High-efficiency optimization design method of cyclone desander based on Ansys Workbench

Abstract

The invention discloses an efficient optimization design method for a cyclone desander based on Ansys Workbench. The method can build a unified process based on the Ansys Workbench work platform with a fluid simulation module and an optimization design module. In the fluid simulation module, various structural parameters, operating parameters and physical property parameters are established. In the optimization design module, the structural parameters, operating parameters and physical property parameters are used as control variables, and the performance parameters of the cyclone desander are used as target variables. A multi-objective rapid optimization design method is established by effectively combining experimental design and response surface analysis. In the optimization design process of the cyclone desander, experimental samples containing numerical values ​​of input parameters and output parameters are automatically explored, multi-parameter optimization is carried out in combination with response surface analysis, and reverse substitution verification is used to form an optimization design scheme for the cyclone desander, which effectively drives product research and development, and is convenient to implement as a whole, efficient in operation, and reliable in precision.

Description

Technical Field

[0001] The present invention relates to the technical field of design and manufacturing of a solid-liquid separation cyclone separator, and more specifically, to a highly efficient optimization design method for a cyclone desander based on Ansys Workbench. Background Art

[0002] Cyclone separator is a device that uses the principle of centrifugal sedimentation to separate incompatible mixtures with density differences. It has many advantages such as simple structure, convenient operation, convenient maintenance, large production capacity, high separation efficiency, and small footprint. It is suitable for many fields such as gas-liquid separation, solid-liquid separation, and simultaneous separation of gas, liquid, and solid. As a solid-liquid separation device, cyclone desander is now widely used in industries such as petroleum, mining, metallurgy, coal, and agricultural irrigation. Its performance will have an important impact on the economic benefits and product quality of related industries.

[0003] Although there are only three performance evaluation indicators for cyclone desander, namely separation efficiency, classification efficiency and pressure drop, they are affected by structural parameters, operating parameters and physical parameters at the same time. Among them, structural parameters include column diameter, column height, feed port diameter, overflow pipe diameter, overflow pipe insertion depth, discharge port diameter, cone angle, etc.; operating parameters include inflow velocity or working pressure; physical parameters include particle concentration, particle density, particle size and its distribution.

[0004] Due to too many factors affecting performance, it is difficult for domestic and foreign manufacturers to conduct multi-parameter coordinated design of cyclone desanders and carry out detailed model planning. In practical applications, the cyclone desander mainly completes the preliminary design of structural parameters based on empirical dimensions, and completes the selection of existing products based on production capacity and classification particle size. However, the designed products have single structural parameters and cannot adapt to changes in the properties of the separation medium and operating conditions. Therefore, it is difficult to achieve optimal performance under specific working conditions. There are usually disadvantages such as low separation efficiency, poor classification accuracy, and high energy consumption. Therefore, it is of great significance to complete the efficient optimization design of cyclone desanders by conducting research on design and selection methods.

[0005] The optimization design methods of cyclone desander are currently divided into two categories: experiments and numerical simulations. The experimental methods include single-factor experiments and experimental design methods. The single-factor experimental method can directly establish the influence of various factors and select key parameters by conducting experiments to quantitatively analyze the influence of various parameters on the performance of cyclone desander. However, the experimental volume is huge and the coupling influence between factors is ignored. The experimental design method compiles an accurate experimental plan according to the number of parameters and the value range, completes statistical analysis through experiments, and then realizes parameter optimization. Obviously, this method is also restricted by real experiments. The number of variable parameters and experimental samples are limited, and only partial parameter optimization can be achieved. The numerical simulation method simulates the fluid dynamics of the cyclone desander to obtain the influence of various parameters on the internal flow field characteristics, establish the working mechanism of cyclone desander, and improve the theoretical analysis. This method is mainly carried out on a computer, which can greatly reduce the cost of real experiments, but it can only be used for local structural improvements of cyclone desanders based on single-factor analysis, and the value of engineering application promotion is not high.

[0006] The method of using experimental design methods to form appropriate experimental plans and constructing experimental samples based on numerical simulation results to carry out the optimization design of cyclone desanders can effectively combine the advantages of the two and is gaining increasing attention from scholars at home and abroad. However, the implementation of this method is currently carried out on different platforms, such as numerical simulation in Fluent and experimental design on Design Expert. It is not very versatile and inefficient, especially for working conditions with very low concentrations of sandy turbid liquid, which is often affected by numerical calculations and fails. Summary of the invention

[0007] An object of the present invention is to solve at least the above problems and to provide at least the advantages which will be described hereinafter.

[0008] Another object of the present invention is to provide an efficient optimization design method for a cyclone desander based on Ansys Workbench to solve the technical problems existing in the prior art for the current cyclone desander selection design and performance optimization, such as platform dispersion, small number of samples, low efficiency, insufficient accuracy, and limited applicability to low sand-containing turbid liquid concentration conditions.

[0009] In order to achieve these purposes and other advantages according to the present invention, an efficient optimization design method for a cyclone desander based on Ansys Workbench is provided, and a unified process is built with a fluid simulation module and an optimization design module based on the Ansys Workbench work platform;

[0010] In the fluid simulation module, the fluid simulation workflow is used to complete the parameterization setting of the cyclone desander. The parameters of the parameterization setting include input parameters and output parameters. The input parameters include the structural parameters, operating parameters and physical parameters of the cyclone desander. The output parameters include the performance evaluation index parameters of the cyclone desander. The input parameters and the output parameters are parameterized.

[0011] In the optimization design module, each input parameter is used as the control variable, and each output parameter is used as the target variable. The automatic exploration of experimental samples is completed through orthogonal experimental design, and multi-parameter optimization is carried out in combination with response surface analysis to obtain the theoretical optimization design scheme of the cyclone desander. The scheme is then verified by reverse substitution to form an optimized design scheme for the cyclone desander.

[0012] Preferably, the steps are carried out in the following order:

[0013] S1. clarifying the input parameters and the output parameters of the cyclone desander, selecting a plurality of the input parameters as the control variables, selecting a plurality of the output parameters as the output variables, and performing parameter setting of the cyclone desander;

[0014] S2, giving a variation range of the input parameter;

[0015] S3, establishing a combined experimental design scheme of the orthogonal experimental design;

[0016] S4, obtaining the experimental sample, wherein the experimental sample includes statistics of different combinations of the input variables and the corresponding values ​​of the output variables;

[0017] S5. Response surface and sensitivity analysis, giving the contribution value of each input variable to the output variable, and obtaining the individual variation law of the output variable with each input variable from the contribution value;

[0018] S6. According to the result of step S5, a single or multiple output variables are clearly used as target variables, and the maximum or minimum value of the target variable is taken as the goal. Considering the compromise between multiple goals and performance, a theoretical optimization design scheme of the cyclone desander represented by the optimization parameters is obtained, and reverse verification is carried out;

[0019] S7. Complete the model selection and design and obtain the optimal design scheme of the cyclone desander.

[0020] Preferably, the specific method of parameter setting is:

[0021] A1. Using the Design Modeler module to establish or import a three-dimensional geometric model of a cyclone desander, and parameterizing the structural parameters of the three-dimensional geometric model of the cyclone desander in the Design Modeler module, wherein the structural parameters include a cylinder radius and an overflow pipe insertion depth;

[0022] A2. Control the mesh size and use the Ansys meshing module to automatically divide the mesh using unstructured meshes;

[0023] A3. Use fluid simulation software to establish a cyclone desander multiphase flow simulation model, and use CFD-POST software to complete the parameterized setting of the operating parameters, physical property parameters and performance evaluation index parameters of the cyclone desander.

[0024] Preferably, in step A3, when establishing a cyclone sand removal multiphase flow simulation model using fluid simulation software, the unstructured tetrahedral grid is converted into a polyhedral grid; the multiphase flow simulation uses the Euler two-phase flow model, in which the main phase is water and the second phase is sand, and the parameterization of the sand particle diameter and the like is completed in the working fluid physical property setting; the turbulence simulation uses the Reynolds stress model, with the velocity inlet and the pressure outlet as boundary conditions, and the parameterization setting of the flow rate and concentration of the sand-containing turbid liquid is completed on the velocity inlet boundary.

[0025] Preferably, in step A3, when the cyclone sand removal multiphase flow simulation model is established using fluid simulation software, the relaxation factor in different iteration step intervals is controlled so that the relaxation factor gradually decreases as the number of iteration steps increases.

[0026] Preferably, the optimization design module includes three parts: experimental design, response surface analysis and optimization analysis. The experimental design part is used to control the selection and generation method of the experimental sample plan based on the number of the input parameters and the given range of variation. The response surface analysis is used to obtain the contribution rate of each input parameter for each output parameter. The parameter optimization analysis part is used to form a final single-objective or multi-objective optimization design plan based on the experimental samples and the optimization algorithm after clarifying the target variable.

[0027] Preferably, in the experimental design part, during the exploration of the experimental samples, the parameterized fluid simulation workflow is based on the cyclone sand removal multiphase flow simulation model, automatically updates the grid according to the single value of each input variable, performs fluid simulation, and directly statistics the calculation results of the output variables obtained from the fluid simulation in the experimental samples.

[0028] Preferably, after obtaining the optimization parameters, based on the input parameters corresponding to the recommended optimal solution, on the one hand, the physical model and the input parameters in the fluid simulation workflow are directly and manually changed, and fluid simulation is performed; on the other hand, the optimization parameters are added as new experimental samples, and CFD numerical calculations are started again in the experimental design part to complete the effectiveness and reliability verification of the cyclone sand removal optimization design results.

[0029] The present invention has at least the following beneficial effects:

[0030] (1) Fluid simulation modeling based on Fluent converts tetrahedral meshes into polyhedral meshes, which can significantly reduce the number of meshes, effectively improve CFD calculation speed, and save time costs.

[0031] (2) In fluid simulation modeling, different relaxation factors can be used in different iterative calculation stages by calling a journal file or a TUI command, so that the relaxation factor can be controlled to gradually decrease in a complete calculation process, which effectively shortens the calculation time while meeting the convergence accuracy. The scope of application of the present invention is not limited to the concentration of sand-containing turbid liquid, especially for the working conditions of extremely low sand-containing turbid liquid concentration, the present invention is still effective.

[0032] (3) During the experimental design process, with the help of the parametric fluid simulation workflow, automatic grid updates and CFD simulation calculations can be completed according to the values ​​of each input variable, and the output variables or target parameter values ​​in the design sample can be directly obtained, thereby greatly reducing the workload of manual participation in the simulation modeling of individual sample fluids, reducing human errors, and improving the stability and reliability of the optimized design.

[0033] (4) After the sample selection and optimization scheme exploration based on the experimental design are completed, reverse verification can be directly carried out at the same time, which is convenient to operate and more feasible.

[0034] (5) When the present invention is used to implement the optimization design of the cyclone separator, the optimal structural parameters can be obtained without in-depth analysis of the internal flow mechanism of the cyclone desander, which provides great convenience for designers and R&D personnel.

[0035] (6) The optimization design method proposed in the present invention is not only suitable for cyclone separators, but also applicable to other fluid-solid separators with similar structures. At the same time, it provides a direction for the efficient optimization design of other fluid machinery, and has strong applicability and good practicality.

[0036] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1It is a basic structural schematic diagram of the cyclone desander of the present invention;

[0038] Figure 2 for Figure 1 Working principle diagram of cyclone desander;

[0039] Figure 3 A working diagram for optimizing the design of the cyclone desander of the present invention;

[0040] Figure 4 It is a schematic diagram of an optimization design module of a cyclone desander based on Ansys Workbench of the present invention;

[0041] Figure 5 It is a comparison chart of the separation efficiency sensitivity analysis results of a certain type of cyclone desander according to an embodiment of the present invention.

[0042] Explanation of the reference numerals in the specification: 1. feed pipe, 2. overflow pipe, 3. column section, 4. cone section, 5. discharge pipe. DETAILED DESCRIPTION

[0043] The present invention will be further described in detail below in conjunction with the accompanying drawings so that those skilled in the art can implement the invention with reference to the description.

[0044] It should be noted that the experimental methods described in the following embodiments are conventional methods unless otherwise specified, and the reagents and materials are commercially available unless otherwise specified; in the description of the present invention, the terms "lateral", "longitudinal", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0045] like Figure 1-5 As shown, the present invention provides an efficient optimization design method for a cyclone desander based on Ansys Workbench, which builds a unified process with a fluid simulation module and an optimization design module based on the Ansys Workbench work platform;

[0046] In the fluid simulation module, the fluid simulation workflow is used to complete the parameterization setting of the cyclone desander. The parameters of the parameterization setting include input parameters and output parameters. The input parameters include the structural parameters, operating parameters and physical parameters of the cyclone desander. The output parameters include the performance evaluation index parameters of the cyclone desander. The input parameters and the output parameters are parameterized.

[0047] In the optimization design module, each input parameter is used as the control variable, and each output parameter is used as the target variable. The automatic exploration of experimental samples is completed through orthogonal experimental design, and multi-parameter optimization is carried out in combination with response surface analysis to obtain the theoretical optimization design scheme of the cyclone desander. The scheme is then verified by reverse substitution to form an optimized design scheme for the cyclone desander.

[0048] Combination Figure 1-2 As shown in the figure, the main structure of the cyclone desander includes four parts, a cylindrical cone cavity, a tangential inlet (feeding port of feed pipe 1), and two axial outlets (the upper one is overflow pipe 2, and the lower one is discharge port or bottom flow port of discharge pipe 5). During the operation of the desander, the sand-containing turbid liquid first enters the cylindrical section 3 through the feed port and flows in a spiral direction in a vertical downward direction. After that, because the density of sand particles is higher than that of water, the centrifugal force is large, so it can overcome the fluid resistance and gradually concentrate on the wall of the cylindrical cone section 4 to form an external cyclone, and finally discharge through the bottom flow port as the radius of the cone section 4 gradually decreases; squeezed by the sand particles of the external cyclone, the water with lower density can only be concentrated in the middle of the cavity in the cylindrical section 3, and then because the radius of the cone section 4 gradually decreases, the squeezing strength of the sand particle flow gradually increases, and the central liquid in the cavity is forced to develop into a vertical upward internal cyclone, and finally discharged along the overflow pipe 2 to complete the solid-liquid separation.

[0049] Obviously, each structural parameter, operating parameter and physical property parameter will directly affect the cyclone desander effect, and their contribution amounts are different, and some parameters are coupled with each other, so they constitute the main variables for the selection design and performance optimization of the cyclone desander, and serve as input parameters in the fluid simulation module, while performance indicators such as separation efficiency, classification efficiency and pressure loss constitute target parameters, and serve as performance evaluation index parameters in the fluid simulation module. The fluid simulation software used in the fluid simulation of the present invention includes but is not limited to FLUENT, CFX, POLYFLOW, etc. The cyclone desander optimization design method proposed in the present invention can be based on Ansys The Workbench work platform uses the fluid simulation module and the optimization design module to build a unified process. In the fluid simulation module, various structural parameters are established in the geometric design part, and various operating parameters and physical parameters are established in the CFD modeling part. In the optimization design module, structural parameters, operating parameters and physical parameters are used as control variables (input parameters), and the performance parameters of the cyclone desander are used as target variables (output parameters). The multi-objective rapid optimization design method is effectively combined with experimental design and response surface analysis. In the optimization design process of the cyclone desander, the experimental samples containing the numerical values ​​of the input parameters and output parameters are automatically explored. According to the experimental design input parameter samples, the corresponding fluid simulation can be automatically completed to obtain the output parameter samples, thereby obtaining the theoretical optimization design scheme of the cyclone desander. This not only avoids the errors caused by human participation in the acquisition of various output parameter samples, but also effectively reduces the time cost, thereby significantly improving the optimization design efficiency. The final optimization design result can be directly reverse input verified, with good feasibility, higher scientificity, convenient overall implementation, efficient operation, reliable accuracy, and can effectively drive product research and development.

[0050] In another technical solution, Figure 3 , 4 As shown in the figure, the efficient optimization design method of cyclone desander based on Ansys Workbench is carried out in the following steps:

[0051] S1. The input parameters and the output parameters of the cyclone desander are clarified, a plurality of the input parameters are selected as the control variables, and a plurality of the output parameters are selected as the output variables to perform parameterized setting of the cyclone desander.

[0052] Based on the on-site requirements, the operating parameters of the cyclone desander (inlet flow rate and working pressure) and the physical parameters of the sand-containing turbid liquid (sand concentration, sand density, and sand particle size distribution) are determined. Based on the existing design experience and the actual flow requirements, the main structural parameters of the cyclone desander are clarified, such as the diameter of the column section 3, the height and cone angle of the cone section 4, and the insertion depth h of the overflow pipe 2.

[0053] In different application scenarios, the degree of attention paid to various performance indicators such as displacement, power consumption, separation efficiency, and classification efficiency varies. At this time, it is also necessary to clarify the target parameters of the cyclone desander based on on-site needs. The target parameters can be one or more.

[0054] After the above parameters are clarified, the control variables and target variables of the cyclone desander are determined, and the performance optimization and selection design of the whole machine can be carried out based on them.

[0055] Then, the fluid simulation parametric modeling (Fluid Flow (Fluent)) is carried out. The fluid simulation workflow (Fluid Flow) on the Ansys Workbench work platform has parametric design capabilities. All the control variables and target variables used in the parameter selection part can be set in each sub-module of the fluid simulation module. After completion, the parameter setting module (Parameter Set) will be automatically activated in the Workbench, listing all the parameters that have been set in the fluid simulation module, and classifying them into input parameters and output parameters. The input parameters are used as design variables and input variables, and the output parameters can be used as output variables and target variables. In addition, the parameter setting module (Parameter Set) can also define extended variables based on existing output variables, such as performance evaluation index parameters.

[0056] Then use the optimization design module (Response Surface Optimization), which consists of three sub-modules, namely, the Design of Experiments experimental design part, the Response Surface response surface analysis part, and the Optimization parameter optimization part.

[0057] S2. Given the variation range of the input parameters. In the experimental design part, the value range and value method of each input variable can be confirmed according to actual needs, while each output variable must rely on the fluid simulation results to obtain.

[0058] S3. Establish a combined experimental design scheme of the orthogonal experimental design.

[0059] S4. Acquire the experimental sample, in which different combinations of the input variables and corresponding values ​​of the output variables are counted.

[0060] S5. Based on the samples obtained from the experimental design, response surface and sensitivity analysis are performed to give the contribution value of each input variable to the output variable, and the individual variation pattern of the output variable with each input variable is obtained from the contribution value.

[0061] S6. According to the result of step S5, a single or multiple output variables are clearly used as target variables, and the maximum or minimum value of the target variable is taken as the goal. Considering the compromise between multiple goals and performance, a theoretical optimization design scheme of the cyclone desander represented by the optimization parameters is obtained, and reverse verification is carried out.

[0062] The optimized design scheme of the cyclone desander obtained by combining fluid simulation and experimental design samples is only the theoretical result of the optimization algorithm. Therefore, after the theoretical optimized design scheme is obtained, it is still necessary to carry out the cyclone desander performance verification to verify the effectiveness and reliability of the optimization results.

[0063] S7. Complete the model selection and design and obtain the optimal design scheme of the cyclone desander.

[0064] In another technical solution, Figure 3 , 4 As shown in the figure, the specific method of parameter setting is:

[0065] A1. Use the Design Modeler module to establish or import a three-dimensional geometric model of the cyclone desander, and parameterize the structural parameters of the three-dimensional geometric model of the cyclone desander in the Design Modeler module, wherein the structural parameters include the radius of the cylinder, the insertion depth of the overflow pipe 2, etc.;

[0066] A2. Apply unstructured grids, reasonably control the grid scale to meet the accuracy requirements of numerical calculations, and use the Ansysmeshing module to automatically divide the grid with unstructured grids;

[0067] A3. Use fluid simulation software to establish a cyclone desander multiphase flow simulation model, and use CFD-POST software to complete the parameterized setting of the operating parameters, physical property parameters and performance evaluation index parameters of the cyclone desander.

[0068] For example, based on Fluent software, complete CFD simulation modeling and parameter settings of other control variables, including Figure 2 (b) The two sub-modules of Setup and Solution are then applied to the fluid simulation post-processing module CFD-POST provided in Ansys Workbench, i.e. the Results section in Figure 2(b). After the post-processing variables are completed, they are usually the customization of the target variables, such as defining the performance parameter separation efficiency of the cyclone desander as the ratio of the mass flow rate of sand at the outlet to that at the inlet. Usually, the definition of each target variable can also be completed in the numerical calculation software Fluent.

[0069] In another technical solution, in step A3, when the cyclone sand removal multiphase flow simulation model is established using fluid simulation software, the unstructured tetrahedral grid is converted into a polyhedral grid; the multiphase flow simulation uses the Euler two-phase flow model, in which the main phase is water and the second phase is sand, and the parameterization of the sand particle diameter and the like is completed in the working fluid physical property setting; the turbulence simulation uses the Reynolds stress model, with the velocity inlet and pressure outlet as boundary conditions, and the parameterization setting of the flow rate and concentration of the sand-containing turbid liquid is completed on the velocity inlet boundary.

[0070] The cyclone desander uses tetrahedral unstructured grids to divide the computational domain, which often results in a large number of grids and occupies more computing resources. Therefore, the tetrahedral grids are first converted into polyhedral grids, which can greatly reduce the number of grids and improve the model calculation speed. The Eulerian two-phase flow model is used for multiphase flow simulation, and the Reynolds stress (RSM) model is used for turbulence simulation.

[0071] In another technical solution, in step A3, when the cyclone sand removal multiphase flow simulation model is established using fluid simulation software, the relaxation factor in different iteration step intervals is controlled so that the relaxation factor gradually decreases as the number of iteration steps increases.

[0072] During the optimization design of the cyclone desander, the control variables are constantly changing within their value ranges, especially the changes in the inlet sand concentration and particle size, which will have a great impact on the iterative calculation process and convergence of CFD. When the sand concentration and particle size are very small, the iterative calculation residual needs to reach 10 -6 The order of magnitude or even lower can meet the convergence accuracy requirement. At this time, the relaxation factor must be low enough and the number of iterative calculation steps must be large enough. If a unified relaxation factor is used for calculation, it will inevitably lead to an increase in computing resources and time costs. This embodiment takes into account both the number of iterative calculations and the convergence accuracy requirements, and uses Fluent's rich custom functions. By calling journal files or TUI commands, different relaxation factors can be used in different iterative calculation stages, thereby controlling the relaxation factor to gradually decrease in a complete calculation process, effectively reducing the calculation time while meeting the convergence accuracy, and controlling the convergence factor size according to the number of iterative steps to automatically adapt to low-concentration sand conditions and improve simulation accuracy.

[0073] In another technical solution, Figure 4 As shown, the optimization design module includes three parts: experimental design, response surface analysis and optimization analysis. The experimental design part is used to control the selection and generation method of the experimental sample plan based on the number of the input parameters and the given range of variation. The response surface analysis is used to obtain the contribution rate of each input parameter for each output parameter. The parameter optimization analysis part is used to form a final single-objective or multi-objective optimization design plan according to the experimental samples and the optimization algorithm after clarifying the target variable.

[0074] The experimental design part Design of Experiments provides a variety of algorithms to control the overall sample size and selection method, and seek an optimized design solution. At this time, the value range and value selection method of each input variable can be confirmed according to actual needs, while each output variable must rely on fluid simulation results to obtain. Based on the samples obtained from the experimental design, the response surface analysis part Response Surface can perform sensitivity analysis on each output parameter, give the contribution value of each input variable to the output variable, and obtain the individual change law of the output variable with each input variable. After the design exploration is completed, the parameter optimization part Optimization can clearly use a single or multiple output variables as the target variable, and take the maximum or minimum value of the target variable as the goal, considering the compromise between multiple goals and performance, and obtaining an optimized design solution.

[0075] In another technical solution, in the experimental design part, during the exploration of the experimental samples, the parameterized fluid simulation workflow is based on the cyclone sand removal multiphase flow simulation model, automatically updates the grid according to the single value of each input variable, performs fluid simulation, and directly statistics the calculation results of the output variables obtained from the fluid simulation in the experimental samples.

[0076] Although the number of input variable combinations is large during each experimental design process, the parameterized fluid simulation workflow can automatically perform meshing and fluid simulation for each sample, and count the corresponding output variable calculation values ​​in the experimental design list, thereby improving the model calculation speed.

[0077] In another technical solution, Figure 3 As shown, after obtaining the optimization parameters, based on the input parameters corresponding to the recommended optimal solution, on the one hand, the physical model and the input parameters in the fluid simulation workflow are directly changed manually, and fluid simulation is performed; on the other hand, the optimization parameters are added as new experimental samples, and the CFD numerical calculation is started again in the experimental design part to complete the effectiveness and reliability verification of the cyclone sand removal optimization design results, thereby further verifying the effectiveness and reliability of the optimization results.

[0078] It should be noted that the performance optimization of cyclone desander is often accompanied by the whole machine selection design. At this time, the above workflow is still valid. It only needs to segment the values ​​of each design variable in the experimental design part and ignore the parameter optimization part for the experimental design module. All candidate samples can be established and fluid simulation calculations can be automatically carried out to provide a theoretical basis for the formulation of cyclone desander model spectrum planning.

[0079] In summary, the high-efficiency optimization design method of cyclone desander based on Ansys Workbench of the present invention is based on Ansys The Workbench work platform uses the fluid simulation module and the optimization design module to build a unified process for convenience. In the fluid simulation module, various structural parameters are established in the geometric design part, and various operating parameters and physical parameters are established in the CFD modeling part. The number of grids is effectively reduced by using polyhedral grids, and the convergence factor is controlled according to the number of iterations to automatically adapt to low-concentration sand conditions and improve simulation accuracy. In the optimization design module, structural parameters, operating parameters and physical parameters are used as control variables (input parameters), and the performance parameters of the cyclone desander are used as target variables (output parameters). The multi-objective rapid optimization design method is effectively combined with experimental design and response surface analysis. The overall optimization design process of the cyclone desander can automatically complete the corresponding fluid simulation (including geometry establishment, grid division, CFD modeling and post-processing, etc.) according to the experimental design input parameter samples, and obtain the output parameter samples, which not only avoids the errors caused by human participation in the acquisition of each output parameter sample, but also improves the efficiency of optimization design. Combined with response surface analysis to carry out multi-parameter optimization, reverse input verification can be directly performed, which has good feasibility and higher scientificity.

[0080] Example:

[0081] Subject to site conditions, such as Figure 1 The diameter of the column section 3 of a certain type of cyclone desander shown in the figure ranges from 90 to 140 mm, and the diameter of the sand particles is 50 to 200 μm. Applying the optimization design method proposed in the present invention, this embodiment uses the column section 3 diameter, the insertion depth of the overflow pipe 2, and the sand particle diameter as control variables, and the separation efficiency (maximum value) as the target variable, and successfully completes the multi-parameter optimization and selection design of the cyclone desander.

[0082] During the optimization implementation process, the specific settings of each module are as follows:

[0083] (1) In the fluid simulation module, the diameter of column section 3 varies from 90 to 140 mm, the insertion depth of overflow pipe 2 varies from 0 to 200 mm, and the diameter of sand particles takes discrete values ​​of 100, 150, and 200 μm respectively; the inlet conditions are: the flow rate of sand-containing turbid liquid is 6 m / s, and the volume fraction of sand particles is 1%; the outlet conditions are: the gauge pressure is 0 MPa.

[0084] (2) In the experimental design module, select the central composite design method, automatically establish the experimental sample, and determine the appropriate sample size based on the quality of the experimental sample.

[0085] Based on the default multivariable optimization algorithm, the structural parameter optimization results corresponding to different sand particle diameters are obtained, as shown in Table 1 below.

[0086] Table 1 Optimization design results of a certain type of cyclone desander structure

[0087]

[0088] Since the separation efficiency of cyclone sand removal increases with the increase of sand particle size, the structural parameter values ​​corresponding to different particle sizes under the same working conditions tend to be consistent after optimization, which further proves the scientificity and effectiveness of the high-efficiency optimization design method of cyclone sand remover based on Ansys Workbench of the present invention. At the same time, the sensitivity analysis of the target parameters can directly obtain the contribution rate of each control variable to the target variable, such as Figure 5 As shown in the figure, the curve of the change law of each target variable with each control variable can be established. Figure 5 It can be seen that the cylinder radius R in the first column on the left has the greatest sensitivity to the separation efficiency, followed by the insertion depth h in the middle, and the least sensitive is the sand particle diameter D on the far right.

[0089] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation modes, and they can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

Claims

1. The high-efficiency optimization design method of cyclone desander based on Ansys Workbench is characterized by: Based on the Ansys Workbench work platform, a unified process is built with fluid simulation module and optimization design module; In the fluid simulation module, the fluid simulation workflow is used to complete the parameterization setting of the cyclone desander. The parameters of the parameterization setting include input parameters and output parameters. The input parameters include the structural parameters, operating parameters and physical parameters of the cyclone desander. The output parameters include the performance evaluation index parameters of the cyclone desander. The input parameters and the output parameters are parameterized. The specific method of parameter setting is: A1. Using the Design Modeler module to establish or import a three-dimensional geometric model of a cyclone desander, and parameterizing the structural parameters of the three-dimensional geometric model of the cyclone desander in the Design Modeler module, wherein the structural parameters include a cylinder radius and an overflow pipe insertion depth; A2. Control the mesh size and use the Ansys meshing module to automatically divide the mesh using unstructured meshes; A3. Using fluid simulation software to establish a cyclone desander multiphase flow simulation model, controlling the relaxation factor in different iteration step intervals so that the relaxation factor gradually decreases as the number of iteration steps increases, and combining CFD-POST software to complete the parameterization setting of the operating parameters, physical property parameters and performance evaluation index parameters of the cyclone desander; In the optimization design module, each input parameter is used as the control variable, and each output parameter is used as the target variable. The automatic exploration of experimental samples is completed through orthogonal experimental design, and multi-parameter optimization is carried out in combination with response surface analysis to obtain the theoretical optimization design scheme of the cyclone desander. The scheme is then verified by reverse substitution to form an optimized design scheme for the cyclone desander.

2. The high-efficiency optimization design method for a cyclone desander based on Ansys Workbench according to claim 1, characterized in that: Follow the steps below in order: S1. clarifying the input parameters and the output parameters of the cyclone desander, selecting a plurality of the input parameters as the control variables, selecting a plurality of the output parameters as the output variables, and performing parameter setting of the cyclone desander; S2, giving a variation range of the input parameter; S3, establishing a combined experimental design scheme of the orthogonal experimental design; S4, obtaining the experimental sample, wherein the experimental sample includes statistics of different combinations of the input variables and the corresponding values ​​of the output variables; S5. Response surface and sensitivity analysis, giving the contribution value of each input variable to the output variable, and obtaining the individual variation law of the output variable with each input variable from the contribution value; S6. According to the result of step S5, a single or multiple output variables are clearly used as target variables, and the maximum or minimum value of the target variable is taken as the goal. Considering the compromise between multiple goals and performance, a theoretical optimization design scheme of the cyclone desander represented by the optimization parameters is obtained, and reverse verification is carried out; S7. Complete the model selection and design and obtain the optimal design scheme of the cyclone desander.

3. The high-efficiency optimization design method for cyclone desander based on Ansys Workbench according to claim 2, characterized in that: In step A3, when the cyclone sand removal multiphase flow simulation model is established using fluid simulation software, the unstructured tetrahedral grid is converted into a polyhedral grid; the multiphase flow simulation uses the Euler two-phase flow model, in which the main phase is water and the second phase is sand, and the parameterization of the sand particle diameter and the like is completed in the working fluid physical property setting; the turbulence simulation uses the Reynolds stress model, with the velocity inlet and the pressure outlet as boundary conditions, and the parameterization setting of the flow rate and concentration of the sand-containing turbid liquid is completed on the velocity inlet boundary.

4. The high-efficiency optimization design method for cyclone desander based on Ansys Workbench according to claim 2, characterized in that: The optimization design module includes three parts: experimental design, response surface analysis and optimization analysis. The experimental design part is used to control the selection and generation method of the experimental sample plan based on the number of the input parameters and the given range of variation. The response surface analysis is used to obtain the contribution rate of each input parameter for each output parameter. The parameter optimization analysis part is used to form a final single-objective or multi-objective optimization design plan based on the experimental samples and the optimization algorithm after clarifying the target variable.

5. The high-efficiency optimization design method for cyclone desander based on Ansys Workbench according to claim 4, characterized in that: In the experimental design part, during the exploration of the experimental samples, the parameterized fluid simulation workflow is based on the cyclone sand removal multiphase flow simulation model, automatically updates the grid according to the single value of each input variable, performs fluid simulation, and directly statistics the calculation results of the output variables obtained from the fluid simulation in the experimental samples.

6. The high-efficiency optimization design method for cyclone desander based on Ansys Workbench according to claim 4, characterized in that: After obtaining the optimization parameters, based on the input parameters corresponding to the recommended optimal solution, on the one hand, the physical model and the input parameters in the fluid simulation workflow are directly changed manually, and fluid simulation is performed; on the other hand, the optimization parameters are added as new experimental samples, and CFD numerical calculations are started again in the experimental design part to complete the effectiveness and reliability verification of the cyclone sand removal optimization design results.

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