A method and device for simulating high-viscosity fluid vector coating

Abstract

The present invention discloses a method and device for simulating the vector coating of high-viscosity fluids. The method comprises: establishing a geometric model of the effective area of ​​vector coating; meshing the geometric model to obtain a structured grid and an unstructured grid; adjusting the size of the structured grid and the unstructured grid; selecting a multiphase flow model, and turning on an energy model and a turbulence model; setting the physical parameters of the gas phase and the fluid phase, unit area conditions and boundary conditions, as well as an iteration method, step size and convergence accuracy; according to the iteration method, step size and convergence accuracy, using the multiphase flow model, energy model and turbulence model in combination with the above parameters to perform iterative calculations to obtain a phase diagram, volume fraction and velocity cloud diagram; based on the phase diagram, volume fraction and velocity cloud diagram, determining the relationship between the factors affecting the vector coating and the vector coating effect; when the relationship is consistent with the actual situation, ending the simulation process. The present invention can solve the problem that the parameters affecting the vector coating are unclear and the vector coating effect is difficult to observe.

Description

Technical Field

[0001] The present invention relates to the technical field of coating fluid simulation, in particular to a method and a device for simulating the vector coating of a high-viscosity fluid. Background Art

[0002] When an aircraft flies inside the atmosphere, the solid fuel tank has to withstand a series of extreme conditions such as high temperature, high pressure and high friction. Therefore, the shell must be covered with a protective layer during flight to protect the shell from being disturbed by external high temperature conditions. At the same time, the shell will produce static electricity due to intense friction with the air during high-speed flight. It should also avoid interference from static factors, so it must be covered with an anti-static coating. Related research has developed a coating that has both exothermic and anti-static effects. The coating has the characteristics of high viscosity, low density, and a large solid content. Due to the high viscosity of the coating, it is difficult to implement mature coating processes such as spraying. At present, it is still mainly applied manually using a long rod to tie a fiber cloth to dip the paint. The biggest disadvantage of this method is that it cannot stably guarantee the quality of the coating process. Due to the uncertainty of manual coating in controlling the coating thickness and coating position accuracy, it is easy to cause the coating to sag and the coating uniformity to be low.

[0003] The application and development of Fluent has reduced the research workload and computer hardware requirements. Fluent's two-phase flow simulation principle can be used as an effective way and basis for optimizing the calculation process and changing the key parameters of vector coating. It can reduce a large amount of fluid experimental investment and overcome the limitations of vector coating device experiments.

[0004] However, how to determine the relationship between the types of coating parameters and the coating effects, accurately obtain the unclear parameters affecting vector coating, and the difficulty in observing the effects of vector coating are issues that need to be solved urgently. Summary of the Invention

[0005] The technical problem solved by the present invention is to overcome the deficiencies of the prior art and provide a method and device for simulating the vector coating of high-viscosity fluids.

[0006] The technical solution of the present invention is:

[0007] In a first aspect, an embodiment of the present invention provides a method for simulating vector coating of a high-viscosity fluid, comprising:

[0008] Establish the geometric model of the effective area of ​​vector coating corresponding to the solid fuel tank;

[0009] Performing mesh division on the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model;

[0010] Importing the structured grid and the unstructured grid into Fluent to perform grid checking and adjust the sizes of the structured grid and the unstructured grid;

[0011] Select the multiphase flow model and enable the energy model and turbulence model;

[0012] Set the physical parameters, unit region conditions and boundary conditions corresponding to the gas phase and fluid, as well as the iteration method, step size and convergence accuracy;

[0013] According to the iterative method, the step size, and the convergence accuracy, the multiphase flow model, the energy model, and the turbulence model are used in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions, and the boundary conditions to perform iterative calculations to obtain a phase diagram, a volume fraction, and a velocity contour map;

[0014] Determining the relationship between factors affecting vector casting and the effect of vector casting based on the phase diagram, the volume fraction, and the velocity cloud diagram;

[0015] When the relationship is consistent with the actual situation, the simulation process ends.

[0016] Optionally, the geometric model includes: a fluid domain dominated by air phase, a fluid domain of a compressed air outlet, and a fluid domain of a high-viscosity fluid.

[0017] Optionally, meshing the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model includes:

[0018] The geometric model is meshed by mainly using structural meshing and locally using unstructured meshing for encryption. At the outlet of the compressed air, the mesh is meshed by using the locally encrypted unstructured meshing method to obtain the structural mesh and unstructured mesh of the geometric model.

[0019] Optionally, the boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated by the rotation speed of the coating device, a fluid domain boundary being a pressure outlet, and an outlet pressure being atmospheric pressure.

[0020] Optionally, after determining the relationship between the factors affecting the vector casting and the vector casting effect based on the phase diagram, the volume fraction and the velocity cloud diagram, the method further includes:

[0021] In the case that the relationship does not conform to the actual situation, the meshing of the geometric model is iteratively performed to obtain the structured mesh and the unstructured mesh of the geometric model, until the step of determining the relationship between the factors affecting the vector casting and the vector casting effect based on the phase diagram, the volume fraction and the velocity cloud map.

[0022] In a second aspect, an embodiment of the present invention provides a device for simulating vector coating of a high-viscosity fluid, comprising:

[0023] A geometric model building module is used to build a geometric model of the effective area of ​​the vector coating corresponding to the solid fuel tank;

[0024] A grid acquisition module, configured to perform grid division on the geometric model to obtain a structured grid and an unstructured grid of the geometric model;

[0025] A grid size adjustment module, used for importing the structured grid and the unstructured grid into Fluent to perform grid inspection and adjust the sizes of the structured grid and the unstructured grid;

[0026] Multiphase flow model selection module, used to select the multiphase flow model and enable the energy model and turbulence model;

[0027] Parameter setting module, used to set the physical parameters of the gas phase and fluid, unit area conditions and boundary conditions, as well as iteration method, step size and convergence accuracy;

[0028] a phase diagram acquisition module, configured to perform iterative calculations based on the iterative method, the step size, and the convergence accuracy using the multiphase flow model, the energy model, and the turbulence model in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions, and the boundary conditions to obtain a phase diagram, a volume fraction, and a velocity contour map;

[0029] a relationship determination module, configured to determine the relationship between factors influencing vector casting and the effect of vector casting based on the phase diagram, the volume fraction, and the velocity cloud diagram;

[0030] The simulation process ending module is used to end the simulation process when the relationship is consistent with the actual situation.

[0031] Optionally, the geometric model includes: a fluid domain dominated by air phase, a fluid domain of a compressed air outlet, and a fluid domain of a high-viscosity fluid.

[0032] Optionally, the grid acquisition module includes:

[0033] The grid acquisition unit is used to grid the geometric model by adopting a method of mainly using structural grid division and locally using unstructured grid encryption, and to grid the compressed air outlet position by adopting a locally encrypted unstructured grid division method to obtain the structural grid and unstructured grid of the geometric model.

[0034] Optionally, the boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated by the rotation speed of the coating device, a fluid domain boundary being a pressure outlet, and an outlet pressure being atmospheric pressure.

[0035] Optionally, the device further comprises:

[0036] An iterative execution module is used to iteratively execute the grid acquisition module, the grid size adjustment module, the multiphase flow model selection module, the parameter setting module, the phase diagram acquisition module and the relationship determination module when the relationship does not conform to the actual situation.

[0037] The advantages of the present invention compared with the prior art are:

[0038] The embodiments of the present invention provide a method for simulating the vector coating of high-viscosity fluids, establish physical models for different vector coating scenarios, obtain corresponding coating effects by adjusting relevant influencing parameters, obtain cloud maps of volume fraction, velocity vector, etc., and determine the values ​​of the vector coating parameters based on the cloud map data. A preliminary design evaluation of the vector coating device is obtained, the relationship between each influencing parameter and the vector coating effect is determined, and the coating atomization conditions of different vector coating scenarios are observed in advance, which can significantly reduce experimental costs and time. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of the steps of a method for simulating vector coating of a high-viscosity fluid provided by an embodiment of the present invention;

[0040] Figure 2 A schematic diagram of two-dimensional grid division of a vector-cast fluid domain provided by an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of setting conditions for a two-phase flow model provided in an embodiment of the present invention;

[0042] Figure 4 A schematic structural diagram of a device for simulating vector coating of high-viscosity fluids provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] Example 1

[0044] Reference Figure 1 , shows a flowchart of the steps of a method for simulating vector coating of high viscosity fluid provided by an embodiment of the present invention, such as Figure 1 As shown, the method may include the following steps:

[0045] Step 101: Establish a geometric model of the effective area of ​​vector coating corresponding to the solid fuel tank.

[0046] In an embodiment of the present invention, the vector coating effects under different conditions such as compressed air ring, vector baffle, and coating head speed can be simulated by a two-phase flow method, and the relationship between the type of coating parameters and the coating effect is determined, thereby solving the problem of unclear vector coating influencing parameters and difficult observation of vector coating effects.

[0047] First, a geometric model of the effective area for vector coating corresponding to the solid fuel tank can be established. Specifically, a geometric model of the fluid domain for high-viscosity fluid vector coating can be established in Creo 3D software. The geometry can then be adjusted in ANSYS Workbench, allowing ANSYS Workbench to repair the regional geometry and process details, thereby obtaining a geometric model of the effective area for vector coating. The geometric model can include three regions: the fluid domain dominated by the air phase, the fluid domain of the compressed air outlet, and the fluid domain of the high-viscosity fluid.

[0048] After the geometric model of the effective area of ​​the vector coating corresponding to the solid fuel tank is established, step 102 is executed.

[0049] Step 102: Meshing the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model.

[0050] After establishing the geometric model of the effective area of ​​the vector coating corresponding to the solid fuel tank, the constructed geometric model can be meshed to obtain the structured mesh and unstructured mesh of the geometric model. Specifically, the geometric model can be meshed by using the structured mesh for the main body and the unstructured mesh for local encryption, and the mesh can be meshed by using the locally encrypted unstructured mesh at the outlet of the compressed air to obtain the structured mesh and unstructured mesh of the geometric model. By using the locally encrypted unstructured mesh, the calculation speed can be improved while ensuring the mesh quality, such as Figure 2 shown.

[0051] In a specific implementation, after the geometric model is constructed, the constructed model can be imported into the meshing software ICEM CFD to divide the boundary of the geometric model and generate the computational domain mesh.

[0052] After meshing the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model, step 103 is executed.

[0053] Step 103: Import the structured grid and the unstructured grid into Fluent to perform grid inspection and adjust the sizes of the structured grid and the unstructured grid.

[0054] After meshing the geometry to obtain the structured and unstructured meshes, you can import the structured and unstructured meshes into Fluent for mesh checking and mesh size adjustment. Specifically, you can convert the structured and unstructured meshes into Fluent, import them into Fluent, check the meshes, adjust the mesh size ratio, and set the solver. This check includes verifying that the meshing has no negative volumes, adjusting the mesh size to millimeters, and selecting a pressure-based solver.

[0055] In practical applications, the iterative calculation of structured grids converges quickly, but the accuracy is not as high as that of unstructured grids. Unstructured grids are used for encryption in areas where local accuracy is required to increase accuracy, but the convergence speed is slow and the calculation amount is large. Therefore, local unstructured grid encryption is used.

[0056] After the structured grid and the unstructured grid are imported into Fluent for grid checking and the sizes of the structured grid and the unstructured grid are adjusted, step 104 is executed.

[0057] Step 104: Select the multiphase flow model and enable the energy model and turbulence model.

[0058] In this embodiment, after completing the grid division and the corresponding size adjustment, you can select the two-phase flow model, determine that the main phase is air and the secondary phase is a high-viscosity fluid, and enable physical models such as the energy model and turbulence model. Figure 3 As shown, in the physical model definition interface, select the Euler multiphase flow model, the number of phases is 2, the energy model is turned on, and the turbulence model selects the Realizable k-ε model.

[0059] After the multiphase flow model is selected and the energy model and the turbulence model are enabled, step 105 is executed.

[0060] Step 105: Set the physical parameters, unit region conditions and boundary conditions corresponding to the gas phase and fluid, as well as the iteration method, step size and convergence accuracy.

[0061] After selecting the multiphase flow model and enabling the energy and turbulence models, you can set the physical parameters, cell region conditions, and boundary conditions for the gas and fluid phases, as well as the iteration method, step size, and convergence accuracy. In this example, the boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated from the coating device speed, a pressure outlet at the fluid domain boundary, and atmospheric pressure at the outlet.

[0062] In a specific implementation, the physical parameters of the gas phase and the fluid phase of the two-phase flow are set, wherein air is the main phase and the high-viscosity liquid is the secondary phase. The parameters of the gas-liquid two-phase include density and dynamic viscosity.

[0063] After that, set the iteration method, step size and convergence accuracy, set the maximum number of iterations to 20 times, the step size to 0.0001s, and the number of steps to 50,000 steps.

[0064] After setting the physical parameters corresponding to the gas phase and fluid, the unit region conditions and boundary conditions, as well as the iteration method, step size and convergence accuracy, step 106 is executed.

[0065] Step 106: According to the iterative method, the step size and the convergence accuracy, the multiphase flow model, the energy model and the turbulence model are used in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions and the boundary conditions to perform iterative calculations to obtain a phase diagram, a volume fraction and a velocity cloud diagram.

[0066] After setting the relevant parameters, iterative calculations can be performed using the multiphase flow model, energy model, and turbulence model in combination with the structured and unstructured grids, physical parameters, cell area conditions, and boundary conditions, based on the iteration method, step size, and convergence accuracy, to obtain phase diagrams, volume fractions, and velocity contours. Specifically, iterative calculations can be performed based on the initialized flow field. After convergence, the results are processed to obtain pressure distribution contours, velocity distribution contours, and simulated phase diagrams.

[0067] After obtaining the phase diagram, the reference score, and the velocity cloud diagram, step 107 is executed.

[0068] Step 107: Based on the phase diagram, the volume fraction, and the velocity contour diagram, determine the relationship between the factors affecting the vector casting and the vector casting effect.

[0069] After obtaining the phase diagram, volume fraction, and velocity cloud map, the relationship between the factors affecting vector casting and the effect of vector casting can be determined based on the phase diagram, volume fraction, and velocity cloud map. That is, the relationship between the factors affecting vector casting and the effect of vector casting can be obtained by comparing the data of multiple sets of cloud maps.

[0070] After the relationship between the image vector casting factor and the vector casting effect is determined based on the phase diagram, the volume fraction, and the velocity cloud diagram, step 108 is executed.

[0071] Step 108: When the relationship is consistent with the actual situation, the simulation process ends.

[0072] After determining the relationship between the image vector coating factor and the vector coating effect based on the phase diagram, volume fraction and velocity cloud diagram, the relationship between the image vector coating factor and the vector coating effect is the simulation result. At this time, the simulation result can be compared with the actual result. If the simulation result is consistent with the actual result, the simulation process can be ended. Otherwise, the geometric model can be modified and steps 102 to 107 can be iteratively executed until the simulation result is consistent with the actual result.

[0073] The embodiment of the present invention is the first fluid simulation method to solve the vector coating effect of high-viscosity fluid. It obtains the parameters affecting vector coating, such as the spinning head rotation speed, the spinning head outlet size, the compressed air ring pressure and the dynamic viscosity of the coating, by a two-phase flow method. It can significantly reduce the cost and time spent on structural design, parameter selection and experimental equipment of the vector coating device.

[0074] Example 2

[0075] Reference Figure 4 , shows a schematic structural diagram of a device for simulating high-viscosity fluid vector coating provided by an embodiment of the present invention, such as Figure 4 As shown, the device may include the following modules:

[0076] A geometric model building module 410 is used to build a geometric model of the effective area of ​​the vector coating corresponding to the solid fuel tank;

[0077] A grid acquisition module 420 is used to perform grid division on the geometric model to obtain a structured grid and an unstructured grid of the geometric model;

[0078] A grid size adjustment module 430 is used to import the structured grid and the unstructured grid into Fluent to perform grid inspection and adjust the size of the structured grid and the unstructured grid;

[0079] The multiphase flow model selection module 440 is used to select a multiphase flow model and enable an energy model and a turbulence model;

[0080] Parameter setting module 450, used to set the physical parameters corresponding to the gas phase and fluid, unit region conditions and boundary conditions, as well as the iteration method, step size and convergence accuracy;

[0081] a phase diagram acquisition module 460 for performing iterative calculations based on the iterative method, the step size, and the convergence accuracy using the multiphase flow model, the energy model, and the turbulence model in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions, and the boundary conditions to obtain a phase diagram, a volume fraction, and a velocity contour map;

[0082] A relationship determination module 470 is configured to determine a relationship between factors affecting vector casting and an effect of vector casting based on the phase diagram, the volume fraction, and the velocity contour map;

[0083] The simulation process ending module 480 is used to end the simulation process when the relationship is consistent with the actual situation.

[0084] Optionally, the geometric model includes: a fluid domain dominated by air phase, a fluid domain of a compressed air outlet, and a fluid domain of a high-viscosity fluid.

[0085] Optionally, the grid acquisition module includes:

[0086] The grid acquisition unit is used to grid the geometric model by adopting a method of mainly using structural grid division and locally using unstructured grid encryption, and to grid the compressed air outlet position by adopting a locally encrypted unstructured grid division method to obtain the structural grid and unstructured grid of the geometric model.

[0087] Optionally, the boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated by the rotation speed of the coating device, a fluid domain boundary being a pressure outlet, and an outlet pressure being atmospheric pressure.

[0088] Optionally, the device further comprises:

[0089] An iterative execution module is used to iteratively execute the grid acquisition module, the grid size adjustment module, the multiphase flow model selection module, the parameter setting module, the phase diagram acquisition module and the relationship determination module when the relationship does not conform to the actual situation.

[0090] The specific embodiments described in this application can help those skilled in the art to more fully understand this application, but do not limit this application in any way. Therefore, those skilled in the art should understand that this application can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and technical essence of this application should be included in the scope of protection of the patent application.

[0091] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for simulating the vector coating of a high-viscosity fluid, characterized in that: include: Establish the geometric model of the effective area of ​​vector coating corresponding to the solid fuel tank; Performing mesh division on the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model; Importing the structured grid and the unstructured grid into Fluent to perform grid checking and adjust the sizes of the structured grid and the unstructured grid; Select the multiphase flow model and enable the energy model and turbulence model; Set the physical parameters, unit region conditions and boundary conditions corresponding to the gas phase and fluid, as well as the iteration method, step size and convergence accuracy; According to the iterative method, the step size, and the convergence accuracy, the multiphase flow model, the energy model, and the turbulence model are used in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions, and the boundary conditions to perform iterative calculations to obtain a phase diagram, a volume fraction, and a velocity contour map; Determining the relationship between factors affecting vector casting and the effect of vector casting based on the phase diagram, the volume fraction, and the velocity cloud diagram; When the relationship is consistent with the actual situation, the simulation process ends.

2. The method according to claim 1, characterized in that The geometric model includes: a fluid domain dominated by air phase, a fluid domain of a compressed air outlet, and a fluid domain of a high-viscosity fluid.

3. The method according to claim 1, characterized in that The meshing of the geometric model to obtain a structured mesh and an unstructured mesh of the geometric model includes: The geometric model is meshed by mainly using structural meshing and locally using unstructured meshing for encryption. At the outlet of the compressed air, the mesh is meshed by using the locally encrypted unstructured meshing method to obtain the structural mesh and unstructured mesh of the geometric model.

4. The method according to claim 1, wherein The boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated by the rotation speed of the coating device, a fluid domain boundary as a pressure outlet, and an outlet pressure as atmospheric pressure.

5. The method according to claim 1, wherein After determining the relationship between the factors affecting the vector casting and the vector casting effect based on the phase diagram, the volume fraction and the velocity cloud diagram, the method further includes: In the case that the relationship does not conform to the actual situation, the meshing of the geometric model is iteratively performed to obtain the structured mesh and the unstructured mesh of the geometric model, until the step of determining the relationship between the factors affecting the vector casting and the vector casting effect based on the phase diagram, the volume fraction and the velocity cloud map.

6. A device for simulating the vector coating of high-viscosity fluids, characterized in that: include: A geometric model building module is used to build a geometric model of the effective area of ​​the vector coating corresponding to the solid fuel tank; A grid acquisition module, configured to perform grid division on the geometric model to obtain a structured grid and an unstructured grid of the geometric model; A grid size adjustment module, used for importing the structured grid and the unstructured grid into Fluent to perform grid inspection and adjust the sizes of the structured grid and the unstructured grid; Multiphase flow model selection module, used to select the multiphase flow model and enable the energy model and turbulence model; Parameter setting module, used to set the physical parameters of the gas phase and fluid, unit area conditions and boundary conditions, as well as iteration method, step size and convergence accuracy; a phase diagram acquisition module, configured to perform iterative calculations based on the iterative method, the step size, and the convergence accuracy using the multiphase flow model, the energy model, and the turbulence model in combination with the structured grid, the unstructured grid, the physical parameters, the unit area conditions, and the boundary conditions to obtain a phase diagram, a volume fraction, and a velocity contour map; a relationship determination module, configured to determine the relationship between factors influencing vector casting and the effect of vector casting based on the phase diagram, the volume fraction, and the velocity cloud diagram; The simulation process ending module is used to end the simulation process when the relationship is consistent with the actual situation.

7. The device according to claim 6, characterized in that The geometric model includes: a fluid domain dominated by air phase, a fluid domain of a compressed air outlet, and a fluid domain of a high-viscosity fluid.

8. The device according to claim 6, characterized in that The grid acquisition module includes: The grid acquisition unit is used to grid the geometric model by adopting a method of mainly using structural grid division and locally using unstructured grid encryption, and to grid the compressed air outlet position by adopting a locally encrypted unstructured grid division method to obtain the structural grid and unstructured grid of the geometric model.

9. The device according to claim 6, characterized in that The boundary conditions include: a gas phase pressure inlet, a liquid phase velocity inlet calculated by the rotation speed of the coating device, a fluid domain boundary as a pressure outlet, and an outlet pressure as atmospheric pressure.

10. The device according to claim 6, characterized in that The device further comprises: An iterative execution module is used to iteratively execute the grid acquisition module, the grid size adjustment module, the multiphase flow model selection module, the parameter setting module, the phase diagram acquisition module and the relationship determination module when the relationship does not conform to the actual situation.

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