Rapid analysis method and device for airflow in glass tin bath

Abstract

The invention discloses a method and a device for rapidly analyzing airflow of a glass tin bath, which are used for solving the technical problem of poor simulation analysis effect of the glass tin bath in the prior art. The method comprises the following steps: establishing a geometric model of the glass tin bath, and extracting a computational domain of the geometric model; performing grid division on the computational domain to obtain a grid model, and setting boundary conditions of the grid model; performing parameterization setting on the grid model, and determining multiple parametric variables and multiple response variables; performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain a simulation result; and based on the simulation result, performing parameter optimization on the multi-parameter variables to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination. Therefore, through a parameterized simulation mode and in combination with parameter optimization, rapid analysis of the airflow of the glass tin bath is realized, the calculation complexity is reduced, the simulation efficiency is improved, and a better simulation effect is brought.

Description

Technical Field

[0001] The present invention relates to the technical field of glass simulation analysis, and in particular to a method for quickly analyzing airflow in a glass tin bath, a device for quickly analyzing airflow in a glass tin bath, an electronic device and a storage medium. Background Art

[0002] In the glass production line, the tin bath, which is the glass forming area, is one of the important thermal equipment in the glass production process. In this section, the bottom of the glass is molten tin liquid, and the upper space is filled with protective gas to prevent the tin liquid from being oxidized. In the actual production process, in order to ensure the smooth operation of the production line and the stability of glass quality, it is inevitable to make large or small adjustments to the production line. These adjustments are mainly based on the production experience of technicians and related research reports.

[0003] In the existing related technologies, the glass tin bath airflow is analyzed mainly in the following three ways:

[0004] Method 1: By testing the glass warpage value and tin penetration amount, the protective gas flow, composition, opening of the vent, and the amount of sulfur dioxide under the glass plate are adjusted. This adjustment method has a long response time and lacks timeliness.

[0005] Method 2: Use physical simulation methods to simulate the production of glass production lines at room temperature to study the effects of different batch ratios, edge drawing machine parameters, etc. on glass forming. This method improves the efficiency of studying production line problems to a certain extent, but due to the volume limitations of the physical model, there will be a large difference from the actual situation of the production line, and it is difficult to study the situation of the protective gas.

[0006] Method 3: Use finite element simulation software to simulate the temperature and velocity distribution of the glass ribbon, the temperature and velocity distribution of the protective gas in the glass tin bath forming process, and provide a reference for the production line action adjustment. However, its technical route is to optimize the model and reduce the calculation error by comparing the calculated results with the actual values. This process requires calculation of each case.

[0007] It can be seen that the above-mentioned methods for analyzing the glass tin bath have more or less problems such as long simulation time, low efficiency, and complex calculation, which leads to poor simulation analysis results. Summary of the invention

[0008] The present invention provides a glass tin bath airflow rapid analysis method, a glass tin bath airflow rapid analysis device, an electronic device and a storage medium, which are used to solve or partially solve the technical problem of poor glass tin bath simulation analysis effect in the existing related technology.

[0009] The present invention provides a method for rapid analysis of airflow in a glass tin bath, the method comprising:

[0010] Establishing a geometric model of a glass tin bath and extracting a calculation domain of the geometric model;

[0011] Meshing the computational domain to obtain a mesh model, and setting boundary conditions of the mesh model;

[0012] Parameterizing the grid model to determine multi-parameter variables and multi-response variables;

[0013] Perform parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results;

[0014] Based on the simulation results, parameter optimization is performed on the multi-parameter variables to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination.

[0015] Optionally, parameterizing the grid model to determine multiple parameter variables and multiple response variables includes:

[0016] Setting multiple output physical quantities of the key focus area of ​​the glass tin bath in the grid model as parameter variables to obtain multi-parameter variables;

[0017] A plurality of boundary condition variables affecting the plurality of output physical quantities are set as response variables to obtain multiple response variables.

[0018] Optionally, the method further comprises:

[0019] If the size of the geometric model needs to be changed, and the size change of the geometric model will cause the mesh of the mesh model to change, the parameter setting is performed by recording a journal.

[0020] Optionally, performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results includes:

[0021] Using the multiple response variables as input parameters and the multiple parameter variables as output parameters, performing DOE experimental design based on the input parameters and the output parameters to obtain multiple groups of design points;

[0022] Based on the Latin hypercube sampling method, parameter simulation calculation is performed according to the multiple groups of design points to obtain simulation results.

[0023] Optionally, performing parameter optimization on the multi-parameter variables based on the simulation results to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination includes:

[0024] According to a preset screening condition, screening at least one target parameter variable from the multi-parameter variables;

[0025] Analyzing the simulation results, and constructing a nonlinear relationship between the at least one target parameter variable and the multiple response variables according to the analysis results;

[0026] Based on the nonlinear relationship and in combination with preset constraints, parameter optimization is performed on the at least one target parameter variable to obtain an optimal solution combination, and based on the optimal solution combination, an optimal response variable combination of the multiple response variables is solved.

[0027] Optionally, performing parameter optimization on the at least one target parameter variable based on the nonlinear relationship and in combination with preset constraints to obtain an optimal solution combination includes:

[0028] Based on the nonlinear relationship and in combination with preset constraints, a multi-objective genetic algorithm is used to perform parameter optimization on the at least one target parameter variable to obtain a global optimal solution;

[0029] The global optimal solution is used as the optimal solution combination of the at least one target parameter variable under the nonlinear relationship.

[0030] Optionally, the boundary conditions include the protective gas composition, wall properties, heat temperature conditions, and protective gas inlet and outlet conditions of the glass tin bath.

[0031] The present invention also provides a glass tin bath airflow rapid analysis device, comprising:

[0032] A geometric model building module is used to build a geometric model of the glass tin bath and extract a calculation domain of the geometric model;

[0033] A meshing module, used to mesh the computational domain, obtain a mesh model, and set boundary conditions of the mesh model;

[0034] A parameter setting module, used for parameter setting the grid model and determining multi-parameter variables and multi-response variables;

[0035] A parameter simulation module, used for performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results;

[0036] The parameter optimization module is used to perform parameter optimization on the multi-parameter variables based on the simulation results to obtain the optimal solution combination of the multi-parameter variables and the optimal response variable combination corresponding to the optimal solution combination.

[0037] The present invention also provides an electronic device, the device comprising a processor and a memory:

[0038] The memory is used to store program code and transmit the program code to the processor;

[0039] The processor is used to execute the glass tin bath airflow rapid analysis method as described in any one of the above items according to the instructions in the program code.

[0040] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program codes, and the program codes are used to execute the glass tin bath airflow rapid analysis method as described in any one of the above items.

[0041] It can be seen from the above technical solutions that the present invention has the following advantages:

[0042] A method for rapid analysis of airflow in a glass tin bath is provided. First, a geometric model of a glass tin bath is established, and the computational domain of the geometric model is extracted; then, the computational domain is meshed to obtain a mesh model, and boundary conditions of the mesh model are set; then, the mesh model is parameterized to determine multi-parameter variables and multi-response variables; then, parameter simulation is performed based on the multi-parameter variables and multi-response variables to obtain simulation results; finally, based on the simulation results, parameter optimization is performed on the multi-parameter variables to obtain the optimal solution combination of the multi-parameter variables, and the optimal response variable combination corresponding to the optimal solution combination. Thus, through the parametric simulation method combined with parameter optimization, rapid analysis of the airflow in the glass tin bath is achieved, while reducing the computational complexity and improving the simulation efficiency, which can bring better simulation effects than the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A flowchart of the steps of a method for rapid analysis of airflow in a glass tin bath;

[0045] Figure 2 A schematic diagram of a constructed glass tin bath geometric model;

[0046] Figure 3 This is a schematic diagram of the calculation domain results of extracting a glass tin bath;

[0047] FIG4 (a) is a schematic diagram of the overall grid division of a glass tin bath;

[0048] FIG4( b ) is a partial enlarged schematic diagram of a glass tin bath grid division;

[0049] Figure 5 A schematic diagram of a parameter optimization result display interface;

[0050] Figure 6 A schematic diagram of a geometric model of a glass tin bath in a specific example;

[0051] Figure 7 A schematic diagram of a valve angle A for controlling a venting pipeline;

[0052] FIG8 (a) is a schematic diagram showing data when there is no backflow at the discharge port in a TUI interface;

[0053] FIG8( b ) is a schematic diagram showing data when there is backflow at the discharge port in a TUI interface;

[0054] Fig. 9 The present invention is a structural block diagram of a device for rapid analysis of airflow in a glass tin bath. DETAILED DESCRIPTION

[0055] The embodiments of the present invention provide a glass tin bath airflow rapid analysis method, a glass tin bath airflow rapid analysis device, an electronic device and a storage medium, which are used to solve or partially solve the technical problem of poor glass tin bath simulation analysis effect in the existing related technology.

[0056] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] As an example, in the existing related technology, the glass tin bath airflow is analyzed mainly in the following three ways:

[0058] Method 1: By testing the glass warpage value and tin penetration amount, the protective gas flow, composition, opening of the vent, and the amount of sulfur dioxide under the glass plate are adjusted. This adjustment method has a long response time and lacks timeliness.

[0059] Method 2: Use physical simulation methods to simulate the production of glass production lines at room temperature to study the effects of different batch ratios, edge drawing machine parameters, etc. on glass forming. This method improves the efficiency of studying production line problems to a certain extent, but due to the volume limitations of the physical model, there will be a large difference from the actual situation of the production line, and it is difficult to study the situation of the protective gas.

[0060] Method 3: Use finite element simulation software to simulate the temperature and velocity distribution of the glass ribbon, the temperature and velocity distribution of the protective gas in the glass tin bath forming process, and provide a reference for the production line action adjustment. However, its technical route is to optimize the model and reduce the calculation error by comparing the calculated results with the actual values. This process requires calculation of each case.

[0061] It can be seen that the above-mentioned methods for analyzing the glass tin bath have more or less problems such as long simulation time, low efficiency, and complex calculation, which leads to poor simulation analysis results.

[0062] Therefore, one of the core inventive points of the embodiment of the present invention is: in view of the deficiencies in the prior art, a method for rapid analysis of airflow in a glass tin bath is proposed by adopting a parametric simulation method. First, a geometric model of the glass tin bath is established, and the calculation domain of the geometric model is extracted; then the calculation domain is meshed to obtain a mesh model, and the boundary conditions of the mesh model are set; then the mesh model is parameterized to determine multi-parameter variables and multi-response variables; then parameter simulation is performed based on the multi-parameter variables and the multi-response variables to obtain simulation results; finally, based on the simulation results, parameter optimization is performed on the multi-parameter variables to obtain the optimal solution combination of the multi-parameter variables, and the optimal response variable combination corresponding to the optimal solution combination. Thus, by defining key simulation characteristics as parameters, regulating and controlling them in the parameter management interface, and using parametric drive to quickly change the geometric dimensions, material parameters, boundary conditions, etc. of the model, it is possible to comprehensively study the influence of certain parameters on key positions. By adopting the technical solution of the present invention, there is no need to use UDF (User-Defined Function) to link with other programming software. It can be realized only in workbench (an integrated development environment or platform for creating, running, debugging and analyzing simulation models), which reduces the computational complexity and improves the simulation efficiency. In addition, when necessary, the creation of a journal is used to provide computational assistance. On the one hand, the boundary conditions required to achieve the target results can be quickly obtained. On the other hand, it is convenient to study the influence of the parameters at key positions on the entire model, so as to realize parametric simulation based on workbench, better conduct in-depth analysis of the airflow of the glass tin bath, and provide an effective reference for subsequent production line adjustments.

[0063] Reference Figure 1 , shows a flowchart of a method for rapid analysis of airflow in a glass tin bath provided by an embodiment of the present invention, which may specifically include the following steps:

[0064] Step 101, establishing a geometric model of a glass tin bath, and extracting a calculation domain of the geometric model;

[0065] First, a three-dimensional geometric model of the glass tin bath can be established. Figure 2Then extract the computational domain, as shown in Figure 3 As shown. Based on the extraction of the calculation domain, the size parameterization can be set at the corresponding position later, such as the valve rotation angle of the release pipe, the release pipe height, etc.

[0066] Step 102, meshing the computational domain to obtain a mesh model, and setting boundary conditions of the mesh model;

[0067] Specifically, a mesh with a hexahedron as the core is used to mesh the computational domain (actually the three-dimensional geometric model of the glass tin bath) to obtain a mesh model. For example, FIG4 (a) shows an overall schematic diagram of a glass tin bath mesh division. FIG4 (b) shows a partial enlarged schematic diagram of a glass tin bath mesh division. In the figure, meshes of different colors correspond to different computational domains.

[0068] Then, according to the actual production situation, boundary conditions are set. Specifically, the boundary conditions that need to be set include the protective gas composition of the glass tin bath, the wall properties, the heat temperature conditions (temperature distribution of the glass plate and the top cover), and the protective gas inlet and outlet conditions.

[0069] Step 103, parameterizing the grid model to determine multi-parameter variables and multi-response variables;

[0070] In this step, several parameters that need to be studied are determined according to actual needs, and the effects of these parameters are set as output parameters.

[0071] Specifically, the grid model is parameterized to determine multi-parameter variables and multi-response variables, which can be as follows: multiple output physical quantities (corresponding to output parameters) of the key focus area of ​​the glass tin bath in the grid model are set as parameter variables to obtain multi-parameter variables; multiple boundary condition variables (corresponding to input parameters) that affect the multiple output physical quantities are set as response variables to obtain multi-response variables.

[0072] For example, the parameter setting example is shown in Table 1 below:

[0073]

[0074] Table 1: Example of parameterization settings

[0075] In Table 1, parameter P1 is the angle of the vent pipe valve, which ranges from 0° to 90°, corresponding to the "fully open" and "closed" states, such as setting it to 50°. Parameter P2 is the height of the vent pipe, such as setting it to 2000mm. Parameter P3 is the velocity of the glass tin bath inlet 3 (inlet3), which can be set in the range of 0.001m / s-0.005m / s, corresponding to the air intake that can be achieved under actual working conditions, such as setting it to 0.002m / s. Parameter P4 is the average flow rate at the outlet of the glass tin bath. Parameter P5 is the average flow rate of the vent (i.e., outlet 2-7). Parameter P6 is the average pressure on the lower surface of the top cover brick. P7 is the mass flow rate of the vent.

[0076] In addition to the parameters listed in Table 1 above, when other parameters need to be studied and analyzed, those skilled in the art may also set other parameters as input parameters or output parameters according to actual conditions. It is to be understood that the present invention is not limited to this.

[0077] Furthermore, if the size change of the 3D geometric model will cause the mesh change, the size parameter can be set by recording a journal. That is, the journal is recorded in advance, and then the size change, mesh division and simulation calculation are realized by automatically running the journal software, so as to realize the automatic execution of a series of tasks.

[0078] In the workbench, a journal file is a script file used to record user interaction operations. These operations may include creating geometry, modifying dimensions, dividing meshes, setting material properties, applying loads, defining boundary conditions, performing simulations, etc. By recording these operations, the journal file can be re-executed to achieve automation.

[0079] In a specific implementation, if the size of the geometric model needs to be changed, and the size change of the geometric model will cause the mesh of the mesh model to change, the parameter setting is performed by recording a journal.

[0080] Step 104, performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results;

[0081] According to the determined input parameters and output parameters, DOE (Design of Experiments) is carried out to give multiple sets of design points and calculate to obtain simulation results.

[0082] Among them, DOE experimental design is a statistical method used to systematically determine the impact of experimental factors on response variables. DOE experimental design is widely used in industry, scientific research, quality management and other fields. It is especially important in finding the best process parameters and optimizing product design.

[0083] In a specific implementation, parameter simulation is performed according to multiple parameter variables and multiple response variables to obtain simulation results. The simulation results can be obtained by: taking multiple response variables as input parameters and multiple parameter variables as output parameters, performing DOE experimental design based on the input parameters and output parameters to obtain multiple groups of design points; and performing parameter simulation calculations based on multiple groups of design points based on the Latin hypercube sampling method to obtain simulation results.

[0084] For example, the DOE experimental design and calculation results provided in the embodiments of the present invention are shown in Table 2 below:

[0085]

[0086] Table 2: Example of DOE experimental design and calculation results

[0087] Step 105 , based on the simulation results, performing parameter optimization on the multi-parameter variables to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination.

[0088] Finally, the calculation results are analyzed and the optimization process is carried out. When the simulation is completed, the calculation results are checked in the software, and optimization is performed based on the optimization algorithm to find the expected value of the response variable and the corresponding parameter variable value.

[0089] In a specific implementation, based on the simulation results, parameter optimization is performed on the multi-parameter variables to obtain the optimal solution combination of the multi-parameter variables and the optimal response variable combination corresponding to the optimal solution combination. The method can be as follows: according to preset screening conditions, at least one target parameter variable is screened from the multi-parameter variables; the simulation results are analyzed, and according to the analysis results, a nonlinear relationship between at least one target parameter variable and the multiple response variables is constructed; based on the nonlinear relationship, combined with preset constraints, parameter optimization is performed on at least one target parameter variable to obtain the optimal solution combination, and according to the optimal solution combination, the optimal response variable combination of the multiple response variables is solved.

[0090] Furthermore, based on the nonlinear relationship and in combination with preset constraints, performing parameter optimization on at least one target parameter variable to obtain an optimal solution combination can be as follows: based on the nonlinear relationship and in combination with preset constraints, performing parameter optimization on at least one target parameter variable using a multi-objective genetic algorithm to obtain a global optimal solution; and using the global optimal solution as the optimal solution combination of at least one target parameter variable under a nonlinear relationship.

[0091] Combined with the above introduction, for example, Figure 5 A schematic diagram of a parameter optimization result display interface is shown.

[0092] First, according to the preset screening conditions, for example, the parameter variables that need to be further optimized or whose optimal solution needs to be found are input in advance, and at least one target parameter variable is screened from the multiple parameter variables. Figure 5 Only the output parameter P7 is shown as the target parameter variable.

[0093] Then, the simulation results are analyzed, and based on the analysis results, a nonlinear relationship between at least one target parameter variable and multiple response variables is constructed. For example, based on the actual simulation analysis results, a nonlinear relationship between the target parameter variable P7 and the multiple response variables P1, P2, and P3 is constructed.

[0094] Finally, based on the nonlinear relationship and the preset constraints, at least one target parameter variable is optimized to obtain the optimal solution combination, and the optimal response variable combination of multiple response variables is solved according to the optimal solution combination. For example, among the many points of the nonlinear relationship constructed above, the target parameter variable P7=5Pa is used as the target, and P7≥0Pa is used as the constraint. The multi-objective genetic algorithm (MOGA) is used to optimize the parameters, find the candidate point that best meets the requirements, and determine the optimal response variable combination composed of the P1, P2, and P3 values ​​corresponding to the candidate point.

[0095] Among them, in multi-objective optimization problems, there may be more than one optimal solution (i.e., the candidate point closest to meeting the requirements) obtained through parameter optimization. Figure 5 After parameter optimization, the three optimal solutions with the smallest error from the expected target and the most consistent with the target parameter variable P7=5Pa can be obtained, namely candidate point 1 (P7=4.9999Pa), candidate point 2 (P7=5.0001Pa) and candidate point 3 (P7=4.9997Pa). Each candidate point corresponds to a set of optimal response variable combinations. Subsequent technicians can combine experience and other parameter values ​​to further analyze the change relationship between multiple parameters corresponding to each candidate point, so as to analyze the changes in the airflow of the glass tin bath in more depth.

[0096] It can be understood that when only one target parameter variable is selected (such as only P7), the optimal solution combination finally obtained is actually the value of the target parameter variable when the corresponding candidate point is selected, such as the P7 value corresponding to candidate point 1, candidate point 2 or candidate point 3. The number of solutions in the optimal solution combination solution set is the number of candidate points. Figure 5There are three optimal solution combinations (corresponding to three candidate points 1, 2, and 3), and the number of parameter variables in each optimal solution combination is one (target parameter variable P7). The optimal response variable combination is the (P1, P2, P3) values ​​corresponding to candidate point 1, candidate point 2, or candidate point 3. Alternatively, technicians can choose to view and analyze only one or two of the values ​​of each candidate point (P1, P2, P3) according to actual needs.

[0097] When two or more target parameter variables are selected (such as selecting P4 and P7 at the same time), it is assumed that two candidate points are obtained through parameter optimization, namely candidate point 4 and candidate point 5. Then the optimal solution combination finally obtained is actually the values ​​of the two target parameter variables when the candidate points are selected, such as the (P4, P7) values ​​corresponding to candidate point 4 or candidate point 5. At this time, there are two optimal solution combinations (corresponding to two candidate points 4 and 5), and the number of parameter variables in each optimal solution combination is two (target parameter variables P4 and P7). The optimal response variable combination is the (P1, P2, P3) values ​​corresponding to candidate point 4 or candidate point 5. Or the technician can also choose to view and analyze only one or two of the values ​​of each candidate point (P1, P2, P3) according to actual needs.

[0098] That is to say, the selection of target parameter variables in subsequent optimization and the selection of the optimal response variable combination of multiple response variables after parameter optimization can be flexibly set according to actual simulation requirements or actual research purposes. It is understandable that the present invention does not limit this.

[0099] In an embodiment of the present invention, a method for rapid analysis of glass tin bath airflow is proposed by adopting a parametric simulation method. By defining key simulation characteristics as parameters and adjusting them in the parameter management interface, the geometric dimensions, material parameters, boundary conditions, etc. of the model can be quickly changed by parametric drive, so that the influence of certain parameters on key positions can be comprehensively studied. By adopting the technical solution of the present invention, there is no need to use UDF to link with other programming software, and it can be implemented only in the workbench, which improves the simulation efficiency while reducing the calculation complexity. When necessary, the calculation assistance is provided by creating a journal. On the one hand, the boundary conditions required to achieve the target results can be quickly obtained. On the other hand, it is convenient to study the influence of the parameters of the key positions on the entire model, so as to realize the parametric simulation based on the workbench, and better conduct in-depth analysis of the glass tin bath airflow, and provide an effective reference for subsequent production line adjustments.

[0100] For ease of understanding, the embodiments of the present invention are described below by using two specific examples in combination with the above-introduced contents.

[0101] Example 1:

[0102] The analysis purpose of designing the simulation experiment is to maximize the flow rate at each outlet by adjusting the air intake volume and the angle of the release valve.

[0103] If other existing methods are used, multiple examples need to be used for analysis, and various working conditions need to be comprehensively compared to obtain the final result. However, the parametric analysis method provided by the embodiment of the present invention can directly and quickly find the target value, and can also analyze the influence trend of each output parameter.

[0104] 1. Create a 3D geometric model of the glass tin bath

[0105] Use 3D modeling software to create a 3D geometric model of the glass tin bath, and extract the calculation domain in 3D computer-aided design software (such as SpaceClaim). Figures 2 to 3 The three-dimensional geometric model and computational domain model of the glass tin bath are shown in Figure 1. In the computational domain, the valve angle A of the vent pipe is set as an input parameter so that the parameter setting here can be recognized in the subsequent solution steps.

[0106] In order to reduce the amount of calculation, the model is simplified. Remove the 13 groups of air intake pipes at the top and simplify it to Figure 6 The schematic diagram of the geometric model is shown. The overall structure is divided into four parts, part 1-4. Air is taken in from part 1-4, and the top surfaces of the four parts are inlets, which are named inlet 1 (inlet1), inlet 2 (inlet2), inlet 3 (inlet3), and inlet 4 (inlet4) respectively. The outlet at the end of the tin bath and the six vents are outlets, which are named outlet 1 (outlet1), outlet 2 (outlet2), outlet 3 (outlet3), outlet 4 (outlet4), outlet 5 (outlet5), outlet 6 (outlet6), and outlet 7 (outlet7). Below the top four parts are cover bricks. Further down is the bottom space in the trough. The bottom surface of the model is defined as a glass plate (wall glass, because this part has little to do with parameter analysis, it is not shown in the figure), so that the software can automatically recognize it as a wall surface.

[0107] Parameterize the valve at the vent. Figure 7 As shown, the valve rotation angle is A (also known as the vent pipe valve opening), which is set as an input parameter. The initial value is 0° for full open and 90° for closed.

[0108] It should be pointed out that the valve rotation angle A, including the vent pipe height described below, are only two examples of parameterized settings. In practical applications, other three-dimensional dimensions can also be used as input parameters for parameterized settings. Such as the height of the tin bath top cover, the outlet height, etc. (dimensions that can be adjusted after the production line is built). For another example, when designing the production line before building the line, the analysis done, such as the tin bath width, length, contraction section position, width, etc., can all be parameterized with reference to the scheme proposed in the embodiment of the present invention. It will be understood that the present invention is not limited to this.

[0109] The height of the release pipe is parameterized, and the initial height is 2000mm. It should be noted that increasing the height of the release pipe will increase the size of the model, causing changes in the subsequent grid and affecting the calculation process. Therefore, it is necessary to record the journal to assist in meshing. However, if the script and parameterization are performed at the same time, it is easy to cause errors in the setting process. Therefore, when the amount of calculation is not very large, it is recommended to use a separate journal recording method to realize the calculation of release pipes of different heights. In the embodiment of the present invention, the stretching length of the release pipe is not parameterized, and the journal method is used in the comparative example mentioned below to realize the simulation calculation of different heights.

[0110] 2. Grid division

[0111] The obtained calculation domain is meshed using meshing software. Considering the calculation efficiency and calculation error, the meshing method with hexahedron as the core is adopted here. The mesh model obtained after meshing is shown in Figure 4 (a) and Figure 4 (b). Among them, the number of grids is 4.7 million, the minimum size is 2.5mm, the maximum size is 320mm, and the orthogonal quality is 0.21, which is greater than 0.2, meeting the subsequent calculation requirements.

[0112] 3. Set boundary conditions

[0113] The boundary conditions are set according to the actual production situation. The inlet and outlet are velocity inlet and pressure outlet respectively. The middle top brick is defined as a porous medium. The temperature of the bottom glass plate is simplified to an expression of temperature variation with position. The specific settings are shown in Table 3 below:

[0114]

[0115] Table 3: Boundary condition settings

[0116] In this example, the SST k-ω model (Shear Stress Transport k-ω Model, an advanced turbulence model) is used. This model combines the advantages of the k-ω model in near-wall calculations and the k-ε model in far-field calculations. Compared with the standard k-ω, the SST k-ω adds a lateral dissipation derivative term and considers the transport process of turbulent shear stress in the definition of turbulent viscosity, making the SST k-ω more applicable.

[0117] 4. Parameterized settings

[0118] Specifically, in this example, the input parameter P1 is the angle of the vent pipe valve, which ranges from 0° to 90°, corresponding to the "fully open" and "closed" states, and the initial angle is set to 0° by default. The input parameter P2 is the velocity of the glass tin bath inlet 3 (inlet3), which can be set in the range of 0.001m / s-0.005m / s, corresponding to the air intake that can be achieved under actual working conditions, such as setting it to 0.003m / s. The output parameter P3 is the average flow rate at the outlet of the glass tin bath. Output P4 is the average flow rate of the vent (i.e. outlet outlet2-7). Parameter P5 is the average flow rate of the vent (i.e. outlet outlet2-7). Parameter P6 is the average pressure on the lower surface of the top cover brick. P7 is the mass flow rate of the vent.

[0119] The convergence is judged based on mass conservation, and the parameterization settings are shown in Table 4 below:

[0120]

[0121] Table 4: Parameterization settings

[0122] Latin Hypercube Sampling (LHS) is used for DOE experimental design. Latin Hypercube Sampling is an experimental design method based on space filling technology. It is mainly used to reduce the variance in uncertainty analysis and sensitivity analysis in simulation. It can more fully explore the entire design variable space with a small number of points. Compared with traditional Monte Carlo Sampling, Latin Hypercube Sampling can more effectively cover the sample space of input variables and provide better distribution estimates when the number of samples is small.

[0123] Based on the DOE experimental design, the design points were generated and the simulation calculations were performed to obtain the results shown in Table 5 below:

[0124]

[0125] Table 5: Design points and calculation results

[0126] Among them, columns P1 and P2 are the design points generated by Latin hypercube sampling, and P3-P7 are the corresponding calculation results.

[0127] 5. Analyze the calculation results

[0128] According to the calculation results in Table 5, the mass flow rate of P6 is 10 -4 The level basically meets the mass conservation. Combined with the residual curve, it can be judged that the calculation results are approximately converged and meet the calculation requirements.

[0129] Then, response surface optimization can be further performed. In the embodiment of the present invention, a multi-objective genetic algorithm is used for optimization. The algorithm can search in a larger solution space, is not easy to fall into a local optimal solution, and is helpful to find a more global optimal response surface model parameter. If only the flow rate is considered, the maximum value of the output parameters P3 and P4 is found, and the results are shown in Table 6 below:

[0130]

[0131] Table 6: Optimization results for maximum flow velocity

[0132] It can be seen from Table 6 that when the opening of the vent pipe valve is very small, the velocity reaches the maximum value. However, in actual situations, although the velocity is the highest at this time, the very small valve opening obviously cannot quickly discharge the pollutants in the air flow, and thus cannot be used in the actual production process. Therefore, at this time, the vent mass flow monitoring data is added and re-analyzed.

[0133] Adding the mass flow monitoring of the vent port, that is, satisfying the maximum flow velocity and the maximum mass flow at the same time. The optimization results are shown in Table 7 below:

[0134]

[0135] Table 7: Optimization results for maximum flow rate and mass flow rate

[0136] From Table 7, it can be seen that when the valve of the vent pipe is basically fully open and the flow rate of inlet 3 is maintained at 0.00336m / s, the flow rate at each location can be maintained at a relatively large value, while also meeting the requirement of a relatively large flow rate at the vent. Obviously, this result is more in line with the actual situation in production. Therefore, the production line can refer to this data for adjustment.

[0137] Example 2 (Comparison of size changes):

[0138] Based on the optimal result of Example 1 above, a parametric simulation calculation is performed on the conditions of different heights of the discharge port by recording a journal.

[0139] The process of creating a 3D geometric model is the same as that in Example 1. When extracting the calculation domain, turn on the script recording switch in the workbench to record the journal file. Increase the stretching and release port height operation until the steps for running the calculation are set, and then end the script recording. The boundary conditions of the valve opening and the flow rate of inlet3 use the data of candidate point 3 in Table 7, and the rest are the same as in Example 1.

[0140] Then open the saved journal file and copy the above content multiple times below the current content. The number of times depends on the different heights of the release ports to be studied. The current content refers to the content in the script file. If you want to implement calculations at different heights, you need to copy all the content in the journal file once to the bottom of the script file content, and then modify the height setting. Repeat this operation to achieve different height modifications.

[0141] The following is part of the code for modifying the height of the release pipe:

[0142]

[0143] The "1000" in the above code means adding 1000mm to 2000mm, that is, this example is used for simulation calculation of a 3000mm high release pipe.

[0144] In Example 1, the initial height of the vent has been defined as 2000mm, and the stretch heights in the copied journal file are set to 500mm, 1000mm, 1500mm, and 2000mm respectively. That is, the journal file needs to be copied 4 times, and the stretch heights are changed to 500mm, 1000mm, 1500mm, and 2000mm respectively. After completion, save the document and run the journal document in the workbench. Finally, the calculation results of different vent pipe heights can be obtained, as shown in Table 8 below:

[0145]

[0146] Table 8: Simulation results of different release heights

[0147] Among them, P2-P5 in Table 8 above respectively represent the average flow velocity at the outlet of the glass tin bath, the average flow velocity at the vent, the average pressure on the lower surface of the top cover brick, and the mass flow rate at the vent.

[0148] It can be seen that as the height of the vent pipe increases, the parameters in various places in the tin bath do not change significantly. This shows that the gradual increase in the height of the vent pipe above 2000mm will not have a significant impact on the gas flow in the tank. However, in the TUI interface (Text User Interface) of the software, it can be seen that as the height increases, the reflux phenomenon of the vent port gradually eases. This is because as the height increases, the flow in the pipe is fully developed, which makes the reflux phenomenon disappear.

[0149] For example, Fig. 8 (a) shows a schematic diagram of data display when there is no backflow at the pressure outlet in a TUI interface, and Fig. 8 (b) shows a schematic diagram of data display when there is backflow at the pressure outlet in a TUI interface. Among them, "Reversed flow on xx faces (xx area) of pressure-outlet xx" indicates that there is backflow at the pressure outlet.

[0150] It can be seen from the above examples 1 and 2 that the use of parametric simulation can not only quickly study the impact of different input parameters such as geometric dimensions and boundary conditions on key positions, but also comprehensively consider various parameters to achieve the desired gas flow conditions.

[0151] Reference Fig. 9 , shows a structural block diagram of a glass tin bath airflow rapid analysis device provided by an embodiment of the present invention, which may specifically include:

[0152] A geometric model building module 901 is used to build a geometric model of a glass tin bath and extract a calculation domain of the geometric model;

[0153] A meshing module 902 is used to mesh the computational domain, obtain a mesh model, and set boundary conditions of the mesh model;

[0154] A parameter setting module 903 is used to perform parameter setting on the grid model and determine multi-parameter variables and multi-response variables;

[0155] A parameter simulation module 904 is used to perform parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results;

[0156] The parameter optimization module 905 is used to perform parameter optimization on the multi-parameter variables based on the simulation results to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination.

[0157] In an optional embodiment, the parameterization setting module 903 includes:

[0158] A parameter variable setting module, used for setting a plurality of output physical quantities of a key focus area of ​​the glass tin bath in the grid model as parameter variables to obtain a multi-parameter variable;

[0159] The response variable setting module is used to set multiple boundary condition variables that affect the multiple output physical quantities as response variables to obtain multiple response variables.

[0160] In an optional embodiment, the device further includes:

[0161] The journal recording execution module is used to perform parameter setting by recording a journal when the size of the geometric model needs to be changed and the size change of the geometric model will cause the mesh of the mesh model to change.

[0162] In an optional embodiment, the parameter simulation module 904 includes:

[0163] A DOE experimental design module is used to use the multiple response variables as input parameters and the multiple parameter variables as output parameters, and to perform DOE experimental design based on the input parameters and the output parameters to obtain multiple groups of design points;

[0164] The parameter simulation calculation module is used to perform parameter simulation calculation according to the multiple groups of design points based on the Latin hypercube sampling method to obtain simulation results.

[0165] In an optional embodiment, the parameter optimization module 905 includes:

[0166] A target parameter variable screening module, used to screen at least one target parameter variable from the multiple parameter variables according to a preset screening condition;

[0167] A nonlinear relationship building module, used for analyzing the simulation results and building a nonlinear relationship between the at least one target parameter variable and the multiple response variables according to the analysis results;

[0168] The parameter optimization submodule is used to perform parameter optimization on the at least one target parameter variable based on the nonlinear relationship and in combination with preset constraints to obtain an optimal solution combination, and solve the optimal response variable combination of the multiple response variables based on the optimal solution combination.

[0169] In an optional embodiment, the parameter optimization submodule includes:

[0170] A global optimal solution solving module, used to optimize the parameters of the at least one target parameter variable using a multi-objective genetic algorithm based on the nonlinear relationship and in combination with preset constraints to obtain a global optimal solution;

[0171] The optimal solution combination determination module is used to use the global optimal solution as the optimal solution combination of the at least one target parameter variable under the nonlinear relationship.

[0172] In an optional embodiment, the boundary conditions include the protective gas composition, wall properties, heat temperature conditions, and protective gas inlet and outlet conditions of the glass tin bath.

[0173] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the aforementioned method embodiment.

[0174] An embodiment of the present invention further provides an electronic device, the device comprising a processor and a memory:

[0175] The memory is used to store the program code and transmit the program code to the processor;

[0176] The processor is used to execute the glass tin bath airflow rapid analysis method of any embodiment of the present invention according to the instructions in the program code.

[0177] An embodiment of the present invention further provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the glass tin bath airflow rapid analysis method of any embodiment of the present invention.

[0178] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0179] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0180] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0181] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0182] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0183] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for rapid analysis of airflow in a glass tin bath, characterized in that: include: Establishing a geometric model of a glass tin bath and extracting a calculation domain of the geometric model; Meshing the computational domain to obtain a mesh model, and setting boundary conditions of the mesh model; Parameterizing the grid model to determine multi-parameter variables and multi-response variables; Perform parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results; Based on the simulation results, parameter optimization is performed on the multi-parameter variables to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination.

2. The method for rapid analysis of airflow in a glass tin bath according to claim 1, characterized in that: The parameterization of the grid model to determine the multi-parameter variables and the multi-response variables includes: Setting multiple output physical quantities of the key focus area of ​​the glass tin bath in the grid model as parameter variables to obtain multi-parameter variables; A plurality of boundary condition variables affecting the plurality of output physical quantities are set as response variables to obtain multiple response variables.

3. The method for rapid analysis of airflow in a glass tin bath according to claim 2, characterized in that: Also includes: If the size of the geometric model needs to be changed, and the size change of the geometric model will cause the mesh of the mesh model to change, the parameter setting is performed by recording a journal.

4. The method for rapid analysis of airflow in a glass tin bath according to claim 1, characterized in that: The performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results includes: Using the multiple response variables as input parameters and the multiple parameter variables as output parameters, performing DOE experimental design based on the input parameters and the output parameters to obtain multiple groups of design points; Based on the Latin hypercube sampling method, parameter simulation calculation is performed according to the multiple groups of design points to obtain simulation results.

5. The method for rapid analysis of airflow in a glass tin bath according to claim 1, characterized in that: The step of performing parameter optimization on the multi-parameter variables based on the simulation results to obtain an optimal solution combination of the multi-parameter variables and an optimal response variable combination corresponding to the optimal solution combination includes: According to a preset screening condition, screening at least one target parameter variable from the multi-parameter variables; Analyzing the simulation results, and constructing a nonlinear relationship between the at least one target parameter variable and the multiple response variables according to the analysis results; Based on the nonlinear relationship and in combination with preset constraints, parameter optimization is performed on the at least one target parameter variable to obtain an optimal solution combination, and based on the optimal solution combination, an optimal response variable combination of the multiple response variables is solved.

6. The method for rapid analysis of airflow in a glass tin bath according to claim 5, characterized in that: The step of performing parameter optimization on the at least one target parameter variable based on the nonlinear relationship and in combination with preset constraints to obtain an optimal solution combination includes: Based on the nonlinear relationship and in combination with preset constraints, a multi-objective genetic algorithm is used to perform parameter optimization on the at least one target parameter variable to obtain a global optimal solution; The global optimal solution is used as the optimal solution combination of the at least one target parameter variable under the nonlinear relationship.

7. The method for rapid analysis of airflow in a glass tin bath according to any one of claims 1 to 6, characterized in that: The boundary conditions include the protective gas composition, wall properties, heat temperature conditions, and protective gas inlet and outlet conditions of the glass tin bath.

8. A glass tin bath airflow rapid analysis device, characterized in that: include: A geometric model building module is used to build a geometric model of the glass tin bath and extract a calculation domain of the geometric model; A meshing module, used to mesh the computational domain, obtain a mesh model, and set boundary conditions of the mesh model; A parameter setting module, used for parameter setting the grid model and determining multi-parameter variables and multi-response variables; A parameter simulation module, used for performing parameter simulation according to the multiple parameter variables and the multiple response variables to obtain simulation results; The parameter optimization module is used to perform parameter optimization on the multi-parameter variables based on the simulation results to obtain the optimal solution combination of the multi-parameter variables and the optimal response variable combination corresponding to the optimal solution combination.

9. An electronic device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the glass tin bath airflow rapid analysis method according to any one of claims 1-7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the glass tin bath airflow rapid analysis method according to any one of claims 1-7.

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