Method for predicting distribution characteristics of particles in valve under wet solid condition

Abstract

The present application relates to the technical field of numerical simulation, and discloses a method for predicting the distribution characteristics of particles in a valve under wet gas-solid conditions. The method comprises establishing a three-dimensional model of the valve, dividing the model into grids, correcting the tangential and normal restitution coefficients in combination with the particle collision and rebound characteristics under wet gas-solid conditions, carrying out numerical simulation using the corrected collision and rebound model, and obtaining simulation data. Through data extraction and image processing, the flow distribution characteristic map and the particle distribution characteristic map inside the valve are generated, the particle accumulation area is determined according to the characteristic maps, the particle number density is extracted, and the high-concentration particle distribution inside the valve is quantitatively analyzed. Based on the quantitative analysis results, the particle capture rate parameter is extracted, and the particle capture characteristics caused by the wall liquid film under wet gas-solid conditions are obtained. The present method can effectively predict the particle distribution and accumulation characteristics inside the valve, and provide a basis for valve design and optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of numerical simulation, and particularly relates to a method for predicting particle distribution characteristics in a valve under wet gas-solid conditions. BACKGROUND

[0002] Valves are used for regulating and controlling medium flow in industrial production and are widely used in chemical, petroleum and power fields. With the development of industrial technology, the application scenarios of gas-solid two-phase flow are increasing, for example, when industrial gas containing solid particles is transported at high temperature and high pressure, the particles may accumulate or aggregate due to wall wetting, affecting the stability of fluid flow and the performance of the valve.

[0003] At present, the research on two-phase flow under wet gas-solid conditions is limited. Existing researches mainly aim at dry environments, and related models cannot accurately describe the influence of liquid film on particle collision and aggregation behavior, resulting in insufficient prediction accuracy of particle distribution characteristics. In addition, the existing numerical simulation methods have low applicability under wet gas-solid conditions, which cannot meet the demand of valve design and maintenance for prediction of particle distribution characteristics.

[0004] Therefore, research on particle distribution characteristics under wet gas-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

[0005] The purpose of the embodiments of the present application is to provide a method for predicting particle distribution characteristics in a valve under wet gas-solid conditions, so as to solve the problem that the existing technology cannot accurately predict particle collision rebound and aggregation behavior under wet gas-solid conditions, especially the prediction accuracy of particle aggregation area and capture rate under the influence of wall liquid film. The method effectively makes up for the above shortcomings and provides a reliable basis for the optimization design of the valve.

[0006] According to the embodiments of the present application, a method for predicting particle distribution characteristics in a valve under wet gas-solid conditions is provided, comprising:

[0007] S1: establishing a three-dimensional model of the valve;

[0008] S2: performing mesh division on the three-dimensional model of the valve;

[0009] S3: combining the three-dimensional model of the valve after mesh division with the particle collision rebound characteristics under wet gas-solid conditions, correcting the tangential restitution coefficient and normal restitution coefficient in the particle collision rebound model, performing numerical simulation on the corrected particle collision rebound model, and obtaining simulation data;

[0010] S4: after data extraction on the simulation data, image processing is performed to obtain a flow distribution characteristic map and a particle distribution characteristic map;

[0011] S5: determining a particle accumulation occurrence region according to the flow distribution feature map and the particle distribution feature map;

[0012] S6: extracting a particle number density according to the particle accumulation occurrence region, and performing quantitative analysis on the high-concentration particle distribution in the valve under the wet gas-solid condition by using a particle number density analysis method;

[0013] S7: extracting a particle capture rate parameter according to the result of the quantitative analysis, and further obtaining a particle capture feature caused by the wall surface liquid film under the wet gas-solid condition;

[0014] The expression of the tangential restitution coefficient is as follows:

[0015] ;

[0016] The expression of the normal restitution coefficient is as follows:

[0017] ;

[0018] wherein, is a fitting coefficient, is a critical angle, is a particle oblique impact angle.

[0019] The technical scheme provided by the embodiment of the present application can include the following beneficial effects:

[0020] As can be seen from the above embodiment, the embodiment of the present application adopts a three-dimensional model construction, a mesh division, and a particle collision rebound model with correction, and combines the particle motion characteristics under the wet gas-solid condition to correct the tangential restitution coefficient and the normal restitution coefficient, thereby overcoming the technical problem that the model under the traditional dry wall surface cannot accurately reflect the influence of the wet gas-solid condition on the particle collision rebound and accumulation behavior, and further improving the accuracy of the particle distribution prediction under the wet gas-solid condition. By introducing the particle number density quantitative analysis method, the problem of insufficient analysis accuracy of the particle accumulation region and the capture rate in the prior art is solved, and the accurate identification and quantitative analysis of the particle accumulation region are realized. Finally, by extracting the particle capture rate parameter, the influence feature of the wet wall surface on the particle distribution is further obtained, thereby providing a more accurate technical basis for the valve design optimization.

[0021] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings incorporated in the specification and constituting a part hereof illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the present application.

[0023] Figure 1 is a flow chart of a method for predicting the distribution of particles inside a valve under wet solid conditions according to an example embodiment.

[0024] Figure 2 is a three-dimensional model of a ball valve according to an example embodiment.

[0025] Figure 3 is a flow chart of a meshing process for a ball valve according to an example embodiment.

[0026] Figure 4 is a diagram of a computational domain for the internal flow passage of a ball valve according to an example embodiment.

[0027] Figure 5 is a diagram of local mesh refinement for a three-dimensional model of a ball valve according to an example embodiment.

[0028] Figure 6 is a diagram of particle-wall collision and reflection according to an example embodiment.

[0029] Figure 7 is a flow chart of a UDF file for boundary conditions of a particle collision and reflection model under wet conditions according to an example embodiment.

[0030] Figure 8 is a grid cell arrangement for particle density solving according to an example embodiment. DETAILED DESCRIPTION

[0031] The example embodiments will be described in detail herein with reference to the attached drawings. The description of the example embodiments is intended to apply to any example embodiment, unless specifically noted otherwise. It is noted that the description is not meant to limit the application to the specific example embodiments described. It is also noted that the description is not meant to limit the application to the specific embodiments described.

[0032] The terminology used in the present application is for the purpose of describing particular example embodiments only and is not intended to be limiting of the present application. As used in this application, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0033] Figure 1 is a flow chart of a method for predicting the distribution of particles inside a valve under wet solid conditions according to an example embodiment, as shown in Figure 1 the method includes the following steps:

[0034] In the specific implementation of step S1, a three-dimensional model of the valve is established;

[0035] 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 in the 3D modeling software SOLIDWORKS. Figure 2 As 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 to STEP format to facilitate subsequent model import into Ansys SpaceClaim software for model pre-processing.

[0036] In the specific implementation of step S2, the three-dimensional model of the valve is meshed;

[0037] Specifically, the 3D model of the valve was imported into Ansys SpaceClaim software for model preprocessing, and then meshed in FLUENT MESHING software. The number of meshes was set, and local mesh encryption was performed on the valve cavity area inside the valve to ensure high-precision meshes in the fluid-particle interaction area, so as to more accurately reflect the flow characteristics.

[0038] The flow chart of grid division is as follows Figure 3 As shown, it includes importing models and preprocessing, defining grid areas, generating grids, checking grid quality, and flow coefficients. , refined mesh, discharge coefficient , compare flow coefficients, compare minimum grid sizes and particle diameter , the next step is numerical solution.

[0039] During model import and preprocessing, in order to reduce the amount of subsequent meshing calculations and improve mesh accuracy, the valve 3D model was simplified in Ansys SpaceClaim software, retaining only parts related to the flow path, deleting irrelevant parts such as brackets, filling holes, gaps unrelated to the flow path, deleting chamfers and fillets, and filling concave and convex areas. 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.

[0040] 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 "Prepare" tab to extract the fluid domain inside the valve and name it "fluid". Finally, select "Convert to FLUENTMESHING" software in the "Workbench" tab.

[0041] In the generation of the grid, the workflow of "Watertight Geometry" in the "FLUENT MESHING" software is selected. After importing the geometric model, the local size is added to the named valve inner surface to be meshed, the local grid is encrypted, then the surface grid is generated, the "geometric model is only composed of fluid area without gap" is checked when describing the geometric structure, and the boundary condition is updated to pressure outlet and pressure inlet, the boundary layer is added, and finally the polyhedral grid "poly-hexcore" is selected to generate the body grid, as shown in the dashed box in Figure 4 The schematic diagram of the calculation domain of the internal flow passage of the ball valve, Figure 5 The schematic diagram of the local grid encryption of the valve.

[0042] In the grid quality inspection, click "Perform Grid Check" in the "Grid" tab. The grid quality parameters can be seen on the lower console. Focus on observing whether there is negative volume and orthogonal quality. If there is negative volume or orthogonal quality is lower than 0.5, it needs to be returned to the "model import and preprocessing" step to modify again.

[0043] After completing the grid quality inspection, the flow coefficient is taken as the target variable to start the grid independence verification. Specifically, first, the initial grid is used for numerical solution to obtain the flow coefficient . Then, the grid size is adjusted to refine the number of grids, and the numerical solution is performed again to obtain the flow coefficient . Compare the error of the flow coefficients of the two times. If the error exceeds 5%, continue to refine the grid and solve again, and gradually optimize 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 the particle diameter . If , the current grid division passes the independence verification and can be used for subsequent numerical solution; if , return to the "grid generation" step to adjust the grid density to ensure the accuracy of the grid independence and the particle distribution characteristics.

[0044] The grid quality of the exemplary embodiments in the present disclosure finally all reaches above 0.7, meeting the requirements of numerical simulation calculation, and the next step of solving can be performed.

[0045] In the specific implementation of step S3, the three-dimensional model of the valve after grid division is combined with the particle collision and rebound characteristics under the wet gas solid condition, the tangential restitution coefficient and the normal restitution coefficient The modified particle collision and rebound model is simulated to obtain simulation data.

[0046] Specifically, when directly calculating the gas-solid two-phase flow, it is often difficult to achieve stable convergence of the calculation or obtain ideal calculation accuracy due to the strong coupling between the particles and the gas in the flow field and the complexity of the particle motion. Therefore, in order to improve the calculation efficiency and the accuracy of the results, two steps are needed: first, a stable gas flow field is established through numerical simulation to ensure that the basic characteristics of the gas flow reach a stable state; then, the particles are introduced, and the trajectory, distribution characteristics of the particles in the gas flow field and the interaction with the wall are further calculated.

[0047] More specifically, first, the grid-divided three-dimensional model of the valve is imported into the FLUENT software, and a uniform grid unit is set in the "Grid Scaling" tab; a single-phase gas flow field is established, and "steady" and "gravity acceleration" are set in the "General" tab; "energy" and "viscosity" are opened in the "Model" tab, and SST turbulent flow model and wall function are set ; in the "Material" tab, the single-phase gas is set as "air"; in the "Cell Zone Conditions" tab, the fluid domain material is set as "air"; in the "Boundary Conditions" tab, the boundary conditions of "outlet" and "inlet" are both set as pressure; in the "Solve" tab, the calculation method is set as Coupled and the control method is set as default; in the "Calculation Monitor" tab, the convergence residual value is set; in the "Initialization" tab, the initialization method is set as "standard initialization", and the initialization setting is completed by clicking the "Initialization" button; in the "Calculation Settings" tab, the iteration number and time step are set, and the "Start Calculation" button is clicked.

[0048] Secondly, through the particle collision and rebound experiment with the liquid film on the wall, the normal component and tangential component of the particle velocity when colliding with the wall are analyzed, as shown in Figure 6 The particle collision and rebound with the wall are shown in the schematic diagram, and the tangential restitution coefficient and the normal restitution coefficient are obtained, which are used to modify the tangential restitution coefficient and the normal restitution coefficient of the particle collision and rebound model under the wet gas-solid condition;

[0049] Finally, after the calculation is completed and the 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 "Injection source", select "Particle type" as "Inert", select "Injection 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 containing the particle collision and rebound model under the modified wet gas-solid condition, and set the "Discrete phase boundary type" in the "Boundary conditions" tab to "user-defined" in the DPM of all wall surfaces, 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, the data of the CASE file and the DATE file are obtained.

[0050] By constructing the gas flow field in advance before particle calculation, the problem of difficulty in convergence and large error in direct calculation of two-phase flow in traditional methods is effectively solved. The numerical calculation method of the embodiment of the application significantly improves the accuracy and reliability of the results, and provides a more reliable and innovative solution for numerical simulation of two-phase flow.

[0051] In numerical calculation, residual error is one of the key indicators for measuring whether the calculation converges, and the judgment condition for terminating the calculation usually includes residual error and iteration step number. When the residual error reaches the preset threshold or the iteration number reaches the upper limit, the calculation will automatically end. In order to improve the accuracy of flow field simulation as much as possible, the residual convergence standard is set to 10 -20 times and the iteration number is 2000 in this case, so as to ensure the reliability and accuracy of the calculation results.

[0052] The reflection boundary condition UDF function containing the particle collision and rebound model under the modified wet gas-solid condition is shown in the flow chart as Figure 7 , and the specific steps are:

[0053] (1) Initialize variables, including the angle between particle velocity and wall normal vector , reflection angle , particle normal , particle critical velocity , normal restitution coefficient , and tangential restitution coefficient .

[0054] (2) Calculate the normal vector, and determine whether it is an axisymmetric rotation case according to the value of rp_axi_swirl, which is a global variable in Fluent, used to identify whether the axisymmetric rotational flow model is enabled. If yes, calculate the three-dimensional normal vector to avoid numerical instability. If not, directly use the two-dimensional normal vector;

[0055] (3) Check the particle type, and determine whether the particle is an inert particle. If yes, continue to the next step. If not, skip the particle processing. In the exemplary embodiments of the present application, the particle type has been set to inert, so the next step can be directly processed;

[0056] (4) Compare the particle normal velocity with the critical velocity , calculate the normal velocity by dot product of particle velocity and normal vector, and calculate the critical velocity of the particle using an empirical formula;

[0057] (5) If , the particle velocity is determined to be 0, and the particle velocity is set to 0, meaning that it is captured by the wall liquid film;

[0058] If , enter the wall reflection logic. First, calculate the reflection angle, and then calculate the tangential recovery coefficient and the normal recovery coefficient according to the size of the reflection angle, the fitting coefficients obtained from experiments, and the formula. Finally, apply the two recovery coefficients to re-adjust the particle velocity and update the initial particle velocity to continue moving.

[0059] Affected by the liquid film, the particle collision and rebound velocity and angle with the wall with liquid film will change. At the same time, the existence of the liquid film is equivalent to adding a protective layer on the wall, reducing the particle collision velocity with the wall, and further causing the change of the particle motion trajectory.

[0060] Therefore, the fitting coefficients and formula obtained from the above experiments are obtained through the particle collision and rebound experiments with the wall with liquid film. By analyzing the normal component and tangential component of the particle collision velocity, the tangential recovery coefficient and the normal recovery coefficient are obtained, and are used to write the reflection boundary condition UDF function of the modified particle collision and rebound model under the wet gas-solid condition in subsequent numerical simulation, to more realistically simulate the particle collision and rebound behavior.

[0061] Through the obtained experimental data, the tangential recovery coefficient and the normal recovery coefficient can be fitted in Origin software, and the tangential recovery coefficient and the normal recovery coefficient change with the particle inclined impact angle The functional relationship of the change is:

[0062] (1) Tangential recovery coefficient

[0063]

[0064] (2) Normal recovery coefficient

[0065]

[0066] wherein, is a fitting coefficient, is a critical angle.

[0067] In the exemplary embodiments of the present application, the fitting coefficient after fitting by experimental data is:

[0068]

[0069] In the specific implementation of step S4, after data extraction on the simulation data and image processing, the flow distribution feature map and the particle distribution feature map are obtained.

[0070] Specifically, the simulation data after calculation is processed by graphics, and a feature section is created to show the internal flow field distribution feature map for better display. In the "Results" tab in FLUENT, select "Cloud" and click "New Surface" to create a suitable feature section, and then select "Velocity" and "VelocityMagnitude" in the "Color Variable" tab, and then click "Save / Display". Similarly, create a cloud map about the internal pressure distribution on the created feature section, and then select "Pressure" and "Static Pressure" in the "Color Variable" tab, and then click "Save / Display".

[0071] In the "Particle Trajectory" tab, select "Particle Variables" and "Particle Velocity Magnitude" in the "Color Variable" tab, and then click "Track" and "Save / Display", so as to obtain the internal particle motion trajectory map.

[0072] In order to better display the distribution of the motion of the particles in the valve or the capture of the wet wall, the valve grid and the particle trajectory are displayed in a figure together, and the transparency of the valve grid is appropriately set, that is, in the "Scene" tab, check "Grid" and "Particle Velocity", and set the grid transparency to 60%, and finally obtain the particle distribution feature map.

[0073] In the implementation of step S5, the particle accumulation occurrence region is determined according to the flow distribution feature map and the particle distribution feature map.

[0074] Specifically, the flow field inside the valve is visually displayed by using the flow distribution feature map and the particle distribution feature map, the interaction between the particles and the wall liquid film under the wet gas-solid condition is observed, and the region where the particle velocity is reduced to 0 is locked. By analyzing the particle mass concentration distribution and the volume concentration distribution in these regions, the specific region where the particle accumulation occurs is marked.

[0075] In the implementation of step S6, the particle number density is extracted according to the particle accumulation occurrence region, and the particle number density analysis method is used to quantitatively analyze the high-concentration particle distribution inside the valve under the wet gas-solid condition.

[0076] Specifically, the particle number density is introduced as a characterization parameter, the equivalent particle number in each grid cell is calculated, the particle number density in the particle accumulation occurrence region is obtained by summing the probability fractions of each particle reaching the grid cell in the flow field, and the spatial distribution characteristics of the particles under the wet gas-solid condition are further quantified according to the particle number density result. The quantification standard includes the total number of particles in each grid cell and the uniformity of the distribution among the grid cells. According to the spatial distribution characteristics of the particles under the wet gas-solid condition, the concentration gradient and the accumulation characteristics of the particles in the spatial distribution are evaluated by counting the equivalent number of particles in the grid cells and combining the probability distribution of the particles reaching the grid cells, so as to further confirm the distribution range and position of the high-concentration particles. The high-concentration particles refer to the particles whose concentration in the accumulation region is greater than the concentration of the particles at the inlet. The particle number density is defined as the equivalent particle number in a given grid (SxS), and the grid cell arrangement mode to be used is as shown in FIG. 1. Figure 8 The probability fraction calculation formula is as follows:

[0077]

[0078] wherein, is the probability fraction of each particle falling on each grid, and is the coordinate of the particle, and is the coordinate of the center point of each grid, and is the distance between the center points of two adjacent grids in the x-axis and y-axis directions.

[0079] ​​By this method, the distribution density of particles in different areas can be quantified intuitively. The areas with high particle number density are often closely related to particle accumulation phenomena, and these areas are usually the key positions prone to wear or blockage during valve operation. Based on the analysis of particle number density, a reference basis can be provided for flow field optimization under wet gas-solid conditions, and a new idea is also provided for the research of particle distribution characteristics.

[0080] In the implementation of step S7, according to the results of the quantitative analysis, the particle capture rate parameter is extracted, and the particle capture characteristics caused by the wall liquid film under the wet gas-solid condition are further obtained.

[0081] Specifically, the particle capture rate is defined as the fraction of the capture probability of particles in the wall liquid film area, and by calculating the difference of the capture rate of particles in different wet wall areas, a distribution model of particle capture is constructed to obtain the capture characteristics of particles inside the valve. The calculation formula of the particle capture rate is:

[0082]

[0083] wherein, is the particle capture rate, is the number of particles captured by the wall, is the total number of particles participating in the calculation in the flow field.

[0084] Through numerical simulation and data extraction, the capture distribution characteristics of particles in different wet wall areas are analyzed. In some specific areas inside the valve, the wall liquid film will lead to a higher particle capture rate due to the influence of flow characteristics or geometric shape. For these areas, the potential particle accumulation area can be identified through the spatial distribution characteristics of the capture rate, so as to optimize the shape design of the inner cavity of the valve and reduce the risk of particle deposition during operation.

[0085] As can be seen from the above embodiments, the embodiments of the present application adopt a three-dimensional model construction, grid division and a modified particle collision and rebound model, and combine the tangential restitution coefficient and the normal restitution coefficient are modified based on the particle motion characteristics under the wet gas-solid condition, which overcomes the technical problem that the model under the traditional dry wall surface cannot accurately reflect the influence of the wet gas-solid condition on the particle collision and rebound and accumulation behavior, and thus improves the accuracy of the prediction of particle distribution under the wet gas-solid condition. By introducing the particle number density quantitative analysis method, the problem of insufficient accuracy of particle accumulation area and capture rate analysis in the prior art is solved, and thus accurate identification and quantitative analysis of the particle accumulation area are realized. Finally, by extracting the particle capture rate parameter, the influence characteristics of the wet wall on the particle distribution are further obtained, and thus a more accurate technical basis is provided for the optimization of valve design.

[0086] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the application embrace any and all variations of the present application that fall within the scope of the general inventive concept as defined by the appended claims and their equivalents. The specification and examples are to be regarded as exemplary in nature and not as restrictive in any way.

[0087] It should be understood that the application is not limited to the precise construction that has been described above and shown in the accompanying drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is to be defined by the appended claims rather than by the description preceding them.

Claims

1. A method for predicting the internal particle distribution characteristics of a valve under wet solid conditions, characterized by, The method comprises the following steps: S1: establishing a three-dimensional model of the valve; S2: meshing the three-dimensional model of the valve; S3: combining the meshed three-dimensional model of the valve with the particle collision and rebound characteristics under the wet gas-solid condition, correcting the tangential and normal restitution coefficients in the particle collision and rebound model, carrying out numerical simulation on the corrected particle collision and rebound model, and obtaining simulation data; S4: extracting data from the simulation data and then carrying out image processing to obtain flow distribution feature maps and particle distribution feature maps; S5: judging the particle accumulation occurrence area according to the flow distribution feature maps and the particle distribution feature maps; S6: extracting the particle number density according to the particle accumulation occurrence area, and quantitatively analyzing the high-concentration particle distribution inside the valve under the wet gas-solid condition by using the particle number density analysis method; S7: extracting the particle capture rate parameter according to the result of the quantitative analysis, and further obtaining the particle capture characteristics caused by the wall film under the wet gas-solid condition. The tangential restitution coefficient The expression of the tangential restitution coefficient is as follows: ； The normal restitution coefficient The expression of the normal restitution coefficient is as follows: ； wherein, is a fitting coefficient, is a critical angle, is a particle oblique impact angle.

2. The method of claim 1, wherein, The meshing of the three-dimensional model of the valve comprises the following steps: The three-dimensional model of the valve is imported into the Ansys SpaceClaim software for model preprocessing, and then is imported into the FLUENT MESHING software for meshing, the number of meshes is set, and local mesh encryption processing is carried out for the valve cavity area inside the valve.

3. The method of claim 1, wherein, The three-dimensional model of the valve after meshing is combined with the particle collision and rebound characteristics under the condition of moisture and solid to correct the tangential restitution coefficient and the normal restitution coefficient in the particle collision and rebound model Numerical simulation is carried out on the corrected particle collision and rebound model, and simulation data are obtained, including:​ (1) The meshed three-dimensional model of the valve is imported into the FLUENT software, and the uniform mesh unit is set in the "Mesh Scaling" tab; the gas flow field is established, and the "steady" and "gravity acceleration" are set in the "General" tab; the "energy" and "viscosity" are opened in the "Model" tab, and the turbulence model and wall function are set; the single-phase gas is set as "air" in the "Material" tab; the fluid domain material is set as "air" in the "Cell Zone Conditions" tab; the boundary conditions of "outlet" and "inlet" are defined in the "Boundary Conditions" tab; the calculation method and control method are set in the "Solve" tab; the convergence residual value is set in the "Calculation Monitor" tab; the initialization method is set as "standard initialization" in the "Initialization" tab, and the initialization setting is completed by clicking the "Initialization" button; the iteration number and time step are set in the "Calculation Settings" tab, and the "Start Calculation" is clicked; (2) Through the particle and liquid film wall collision rebound experiment, and analyze the normal component and tangential component of the velocity of the particle collision, get the tangential restitution coefficient and normal restitution coefficient , and used to correct the tangential restitution coefficient and normal restitution coefficient of the particle collision rebound model under the condition of wet gas solid. (3) After the above calculation is completed, the particle flow field is further established, the "transient" and "gravity acceleration" are set in the "General" tab; the "discrete phase" is opened in the "Model" tab, the "interaction with the continuous phase" is checked, and the "ejection source" is created; the "ejection source type" is selected as "file", wherein the "file" is an externally imported user-defined particle package file; the reflection boundary condition UDF function of the corrected particle collision and rebound model under the wet gas-solid condition is loaded in the "User-Defined" tab, and the DPM related parameters of the wall in the "Boundary Conditions" tab are set as the loaded UDF function; the iteration number and time step are set in the "Run Calculation" tab, and the "Start Calculation" is clicked; finally, the simulation data of the CASE file and the DATE file are obtained.

4. The method of claim 3, wherein, The flow distribution feature map and the particle distribution feature map are obtained after data extraction and image processing on the simulation data, including: In the "Results" tab of the FLUENT software, "cloud map" is selected to draw the flow distribution feature map on the characteristic cross section of the valve, which includes the gas velocity cloud map and the gas pressure cloud map. In the "Particle Trajectory" tab, the particle distribution feature map on the wet wall surface is drawn.

5. The method of claim 1, wherein, According to the flow distribution feature map and the particle distribution feature map, the particle accumulation occurrence area is determined, including: Through the display of the flow distribution feature map and the particle distribution feature map, the position area of the particles with a speed of 0 captured by the liquid film on the wall inside the valve is observed, the particle position is analyzed and marked, the particle number and the concentration degree are compared and analyzed through the flow field numerical analysis, and the particle accumulation area under the wet gas-solid condition is determined.

6. The method of claim 5, wherein, 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 the wet gas-solid condition, including: S61: Introducing particle number density as a characterization parameter, calculating the equivalent particle number in each grid element, summing the probability fraction of each particle in the flow field reaching the grid element, and obtaining the particle number density of the particle accumulation occurrence area; S62: According to the particle number density result, further quantifying the spatial distribution characteristics of particles under the wet gas-solid condition, and the quantification standards include the total number of particles in each grid element and the uniformity of the distribution among grid elements; S63: According to the spatial distribution characteristics of particles under the wet gas-solid condition, by statistically analyzing the equivalent number of particles in the grid element, combining the probability distribution of particles reaching each grid element, evaluating the concentration gradient and accumulation characteristics of particles in spatial distribution, further confirming the distribution range and position of high-concentration particles, and the high-concentration particles refer to the concentration of particles in the accumulation area being greater than the concentration of particles at the inlet.

7. The method of claim 6, wherein, According to the results of the quantitative analysis, the particle capture rate parameter is extracted, and the particle capture characteristics caused by the wall liquid film under the wet gas-solid condition are further obtained, including: According to the high-concentration particle distribution result of the quantitative analysis, the distribution of particles on the wet wall surface is further analyzed, the particle capture rate is defined as the capture probability fraction of particles in the wall liquid film area, the capture characteristics of particles inside the valve are obtained by calculating the difference of the capture rate of particles in different wet wall surface areas, and the prediction of the particle distribution characteristics inside the valve under the wet gas-solid condition is realized.

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