Method for predicting distribution characteristics of particles in valve under moisture and solid conditions

Abstract

The invention relates to the technical field of numerical simulation, and discloses a method for predicting distribution characteristics of particles in a valve under moisture and solid conditions. The method comprises the following steps: establishing a three-dimensional model of the valve, carrying out grid division on the model, correcting a tangential recovery coefficient and a normal recovery coefficient by combining particle collision rebound characteristics under a moisture-solid condition, carrying out numerical simulation by utilizing the corrected collision rebound model, and obtaining simulation data. Through data extraction and image processing, a valve internal flow distribution characteristic graph and a particle distribution characteristic graph are generated, a particle accumulation area is judged according to the characteristic graphs, particle number density is extracted, and high-concentration particle distribution in the valve is quantitatively analyzed. And on the basis of the quantitative analysis result, particle trapping rate parameters are extracted, and particle trapping characteristics caused by a wall surface liquid film under the moisture-solid condition are obtained. The method can effectively predict distribution and accumulation characteristics of particles in the valve, and provides a basis for design and optimization of the valve.

Description

Technical Field

[0001] The present application relates to the field of numerical simulation technology, and in particular to a method for predicting particle distribution characteristics inside a valve under wet solid conditions. Background Art

[0002] Valves are used to regulate and control the flow of media in industrial production and are widely used in the fields of chemical industry, petroleum, and electricity. With the development of industrial technology, the application scenarios of gas-solid two-phase flow are increasing. For example, when conveying industrial gas containing solid particles under high temperature and high pressure, the particles may accumulate or aggregate due to wall wetting, affecting the stability of fluid flow and valve performance.

[0003] At present, the research on two-phase flow under wet gas-solid conditions is relatively limited. Existing research mainly focuses on dry environments, and the relevant models are difficult to accurately describe the impact of liquid film on particle collision and aggregation behavior, resulting in insufficient prediction accuracy of particle distribution characteristics. In addition, the applicability of existing numerical simulation methods under wet gas-solid conditions is low, and it is difficult to meet the needs of valve design and maintenance for the prediction of particle distribution characteristics.

[0004] Therefore, research on the particle distribution characteristics under wet solid conditions can provide effective data support for optimizing valve performance, which is of great significance to improving the efficiency and safety of industrial processes. Summary of the invention

[0005] The purpose of the embodiment of the present application is to provide a method for predicting the particle distribution characteristics inside a valve under wet solid conditions, so as to solve the problem that it is difficult to accurately predict the particle collision rebound and accumulation behavior under wet solid conditions in the prior art, especially under the influence of the wall liquid film, the prediction accuracy of the particle accumulation area and the capture rate is limited. This method effectively makes up for the above shortcomings and provides a reliable basis for the optimal design of the valve.

[0006] According to an embodiment of the present application, a method for predicting particle distribution characteristics inside a valve under wet solid conditions is provided, comprising: S1: Establish a three-dimensional model of the valve; S2: Meshing the three-dimensional model of the valve; S3: The three-dimensional valve model after meshing is combined with the particle collision and rebound characteristics under wet solid conditions, the tangential restitution coefficient and the normal restitution coefficient in the particle collision and rebound model are corrected, and numerical simulation is carried out on the corrected particle collision and rebound model to obtain simulation data; S4: extracting data from the simulation data and then performing image processing to obtain a flow distribution characteristic map and a particle distribution characteristic map; S5: judging the particle accumulation occurrence area according to the flow distribution characteristic diagram and the particle distribution characteristic diagram; S6: extracting the particle number density according to the particle accumulation occurrence area, and using a particle number density analysis method to quantitatively analyze the distribution of high-concentration particles inside the valve under wet solid conditions; S7: extracting a particle capture rate parameter according to the result of the quantitative analysis, and further obtaining the particle capture characteristics caused by the wall liquid film under wet solid conditions; The tangential restitution coefficient The expression is as follows: ; The normal restitution coefficient The expression is as follows: ; in, is the fitting coefficient, is the critical angle, is the particle tilt impact angle.

[0007] The technical solution provided by the embodiments of the present application may have the following beneficial effects: It can be seen from the above embodiments that the embodiments of the present application use three-dimensional model construction, grid division and modified particle collision rebound model, and modify the tangential restitution coefficient and normal restitution coefficient in combination with the particle motion characteristics under wet solid conditions, thereby overcoming the technical problem that the model under the traditional dry wall surface cannot accurately reflect the particle collision rebound and accumulation behavior under wet solid conditions, thereby improving the accuracy of particle distribution prediction under wet solid conditions. By introducing the quantitative analysis method of particle number density, the problem of insufficient accuracy of particle accumulation area and capture rate analysis in the prior art is solved, thereby achieving accurate identification and quantitative analysis of particle accumulation areas. Finally, by extracting the particle capture rate parameter, the influence characteristics of the wet wall surface on the particle distribution are further obtained, thereby providing a more accurate technical basis for valve design optimization.

[0008] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0010] Figure 1 It is a flow chart of a method for predicting particle distribution characteristics inside a valve under wet solid conditions according to an exemplary embodiment.

[0011] Figure 2 is a three-dimensional model diagram of a ball valve according to an exemplary embodiment.

[0012] Figure 3 The figure is a flowchart of ball valve meshing according to an exemplary embodiment.

[0013] Figure 4 It is a schematic diagram of the calculation area of ​​the internal flow channel of a ball valve according to an exemplary embodiment.

[0014] Figure 5 It is a schematic diagram of local mesh encryption of a three-dimensional model of a ball valve according to an exemplary embodiment.

[0015] Figure 6 is a schematic diagram showing the rebound of particles from colliding with a wall according to an exemplary embodiment.

[0016] Figure 7 It is a flow chart of a UDF file of boundary conditions of a particle collision and rebound model under wet conditions according to an exemplary embodiment.

[0017] Figure 8 is a grid unit arrangement for solving particle density according to an exemplary embodiment. DETAILED DESCRIPTION

[0018] Here, exemplary embodiments will be described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0019] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0020] Figure 1 is a flow chart of a method for predicting particle distribution characteristics inside a valve under wet solid conditions according to an exemplary embodiment. Figure 1 As shown, the method includes the following steps: In the specific implementation of step S1, a three-dimensional model of the valve is established; Specifically, a 3D model is established according to the actual geometric dimensions of the valve through operations such as stretching, arraying, mirroring, cutting, and rotating of the 3D modeling software SOLIDWORKS. Figure 2As shown in the figure, the valve stem 1, bracket 2, valve cover 3, ball 4, valve seat 5, and valve body 6 are modeled separately and assembled into a complete ball valve model. The assembled ball valve 3D model is exported into STEP format to facilitate the subsequent model import into Ansys SpaceClaim software for model pre-processing.

[0021] In the specific implementation of step S2, the three-dimensional model of the valve is meshed; Specifically, the 3D model of the valve is imported into Ansys SpaceClaim software for model preprocessing, and then meshed in FLUENT MESHING software. The number of meshes is set, and local mesh encryption is performed on the valve cavity area inside the valve to ensure high-precision meshes in the fluid and particle interaction area, so as to more accurately reflect the flow characteristics.

[0022] The flowchart of grid division is as follows Figure 3 As shown, it includes importing models and preprocessing, defining mesh areas, generating meshes, checking mesh quality, and flow coefficients. , fine mesh, flow coefficient , compare flow coefficients, compare minimum grid sizes and particle diameter , the next step is numerical solution.

[0023] In the import model and preprocessing, in order to reduce the subsequent meshing calculation and improve mesh accuracy, the valve 3D model was simplified in Ansys SpaceClaim software, only the parts related to the flow channel were retained, irrelevant parts such as brackets were deleted, holes, holes and gaps irrelevant to the flow channel were filled, chamfers and fillets were deleted, and concave and convex areas were filled. In order to ensure that the gas medium in the ball valve pipeline and the solid particles in the medium are fully mixed, the upstream pipeline length of the ball valve is extended to 10 times the pipeline diameter through the "pull" function, and the downstream pipeline length is extended to 10 times the pipeline diameter.

[0024] In the defined mesh area, name the valve wall, inlet and outlet, and the valve cavity area inside the valve to be meshed. Then, select the named inlet and outlet surfaces in "Volume Extraction" in the "Preparation" tab to extract the fluid domain inside the valve and name it "fluid". Finally, choose to convert to the "FLUENTMESHING" software in the "Workbench" tab.

[0025] In the mesh generation, select the "Watertight Geometry" workflow in the "FLUENT MESHING" software. After importing the geometric model, add local dimensions to the named valve inner surface to be meshed to encrypt the local mesh. Then, generate the surface mesh. When describing the geometric structure, check "The geometric model consists only of fluid areas without gaps" and update the boundary conditions to pressure outlet and pressure inlet. Add boundary layers, and finally select the polyhedral mesh "poly-hexcore" to generate the volume mesh, such as Figure 4 The dotted box is a schematic diagram of the calculation domain of the internal flow channel of the ball valve. Figure 5 Schematic diagram of local mesh encryption inside the valve.

[0026] In the mesh quality check, click "Perform mesh check" in the "Mesh" tab. The mesh quality parameters can be seen on the console below. Pay attention to whether there is negative volume and orthogonal quality. If negative volume or orthogonal quality is lower than 0.5, you need to return to the "Model Import and Preprocessing" step and modify it again.

[0027] After completing the mesh quality check, the flow coefficient As the target variable, the grid independence verification is started. Specifically, the initial grid is first used for numerical solution to obtain the flow coefficient Then, by adjusting the minimum grid size By refining the number of grids, the numerical solution is re-calculated to obtain the flow coefficient Compare the errors of the two flow coefficients. If the error exceeds 5%, continue to refine the grid and solve again, gradually optimizing the grid division until the error of the flow coefficient is less than 5%. If the error is less than 5%, it indicates that the numerical solution is basically independent of the grid division. Next, compare the minimum size of the grid. and particle diameter .like , then the current grid division passes the independence verification and can be used for subsequent numerical solutions; if , then return to the "Generate Mesh" step and readjust the mesh density to ensure mesh independence and accuracy of particle distribution characteristics.

[0028] The mesh quality of the exemplary embodiments in the present disclosure finally reaches above 0.7, which meets the requirements of numerical simulation calculations and can be used for the next step of solution.

[0029] In the specific implementation of step S3, the three-dimensional valve model after meshing is combined with the particle collision and rebound characteristics under wet solid conditions, and the tangential recovery coefficient in the particle collision and rebound model is calculated. and normal restitution coefficient Correction is made, and numerical simulation is carried out on the corrected particle collision and rebound model to obtain simulation data; Specifically, when directly calculating gas-solid two-phase flow, it is often difficult to achieve stable convergence of calculations or obtain ideal calculation accuracy due to the strong coupling between particles and gas in the flow field and the complexity of particle motion. Therefore, in order to improve the calculation efficiency and the accuracy of the results, it is necessary to proceed in two steps: first, establish a stable gas flow field through numerical simulation to ensure that the basic characteristics of gas flow reach a stable state; then, on this basis, introduce particles and further calculate the particle motion trajectory, distribution characteristics and interaction with the wall in the gas flow field.

[0030] More specifically, first, import the meshed 3D valve model into the FLUENT software, and set a unified mesh unit in the "Mesh Scaling" tab; establish a single-phase gas flow field, set "Steady State" and "Gravity Acceleration" in the "General" tab; open "Energy" and "Viscosity" in the "Model" tab, and set SST turbulence model and wall function; set the single-phase gas to "air" in the "Material" tab; set the fluid domain material to "air" in the "Unit Area Conditions" tab; define the boundary conditions of "outlet" and "inlet" as pressure in the "Boundary Conditions" tab; set the calculation method to Coupled and the control method to default in the "Solution" tab; set the convergence residual value in the "Calculation Monitoring" tab; set the initialization method to "Standard Initialization" in the "Initialization" tab, and click the "Initialize" button to complete the initialization settings; set the number of iterations and time step in the "Calculation Settings" tab, and click "Start Calculation".

[0031] Secondly, through the particle collision and rebound experiment with the wall with liquid film, the normal component and tangential component of the particle velocity when colliding are analyzed, such as Figure 6 The figure shows the schematic diagram of the particle colliding with the wall and rebounding, and the tangential restitution coefficient is obtained. and normal restitution coefficient , and is used to correct the tangential restitution coefficient and normal restitution coefficient of the particle collision rebound model under wet solid conditions; Finally, after the calculation is completed and a stable flow field is obtained, set "Transient" and "Gravity Acceleration" in the "General" tab; open "Discrete Phase" in the "Model" tab, check "Interaction with Continuous Phase", and create a "Jet Source", select "Particle Type" as "Inert", and select "Jet Source Type" as "file", where "file" is an externally imported user-defined particle package file; select "Function" in the "User Defined" tab and load the reflection boundary condition UDF function of the particle collision and rebound model under modified wet solid conditions, and set the "Discrete Phase Boundary Type" in the DPM of all walls in the "Boundary Conditions" tab to "user-defined" and set the "Discrete Phase BC Function" to the custom file "bc_reflect::libduf"; set the number of iterations and time step in the "Run Calculation" tab, and click "Start Calculation"; after calculation, obtain the data of the CASE file and DATE file.

[0032] By pre-constructing the gas flow field before particle calculation, the problem of difficult convergence and large errors in directly calculating two-phase flow in traditional methods is effectively solved. The numerical calculation method of the embodiment of the present application significantly improves the accuracy and credibility of the results, and provides a more reliable and innovative solution for the numerical simulation of two-phase flow.

[0033] In numerical calculation, residual is one of the key indicators to measure whether the calculation has converged, and the judgment criteria for calculation termination usually include residual and iteration number. When the residual reaches the preset threshold or the number of iterations reaches the upper limit, the calculation will automatically end. In order to maximize the accuracy of flow field simulation, the residual convergence standard is set to 10 -20 The power and number of iterations are 2000 to ensure the reliability and accuracy of the calculation results.

[0034] The UDF function writing flow chart of the reflection boundary condition of the particle collision rebound model under the modified wet solid condition is as follows: Figure 7 As shown, the specific steps are: (1) Initialize variables, including the angle between the particle velocity and the wall normal vector , Reflection Angle , particle normal , particle critical velocity , normal restitution coefficient , tangential restitution coefficient ; (2) Calculate the normal vector and determine whether it is an axisymmetric rotation based on the value of rp_axi_swirl. rp_axi_swirl is a global variable in Fluent that is used to indicate whether the axisymmetric rotation flow model is enabled. If so, calculate the three-dimensional normal vector to avoid numerical instability. If not, use the two-dimensional normal vector directly. (3) Check the particle type to determine whether the particle is an inert particle. If so, continue to the next step of processing. If not, skip the particle processing. In the exemplary embodiment of the present application, the particle type is set to be inert, so the next step of processing can be directly performed. (4) Comparison of particle normal velocity and critical speed , calculate the normal velocity by dot-producting the particle velocity and the normal vector , use the empirical formula to calculate the critical velocity of the particle ; (5) If , then the particle velocity is judged to be 0, and the particle velocity is set to 0, which means that it is captured by the wall liquid film; like , then enter the wall reflection logic, first calculate the reflection angle, and then calculate the tangential restitution coefficient based on the reflection angle combined with the fitting coefficient and formula obtained from the experiment and normal restitution coefficient Finally, two recovery coefficients are applied to readjust the particle velocity and update the initial velocity of the particle to continue moving.

[0035] Affected by the liquid film, the rebound speed and angle of the particles colliding with the wall with the liquid film will change. At the same time, the existence of the liquid film is equivalent to adding a protective layer on the wall, which reduces the collision speed between the particles and the wall, thereby causing the particle motion trajectory to change.

[0036] Therefore, the fitting coefficients and formulas obtained from the above experiments are obtained through the particle-wall collision and rebound experiment. The normal component and tangential component of the particle velocity during collision are analyzed to obtain the tangential restitution coefficient: and normal restitution coefficient , and is used in subsequent numerical simulations to write the modified reflection boundary condition UDF function of the particle collision and rebound model under wet-solid conditions, so as to simulate the particle collision and rebound behavior more realistically.

[0037] The tangential restitution coefficient can be obtained by fitting the experimental data in Origin software. and normal restitution coefficient As the particle tilts the impact angle The functional relationship of the change is: (1) Tangential restitution coefficient (2) Normal restitution coefficient in, is the fitting coefficient, is the critical angle.

[0038] In an exemplary embodiment of the present application, the fitting coefficient after fitting the experimental data is: In the specific implementation of step S4, the simulation data is subjected to data extraction and then image processing to obtain a flow distribution characteristic map and a particle distribution characteristic map.

[0039] Specifically, the calculated simulation data is processed graphically. In order to better display the internal flow field distribution characteristic diagram, a characteristic section needs to be created for display. In FLUENT, select "Cloud Map" in the "Results" tab and click "New Surface" to create a suitable characteristic section. In the "Coloring Variables" tab, select "Velocity" and "VelocityMagnitude" in turn, and then click "Save / Show"; Similarly, create another cloud map about the internal pressure distribution on the created characteristic section, select "Pressure" and "Static Pressure" in turn in the "Coloring Variables" tab, and then click "Save / Show";

[0040] In the "Particle Trajectory" tab, select "Particle Variables" and "Particle Velocity Magnitude" in "Shading Variables" and then click "Track" and "Save / Show" to get the motion trajectory of the internal particles.

[0041] In order to better display the movement of particles in the valve or the distribution of particles captured by the wetted wall, the valve grid and the particle trajectory are displayed together in one picture, and the transparency of the valve grid is set appropriately, that is, check "Grid" and "Particle Velocity" in the "Scene" tab, and set the grid transparency to 60%, and finally obtain the particle distribution characteristic map.

[0042] In the specific implementation of step S5, the region where particle accumulation occurs is determined based on the flow distribution characteristic diagram and the particle distribution characteristic diagram.

[0043] Specifically, the flow distribution characteristic diagram and particle distribution characteristic diagram are used to visualize the flow field inside the valve, focusing on the interaction between particles and the wall liquid film under wet solid conditions, and locking the area where the particles are located where the speed is reduced to 0. By analyzing the particle mass concentration distribution and volume concentration distribution in these areas, the specific areas where particle accumulation occurs are marked.

[0044] In the specific implementation of step S6, the particle number density is extracted according to the particle accumulation occurrence area, and the particle number density analysis method is used to quantitatively analyze the distribution of high-concentration particles inside the valve under wet solid conditions.

[0045] Specifically, the particle number density is introduced as a characterization parameter. By calculating the equivalent number of particles in each grid unit and summing the probability scores of each particle in the flow field reaching the grid unit, the particle number density in the area where particle accumulation occurs is obtained; based on the particle number density results, the spatial distribution characteristics of the particles under wet solid conditions are further quantified, and the quantification criteria include the sum of the number of particles in each grid unit and the uniformity of their distribution among the grid units; based on the spatial distribution characteristics of the particles under wet solid conditions, by counting the equivalent number of particles in the grid unit and combining the probability distribution of particle arrival in each grid unit, the concentration gradient and accumulation characteristics of the particles in the spatial distribution are evaluated, and the distribution range and location of high-concentration particles are further confirmed. The high-concentration particles refer to particles in the accumulation area whose concentration is greater than the concentration of particles at the inlet. The particle number density is defined as the equivalent number of particles in a given grid (S×S). The grid unit arrangement to be adopted is as follows: Figure 8 As shown, the probability score calculation formula is as follows:

[0046] in, is the probability score of each particle falling on each grid, and are the coordinates of the particle, and are the coordinates of the center points of each grid, and For two adjacent grid center points Axis and The distance along the axis.

[0047] This method can intuitively quantify the distribution density of particles in different areas. Areas with high particle number density are often closely related to particle accumulation, and these areas are usually key areas that are prone to wear or blockage during valve operation. The analysis based on particle number density can provide a reference for flow field optimization under wet gas-solid conditions, and also provide a new idea for the study of particle distribution characteristics.

[0048] In the specific implementation of step S7, according to the result of the quantitative analysis, the particle capture rate parameter is extracted to further obtain the particle capture characteristics caused by the wall liquid film under the wet solid condition.

[0049] Specifically, the particle capture rate is defined as the probability fraction of particles being captured in the wall liquid film area. By calculating the difference in particle capture rates in different wetted wall areas, a particle capture distribution model is constructed to obtain the capture characteristics of particles inside the valve. The calculation formula for the particle capture rate is:

[0050] in, is the particle capture rate, is the number of particles captured by the wall, is the total number of particles involved in the calculation in the flow field.

[0051] Through numerical simulation and data extraction, the capture distribution characteristics of particles in different wetted wall areas are analyzed. In certain specific areas inside the valve, the wall liquid film will lead to a higher particle capture rate due to the flow characteristics or geometric shape. For these areas, the potential particle accumulation areas can be identified by the spatial distribution characteristics of the capture rate, thereby optimizing the inner cavity shape design of the valve and reducing the risk of particle deposition during operation.

[0052] It can be seen from the above embodiments that the embodiments of the present application adopt three-dimensional model construction, grid division and modified particle collision rebound model, and combine the particle motion characteristics under wet solid conditions to the tangential restitution coefficient and normal restitution coefficient The corrections were made to overcome the technical problem that the traditional dry wall model could not accurately reflect the impact of wet solid conditions on particle collision rebound and accumulation behavior, thereby improving the accuracy of particle distribution prediction under wet solid conditions. By introducing the particle number density quantitative analysis method, the problem of insufficient analysis accuracy of particle accumulation area and capture rate in the existing technology was solved, thereby achieving accurate identification and quantitative analysis of particle accumulation areas. Finally, by extracting the particle capture rate parameters, the influence characteristics of the wet wall on particle distribution were further obtained, thereby providing a more accurate technical basis for valve design optimization.

[0053] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0054] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for predicting the particle distribution characteristics inside a valve under wet solid conditions, characterized in that: include: S1: Establish a three-dimensional model of the valve; S2: Meshing the three-dimensional model of the valve; S3: The three-dimensional valve model after meshing is combined with the particle collision and rebound characteristics under wet solid conditions, the tangential restitution coefficient and the normal restitution coefficient in the particle collision and rebound model are corrected, and numerical simulation is carried out on the corrected particle collision and rebound model to obtain simulation data; S4: extracting data from the simulation data and then performing image processing to obtain a flow distribution characteristic map and a particle distribution characteristic map; S5: judging the particle accumulation occurrence area according to the flow distribution characteristic diagram and the particle distribution characteristic diagram; S6: extracting the particle number density according to the particle accumulation occurrence area, and using a particle number density analysis method to quantitatively analyze the distribution of high-concentration particles inside the valve under wet solid conditions; S7: extracting a particle capture rate parameter according to the result of the quantitative analysis, and further obtaining the particle capture characteristics caused by the wall liquid film under wet solid conditions; The tangential restitution coefficient The expression is as follows: ； The normal restitution coefficient The expression is as follows: ； in, is the fitting coefficient, is the critical angle, is the particle tilt impact angle.

2. The method according to claim 1, characterized in that: Meshing the three-dimensional model of the valve includes: The three-dimensional model of the valve is imported into Ansys SpaceClaim software for model preprocessing, and then imported into FLUENT MESHING software for meshing. The number of meshes is set and local mesh encryption is performed on the valve cavity area inside the valve.

3. The method according to claim 1, characterized in that The three-dimensional valve model after meshing is combined with the particle collision and rebound characteristics under wet solid conditions to calculate the tangential recovery coefficient in the particle collision and rebound model. and normal restitution coefficient The modified particle collision and rebound model is modified and numerical simulation is carried out to obtain simulation data, including: (1) Import the meshed 3D valve model into FLUENT software, and set a unified mesh unit in the "Mesh Scaling" tab; establish the gas flow field, set "Steady State" and "Gravity Acceleration" in the "General" tab; turn on "Energy" and "Viscosity" in the "Model" tab, and set the turbulence model and wall function; set the single-phase gas to "Air" in the "Material" tab; set the fluid domain material to "Air" in the "Unit Region Conditions" tab; define the boundary conditions of "Outlet" and "Inlet" in the "Boundary Conditions" tab; set the calculation method and control method in the "Solution" tab; set the convergence residual value in the "Calculation Monitoring" tab; set the initialization method to "Standard Initialization" in the "Initialization" tab, and click the "Initialize" button to complete the initialization settings; set the number of iterations and time step in the "Calculation Settings" tab, and click "Start Calculation"; (2) Through the particle-wall collision and rebound experiment, the normal component and tangential component of the particle velocity during collision are analyzed to obtain the tangential restitution coefficient and normal restitution coefficient , and is used to correct the tangential restitution coefficient and normal restitution coefficient of the particle collision rebound model under wet solid conditions; (3) After the above calculations are completed, continue to establish the particle flow field. Set "Transient" and "Gravity Acceleration" in the "General" tab; open "Discrete Phase" in the "Model" tab, check "Interaction with Continuous Phase", and create a "Jet Source". Select "Jet Source Type" as "file", where "file" is the user-defined particle package file imported externally; load the modified reflection boundary condition UDF function of the particle collision rebound model under wet solid conditions in the "User Defined" tab, and set the DPM-related parameters of the wall in the "Boundary Conditions" tab to the loaded UDF function; set the number of iterations and time step in the "Run Calculation" tab, and click "Start Calculation"; finally, obtain the simulation data of the CASE file and DATE file.

4. The method according to claim 3, characterized in that: The simulation data is subjected to data extraction and image processing to obtain a flow distribution characteristic diagram and a particle distribution characteristic diagram, including: Select "Cloud Plot" in the "Results" tab in the FLUENT software to draw the flow distribution characteristic diagram on the characteristic section inside the valve, which includes the gas velocity cloud map and the gas pressure cloud map. Draw the particle distribution characteristic diagram on the wetted wall in the "Particle Trajectory" tab.

5. The method according to claim 1, characterized in that: According to the flow distribution characteristic diagram and the particle distribution characteristic diagram, determining the particle accumulation occurrence area includes: Through the flow distribution characteristic diagram and the particle distribution characteristic diagram, the position area of ​​the particles with a velocity of 0 after being captured by the wall liquid film inside the valve is observed, the particle position is analyzed and marked, the number and density of particles are analyzed through flow field numerical comparison, and the area where particles accumulate under wet-solid conditions is determined.

6. The method according to claim 5, characterized in that: According to the particle accumulation occurrence area, the particle number density is extracted, and the particle number density analysis method is used to quantitatively analyze the high-concentration particle distribution inside the valve under wet solid conditions, including: S61: Introducing particle number density as a characterization parameter, by calculating the equivalent number of particles in each grid unit and summing the probability fractions of each particle in the flow field reaching the grid unit, the particle number density in the area where particle accumulation occurs is obtained; S62: further quantifying the spatial distribution characteristics of the particles under wet solid conditions according to the particle number density result, wherein the quantification criteria include the sum of the number of particles in each grid unit and the uniformity of their distribution among the grid units; S63: Based on the spatial distribution characteristics of particles under wet solid conditions, by counting the equivalent number of particles in the grid cells and combining the probability distribution of particle arrival in each grid cell, the concentration gradient and accumulation characteristics of the particles in spatial distribution are evaluated, and the distribution range and position of high-concentration particles are further confirmed. The high-concentration particles refer to particles whose concentration in the accumulation area is greater than that at the inlet.

7. The method according to claim 6, characterized in that: According to the results of the quantitative analysis, the particle capture rate parameters are extracted, and the particle capture characteristics caused by the wall liquid film under wet solid conditions are further obtained, including: According to the high-concentration particle distribution results of the quantitative analysis, the distribution of particles on the wetted wall surface is further analyzed, and the particle capture rate is defined as the capture probability fraction of particles in the wall liquid film area. By calculating the difference in capture rate of particles in different wetted wall areas, the capture characteristics of particles inside the valve are obtained, thereby realizing the prediction of particle distribution characteristics inside the valve under wet solid conditions.

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