coupling matrix, ε0 is the air dielectric constant, ε r is the relative dielectric parameter of the source material, · is the dot product, is the divergence operator. Contact boundary conditions are applied at the contact interface between the source and the source holder, and at the contact interface between the source holder and the rock sample: where p n is the penalty function factor, g n is the contact gap function, p 0 is the pressure when the contact gap is 0. If means if, else means otherwise, that is, if g n < p 0 / p n , T n = -p n g n + p 0 , otherwise, T n = 0; An axial stress is applied at the upper end of the holder. For ease of calculation, a fixed displacement is applied axially at the top of the rock sample or the source holder. Let u z = u 0 . A fixed constraint boundary condition is applied at the bottom of the source holder, making the displacement u = 0. Here, u z is the component of the displacement vector u along the z - direction, u 0 is a specific displacement, generally on the order of millimeters; A periodic oscillating voltage: A*sin(2*pi*f0*t) is applied at the upper part of the source, where A is the amplitude, f0 is the frequency, and t is the vibration time; A grounded voltage is applied at the lower part of the source, and the grounded voltage is zero; According to the meshed grid, the loaded control equations, boundary conditions, stress, and voltage, the PARDISO method is used to solve, and the time parameter is scanned to predict the distribution characteristics of the displacement field, stress field, and voltage field at different times.

[0092] Example 2

[0093] This example provides a method for predicting stress distribution characteristics, including:

[0094] Geometric model construction: Design a source holder with a specific structure and specific material, and construct a geometric model based on the holder structure, as shown in the left figure of Figure 2 . The material physical property parameters are obtained through experimental measurements, including the density and elastic parameters of the holder material, the relevant parameters of the piezoelectric source material, etc. The physical property parameters of the solid material are shown in Table 1, and the physical property parameters of the piezoelectric material are shown in Table 2.

[0095] Mesh generation: High - quality mesh generation of the numerical model is carried out by combining hexahedral meshes and tetrahedral meshes, as shown in the right figure of Figure 2 ;

[0096] Control equation construction: Apply the control equation (1) to all model regions and the control equation (2) to the piezoelectric material (the source), as Figure 3 shown;

[0097]

[0098]

[0099] where σ is the stress tensor, specifically characterized as C is the stiffness matrix, composed of the Young's modulus E, Poisson's ratio v, and shear modulus G of the solid material, is the gradient operator, u is the displacement, V is the voltage, and e is the coupling matrix. In Equation 2, ε 0 is the air dielectric coefficient, and ε r is the relative dielectric parameter of the material. · is the dot product, is the divergence operator.

[0100] Apply the boundary conditions, as Figure 4 shown;

[0101] (1) For the contact interfaces between the source and the gripper, and between the gripper and the rock sample, use the contact boundary conditions. The contact interface pressure is defined as:

[0102]

[0103] where p n is the penalty function factor, g n is the contact gap function, and p 0 is the pressure when the contact gap is 0. If means if, that is, if g n <p 0 / p n , T n =-p n g n +p 0 , otherwise, T n =0.

[0104] (2) Axial prestress of the sample: Apply axial stress at the upper end of the gripper. For convenience of calculation, apply a fixed displacement along the axial direction at the top of the sample or the gripper, and let u z =u 0 , where u z is the component of the displacement vector u along the z direction, and u 0 is a specific displacement, generally on the order of millimeters.

[0105] (3) Piezoelectric material boundary conditions: The seismic source is a piezoelectric material, which is excited to deform by applying a periodically oscillating voltage. Specifically, a voltage of A*sin(2*pi*f0*t) is applied to the upper part, where A is the amplitude, f0 is the frequency, and t is the vibration time. Therefore, the entire change process is quasi-static. The voltage applied to the lower part of the seismic source is 0, which is the grounded voltage.

[0106] (4) Fixed boundary conditions: Fixed constraint boundary conditions are applied at the bottom of the gripper, setting the displacement u = 0;

[0107] Parameter scanning is performed to obtain the distribution characteristics of the stress field and electric field under quasi-static conditions of the low-frequency seismic source. Based on the mesh, governing equations, and boundary conditions, the PARDISO method is used for solving. By scanning the parameter t, the characteristics of the displacement field u, stress field σ, and voltage field V at different times are obtained. The stress distribution state is as Figure 5 shown. The stress distribution in the sample is uniform under high pressure, while the piezoelectric seismic source bears very little stress. To illustrate this more clearly Figure 6 shows the stress distribution characteristics selected along the axis direction of the numerical model. The gray area represents the range of the piezoelectric seismic source. It can be seen that the stress at the location of the seismic source is less than 20 MPa. Further, by scanning the time parameter t, the characteristics of the stress field at different times are obtained. Figure 7 a shows the electric field characteristics at t = 0 s. At this time, the electric field distribution range is from -800 V to 800 V. Figure 7 b shows the electric field characteristics at t = 0.01 s. At this time, the piezoelectric material is in the maximum compression state and the material is in the polarized state. Figure 7 c shows the electric field characteristics at t = 0.035 s. At this time, the piezoelectric material is in the maximum stretching state and the material is in the polarized state. The implementation effect of the displacement caused by the piezoelectric material is as Figure 8 shown. The longitudinal unit coordinate is microstrain, and the horizontal coordinate is the range of the time parameter scan, with the unit of second (s). It can be seen that as time increases, the strain shows periodic vibration. After removing the pre-strain of 0.01 mm, the effective amplitude of the strain of the rock sample is about 10 -7 or so, which is in line with the prediction.

[0108] Table 1 Solid material parameters

[0109]

[0110] Table 2 Piezoelectric material parameters

[0111]

[0112]

[0113] Example 3

[0114] As Figure 9As shown in the figure, this embodiment provides a stress distribution characteristic prediction device, including:

[0115] A construction module, configured to construct a geometric model according to the physical property parameters of the seismic source gripper and the seismic source, the structure of the seismic source gripper, and the rock sample;

[0116] A generation and meshing module, configured to generate a numerical model according to the geometric model and perform mesh division on the numerical model;

[0117] A first loading module, configured to load a control equation into the numerically modeled model that has completed mesh division;

[0118] A second loading module, configured to load boundary conditions and axial stress into the numerically modeled model that has completed loading the control equation;

[0119] A solution and prediction module, configured to solve the control equation by the PARDISO method and predict the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in a low-frequency seismic source quasi-static state through time parameter scanning.

[0120] Embodiment 4

[0121] This embodiment provides an electronic device, which includes:

[0122] At least one processor; and,

[0123] A memory communicatively connected to the at least one processor; wherein,

[0124] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the stress distribution characteristic prediction method in Embodiment 1.

[0125] The electronic device according to an embodiment of the present disclosure includes a memory and a processor, and the memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0126] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In an embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0127] Those skilled in the art should be able to understand that, in order to solve the technical problem of how to obtain good user experience effects, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included in the protection scope of this disclosure.

[0128] For the detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details will not be repeated here.

[0129] Embodiment 5

[0130] This embodiment provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to execute the stress distribution feature prediction method in Embodiment 1.

[0131] According to the computer-readable storage medium of an embodiment of the present disclosure, non-temporary computer-readable instructions are stored thereon. When the non-temporary computer-readable instructions are run by a processor, all or part of the steps of the methods of the foregoing embodiments of the present disclosure are executed.

[0132] The above computer-readable storage medium includes but is not limited to: optical storage media (such as CD-ROMs and DVDs), magneto-optical storage media (such as MOs), magnetic storage media (such as magnetic tapes or external hard drives), media with built-in rewritable non-volatile memories (such as memory cards), and media with built-in ROMs (such as ROM cartridges).

[0133] The embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for predicting stress distribution characteristics, characterized in that, it includes: Constructing a geometric model based on the physical properties of the seismic source holder and the seismic source, the structure of the seismic source holder, and the rock sample; Generating a numerical model according to the geometric model and performing mesh division on the numerical model; Loading a control equation on the numerically modeled model that has completed mesh division; Loading boundary conditions and axial stress on the numerically modeled model that has completed loading the control equation; Solving the control equation by the PARDISO method and predicting the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in the quasi-static state of a low-frequency seismic source through time parameter scanning.

2. The stress distribution characteristic prediction method according to claim 1, characterized in that, Performing high-quality mesh division on the numerical model through hexahedral meshes and tetrahedral meshes.

3. The stress distribution characteristic prediction method according to claim 1, characterized in that, Loading the control equation includes: Loading a first control equation on the numerical model: where σ is the stress tensor, C is the stiffness matrix, which is composed of the Young's modulus E, Poisson's ratio υ, and shear modulus G of the solid material, is the gradient operator.

4. The stress distribution characteristic prediction method according to claim 3, characterized in that, Loading the control equation further includes: Loading a second control equation on the seismic source: Among them, u is displacement, V is voltage, e is the coupling matrix, and ε 0 is the air dielectric constant, and ε r is the relative dielectric parameter of the source material, · is the dot product, is the divergence operator.

5. The stress distribution characteristic prediction method according to claim 1, characterized in that, Loading the boundary conditions includes: Using contact boundary conditions at the contact interface between the seismic source and the seismic source holder and at the contact interface between the seismic source holder and the rock sample: Among them, p n is the penalty function factor, g n is the contact clearance function, p 0 is the pressure when the contact clearance is 0. If means if, else means otherwise, that is, if g n < p 0 / p n , T n = - p n g n + p 0 , otherwise, T n = 0.

6. The stress distribution characteristic prediction method according to claim 1, characterized in that, Loading the axial prestress includes: Axial stress is applied to the upper end of the seismic source holder. For the convenience of calculation, a fixed displacement is applied axially along the top of the rock sample or the seismic source holder, and let u z = u 0 ; Loading a fixed constraint boundary condition at the bottom of the seismic source holder, setting the displacement u = 0; where, u z is the component of the displacement vector u along the z direction, and u 0 is a specific displacement, generally on the order of millimeters.

7. The stress distribution characteristic prediction method according to claim 1, characterized in that, Loading the boundary conditions further includes: The seismic source is a piezoelectric material, and the seismic source is excited to deform by loading a periodically oscillating voltage; loading a voltage on the upper part of the seismic source: A*sin(2*pi*f0*t); Loading a voltage of 0 on the lower part of the seismic source; wherein, A is the amplitude, f0 is the frequency, and t is the vibration time.

8. An electronic device, characterized in that, the electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the stress distribution characteristic prediction method according to any one of claims 1-7.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to execute the stress distribution characteristic prediction method according to any one of claims 1-7.

10. A stress distribution characteristic prediction device, characterized in that, it includes: A construction module for constructing a geometric model based on the physical properties of the seismic source holder and the seismic source, the structure of the seismic source holder, and the rock sample; A generation and division module for generating a numerical model according to the geometric model and performing mesh division on the numerical model; The first loading module is used to load the governing equations into the numerical model that has completed mesh generation. The second loading module is used to load the boundary conditions and axial stress into the numerical model that has completed the loading of the governing equations. The solving and prediction module is used to solve the governing equations by the PARDISO method and predict the distribution characteristics of the displacement field, stress field, and electric field at different times when the numerical model is in the quasi-static state of low-frequency seismic sources through time parameter scanning.

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