A portable large-cavity temperature and humidity generator optimization method based on CFD

Abstract

The application discloses a portable large-cavity temperature and humidity generator optimization method based on CFD. The method is used for optimizing and designing a temperature and humidity generator in a combined mode of experimental test and simulation calculation. In the method, a fluid dynamics equation set is introduced to describe temperature and humidity flow field variation rules inside a cavity of the temperature and humidity generator to be optimized. A coupling relationship between the fluid dynamics equation set and heat transfer equations and water transport and diffusion equations is established through physical quantities such as density and viscosity. The temperature and humidity field distribution inside the cavity of the temperature and humidity generator to be optimized can be realized through arranging a small number of temperature and humidity sensors inside the cavity of the actual temperature and humidity generator to be optimized and combining a multi-physical field coupling model. Finally, the simulation result is used for guiding the optimization design of the temperature and humidity generator, so that the development cost of the portable large-cavity temperature and humidity generator is reduced, resource waste is avoided, and the development efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of measurement systems for measuring physical quantities, and particularly relates to an optimization method for a portable large-cavity temperature and humidity generator based on CFD. Background Technology

[0002] According to the requirements of JJF (Military Industry) 165-2017 "Calibration Specification for Digital Thermohygrometers" and other regulations, various thermometers and hygrometers need to be regularly calibrated. Therefore, a stable and controllable temperature and humidity calibration environment is necessary. Temperature and humidity generators are the main equipment for calibrating thermometers and hygrometers in the laboratory.

[0003] Currently, the technology for standard temperature and humidity generators used in laboratories both domestically and internationally has matured. Temperature and humidity standard chambers used in laboratories of various metrology institutions mainly generate constant and uniform temperature and humidity fields through dual-temperature methods and temperature and humidity adjustment methods. In recent years, the demand for portable temperature and humidity generators has also increased rapidly. Domestic researchers have developed various portable temperature and humidity control boxes using different principles and methods, such as independent temperature and humidity control and water circulation, efficient gas-liquid heat exchange, and multi-cavity internal permeation methods using a three-way gas distribution system with solenoid valves. However, the test chambers of the above-mentioned temperature and humidity generators are relatively small and cannot meet practical needs. Therefore, it is necessary to develop portable temperature generators with larger chambers.

[0004] When developing a large-cavity portable temperature and humidity generator, it is necessary to test the temperature and humidity distribution inside the cavity. The existing method is to directly test the temperature and humidity distribution inside the cavity after the initial design of the large-cavity portable temperature generator is completed. This method requires the selection of a large number of sample points for testing, and the number of sample points increases exponentially with the accuracy requirements. This will lead to a sharp increase in the cost and difficulty of the experiment and generator design. Summary of the Invention

[0005] In view of this, this application proposes a CFD-based optimization method for a portable large-cavity temperature and humidity generator. This method combines experimental testing with simulation calculations to optimize the design of the temperature and humidity generator. The method introduces fluid dynamics equations to describe the temperature and humidity flow field changes inside the cavity. It establishes the coupling relationship between the fluid dynamics equations and the heat transfer and moisture transport and diffusion equations using physical quantities such as density and viscosity. By arranging a small number of temperature and humidity sensors inside the temperature and humidity generator cavity and combining them with a multiphysics coupling model, the temperature and humidity field distribution inside the cavity can be monitored. The simulation results guide the optimization design of the temperature and humidity generator, improving the development efficiency of a portable large-cavity high-efficiency temperature and humidity generator and avoiding resource waste.

[0006] To achieve this objective, the present invention adopts the following technical solution: an optimization method for a portable large-cavity temperature and humidity generator based on CFD, the method comprising:

[0007] S1: Establish a three-dimensional multiphysics coupling model based on non-isothermal flow and moisture transport based on the temperature and humidity generator to be optimized;

[0008] S2: Mesh the above three-dimensional multiphysics coupling model and set the material property parameters;

[0009] S3: Determine the boundary conditions and initial conditions for the finite element analysis of the above multiphysics coupling model;

[0010] S4: Simulation calculations yielded transient distribution curves of temperature and relative humidity of the temperature and humidity generator to be optimized at different times;

[0011] S5: Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized through experimental measurements. Use the measured curves and the distribution curves obtained from the simulation in S4 to verify and optimize the three-dimensional multiphysics coupling model of the temperature and humidity generator to be optimized.

[0012] S6: Utilize the three-dimensional multiphysics coupling model finally optimized in S5 to optimize the design of the temperature and humidity generator, and obtain the optimal combination of design parameters for the temperature and humidity generator that meets the technical requirements.

[0013] Preferably, S1 includes:

[0014] S11: Establish a three-dimensional structural model of the temperature and humidity generator to be optimized in COMSOL Multiphysics software. The size of the three-dimensional structural model is 1 / 2 of the temperature and humidity generator to be optimized.

[0015] S12: Couple the k-ε turbulence model, solid and fluid heat transfer model and air moisture transport model to the three-dimensional structural model in S11 as solvers, and couple the MRES algorithm as the solution algorithm to obtain the three-dimensional multiphysics coupled model of the temperature and humidity generator to be optimized.

[0016] Preferably, the mesh division in S2 is as follows:

[0017] S2-1: Automatically generate a polyhedral mesh from the three-dimensional multiphysics coupling model in S1, and set the mesh size to Size;

[0018] S2-2: Set the boundary between air and solid in the three-dimensional multiphysics coupling model as a boundary layer mesh, and refine the boundary layer mesh at the angle, setting the split angle to J;

[0019] S2-3: Further refine the mesh of each local structure in the three-dimensional multiphysics coupling model, and set the mesh size to Size1;

[0020] S2-4: Verify the divided mesh to determine if the mesh division is qualified. If it is not qualified, the mesh needs to be further refined until it is qualified.

[0021] Preferably, in S2-4, the condition for judging the mesh division as qualified is: under the boundary condition, when the change in the air Nusselt number on the inner wall of the cavity of the temperature and humidity generator to be optimized is less than 1%, the mesh division is considered qualified.

[0022] Preferably, the material properties in S2 are: the materials of each local structure of the temperature and humidity generator, as well as the material's density, dynamic viscosity, thermal conductivity, and constant pressure heat capacity.

[0023] Preferably, the boundary conditions in S3 include, but are not limited to: natural convection heat transfer boundary conditions, fluid-structure interaction boundary conditions, open boundary conditions, and adiabatic boundary conditions;

[0024] Initial conditions include: ambient temperature T amb The air velocity at the inlet of the temperature and humidity generator to be optimized is v0, the air temperature at the inlet is Tf, the relative humidity at the inlet is RH, and the final relative humidity RHf specified by the temperature and humidity generator is RHf.

[0025] Preferably, the process of calculating the transient distribution of temperature and relative humidity in step S4 includes:

[0026] S41: Based on the design specifications of the temperature and humidity generator to be optimized, the heat source function of its temperature control module should be provided:

[0027]

[0028] In the formula, t is time, in minutes, and T heat This is the temperature of the heat source, and its value depends on the power supply.

[0029] S42: Calculate the steady-state solution of the k-ε turbulence model using the heat source function, and set the steady-state solution of the velocity field of the k-ε turbulence model as the velocity field in the solid and fluid heat transfer in the three-dimensional multiphysics coupling model and the velocity field in the air moisture transport model, respectively.

[0030] S43: Set all other parameters in the three-dimensional multiphysics coupling model to be the same as those of the temperature and humidity generator to be optimized, and use the set model to calculate the simulated temperature and relative humidity transient distribution of the temperature and humidity generator to be optimized at different times.

[0031] Preferably, S5 includes:

[0032] S51: Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized. Set 15 sets of temperature and relative humidity detection points in the temperature and humidity generator to be optimized. Each set of tests lasts for 60 minutes, with a test interval of 1 minute. Fix 4 wireless temperature and humidity sensors at different locations in the test chamber of the temperature and humidity generator. Test and record the data of the 4 wireless temperature and humidity sensors every 1 minute to obtain 4 temperature curves and 4 relative humidity measured curves at different times.

[0033] S52: Calculate the average relative error and correlation coefficient between the measured temperature and relative humidity curves and the corresponding simulation curves, and determine whether the calculation results of the simulation model are valid. If invalid, the three-dimensional multiphysics coupling model needs to be further optimized until the model is valid. If valid, the model is used to optimize the design of the temperature and humidity generator.

[0034] Preferably, S6 includes:

[0035] S61: Change some parameters of the temperature and humidity generator to be optimized;

[0036] S62: Calculate the time required for uniform temperature and humidity distribution in the test room of the temperature and humidity generator to be optimized under different parameters using parametric scanning;

[0037] S63: Based on the optimal response time, obtain the best combination of design parameters for the temperature and humidity generator to be optimized, which meets the technical requirements.

[0038] Preferably, the parameters include the length l and height h of the test chamber of the temperature and humidity generator to be optimized, the air velocity at the air inlet v0, and the velocity v0 of the internal circulating fan.

[0039] The beneficial effects of this invention are: This invention proposes for the first time an optimization method for portable large-cavity humidity generators based on CFD. This method reduces the development cost of portable large-cavity temperature and humidity generators and improves their development efficiency by combining simulation calculations and experimental tests. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating the optimization method for a portable large-cavity humidity generator based on CFD according to an embodiment of this application.

[0041] Figure 2 This is a schematic diagram of the portable large-cavity humidity generator to be optimized in the embodiments of this application;

[0042] In the diagram: 1. Base 2. Side panel 3. Air inlet 4. Air inlet duct 5. Air outlet 6. Cavity 7. Upper shell 8. Test chamber 9. Baffle 10. Small column array 11. Bottom panel 12. Circulation chamber 13. Internal circulation fan 14. Internal heat transfer grid 15. Internal heat-conducting metal base 16. Temperature control module 17. External heat-conducting metal base 18. External heat transfer grid 19. External circulation fan. Detailed Implementation

[0043] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

[0044] The CFD-based optimization method for portable large-cavity humidity generators proposed in this application mainly describes the temperature-humidity flow field variation law inside the cavity by introducing a set of fluid dynamics equations. The coupling relationship between the set of fluid dynamics equations and the heat transfer equation and the moisture transport and diffusion equation is established by using physical quantities such as density and viscosity. Then, by arranging a small number of temperature and humidity sensors inside the cavity and combining them with a multiphysics coupling model, the temperature and humidity field distribution inside the cavity can be monitored. The simulation results are used to guide the optimization design of the temperature and humidity generator, which improves the development efficiency of portable large-cavity high-efficiency temperature and humidity generators and avoids resource waste.

[0045] The following is in conjunction with the appendix Figures 1-2 The present invention provides a detailed description of the optimization method for the portable large-cavity humidity generator, along with specific embodiments.

[0046] Example

[0047] like Figure 1 As shown, the method includes the following steps:

[0048] Step 1: Establish a three-dimensional multiphysics coupling model based on non-isothermal flow and moisture transport for the temperature and humidity generator to be optimized;

[0049] To illustrate the method of this application in detail, as an example, in conjunction with... Figure 2 The structure of the temperature and humidity generator to be optimized is described below. The temperature and humidity generator includes: a base 1, a cavity 6, and a side panel 2 connecting the base 1 and the cavity 6. The cavity 6 includes a test chamber 8 and a circulation chamber 12. The test chamber 8 and the cavity 6 share an upper shell 7. The circulation chamber 12 is formed by gaps between the three sides and the bottom of the test chamber 8 and the three sides and the bottom of the upper shell 7.

[0050] The cavity 6 has an air inlet 3 and an air outlet 5 on its side. The air inlet 3 extends into the circulation cavity 12 through the air inlet duct 4 connected to it. Both sides of the test cavity 8 are equipped with baffles 9 with perforated structures. The bottom panel 11 of the test cavity 8 is equipped with a small column array 10 for placing the sample to be tested. The bottom panel 11 of the test cavity 8 has an opening in the middle. The internal circulation fan 13, internal heat transfer grid 14, internal heat-conducting metal base 15, temperature control module 16, external heat-conducting metal base 17, external heat transfer grid 18 and external circulation fan 19 are installed sequentially from top to bottom. The internal circulation fan 13, internal heat transfer grid 14, internal heat-conducting metal base 15 and temperature control module 16 are located inside the test cavity 8, while the external heat-conducting metal base 17, external heat transfer grid 18 and external circulation fan 19 are located inside the circulation cavity 12.

[0051] The materials and structural parameters of the aforementioned local structures of the temperature and humidity generator to be optimized are as follows: the base 1 and the side panel 2 are made of iron plate; the flow velocity at the air inlet 3 is v. in m / s; the air inlet duct 4 is an epoxy resin round tube with an inner diameter of 2mm; the outer shell of the cavity 6 is composed of an inner layer of 2mm thick epoxy resin and an outer layer of 15mm thick heat-insulating foam; the upper shell 7 of the cavity 6 is provided with a transparent observation round hole; the baffle 9 is made of epoxy resin and has uniformly distributed 38mm×8mm rounded rectangular holes; the column array 10 for placing the sample to be tested is a 10×10 array combination formed by epoxy resin cylinders with a radius of 1.5mm and a height of 15mm; the bottom panel 11 of the test chamber 8 is made of epoxy resin material with a thickness of 2mm; the internal circulating fan 13 flows upward in the normal direction with a flow rate of v0m / s; the internal heat transfer grid 14, the internal heat-conducting metal base 15, the external heat-conducting metal base 17 and the external heat transfer grid 18 are made of copper; the temperature control module 16 is a cascade semiconductor temperature control element; the external circulating fan 19 flows downward in the normal direction with a flow rate of v1m / s.

[0052] In this step, the COMSOL Multiphysics software is first used to establish a three-dimensional structural model of the temperature and humidity generator to be optimized. The size of the three-dimensional structural model is reduced by 1 / 2 compared to the actual temperature and humidity generator.

[0053] Next, the k-ε turbulence model, solid and fluid heat transfer model, and air moisture transport model are coupled onto the established three-dimensional structural model as solvers, and the MRES algorithm is coupled as the solution algorithm to obtain the three-dimensional multiphysics coupled model of the temperature and humidity generator to be optimized.

[0054] Step 2: Mesh the above three-dimensional multiphysics coupling model and set the material property parameters;

[0055] First, based on the materials of each local structure of the temperature and humidity generator to be optimized given in the previous step, set the material properties and parameters of each local structure in the three-dimensional multiphysics coupling model, including: density, dynamic viscosity, thermal conductivity and constant pressure heat capacity.

[0056] Next, mesh generation is performed: (1) The three-dimensional multiphysics coupling model is automatically generated into a polyhedral mesh, and the mesh size is set to Size. In this embodiment, it is 1.4 < Size ≤ 18, and the unit is mm; (2) The boundary part between air and solid in the three-dimensional multiphysics coupling model is set as a boundary layer mesh, and the boundary layer mesh is refined at the angle. The splitting angle is set to J. In this embodiment, it is 50° < J ≤ 240°; (3) The mesh of each local structure in the three-dimensional multiphysics coupling model is further refined. The mesh size of the further refined mesh is set to Size1, and 0.5 < Size1 ≤ 7.8, and the unit is mm; (4) The mesh after division is verified. Under the condition of boundary value, if the change of the air Nusselt number on the inner wall of the cavity 6 of the temperature and humidity generator to be optimized is less than 1%, the mesh generation is considered qualified. If it is not qualified, the mesh needs to be further refined until it is qualified.

[0057] Step 3: Determine the boundary conditions and initial conditions for the finite element analysis of the above multiphysics coupling model;

[0058] The boundary conditions here include: the surface of the side panel 2 is set as a natural convection heat transfer boundary condition; the exterior of the air inlet duct 4, the interior of the side of the cavity 6, the bottom of the upper shell 7, the test chamber 8, the surface of the baffle 9, the small column array 10, the bottom panel 11, the interior of the circulation chamber 12, the internal heat transfer grid 14, the internal heat-conducting metal base 15, the external heat-conducting metal base 17, the external heat transfer grid 18, and the surface of the external circulation fan 19 are set as fluid-structure interaction boundary conditions; the air outlet 5 is set as a pressure outlet boundary condition; the left and right sides of the lower part of the circulation chamber 12 are set as open boundaries; and the remaining surfaces are set as adiabatic boundary conditions.

[0059] Initial conditions include: ambient temperature T amb The air velocity at the air inlet 3 of the temperature and humidity generator to be optimized is v0, the air temperature at the air inlet 3 is Tf, the relative humidity at the air inlet 3 is RH, and the final relative humidity RHf specified by the temperature and humidity generator is RHf.

[0060] Step 4: Simulation calculations are used to obtain the transient distribution curves of temperature and relative humidity of the temperature and humidity generator to be optimized at different times. The process is as follows:

[0061] (1) Based on the design specifications of the temperature and humidity generator to be optimized, the heat source function of its temperature control module should be given:

[0062]

[0063] In the formula, t is time, in minutes, and T heat This is the temperature of the heat source, and its value depends on the power supply.

[0064] (2) The steady-state solution of the k-ε turbulence model is calculated using the heat source function, and the steady-state solution of the velocity field of the k-ε turbulence model is set as the velocity field in the solid and fluid heat transfer in the three-dimensional multiphysics coupling model and the velocity field in the air moisture transport model, respectively.

[0065] (3) Set all other parameters in the three-dimensional multiphysics coupling model to be the same as those of the temperature and humidity generator to be optimized, and calculate the transient distribution curves of the simulated temperature and relative humidity of the temperature and humidity generator to be optimized at different times.

[0066] Step 5: Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized through experiments. Using the measured curves and the transient temperature and relative humidity distributions obtained from the simulation in S4, optimize the three-dimensional multiphysics coupling model of the temperature and humidity generator to be optimized. The specific process is as follows:

[0067] (1) Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized.

[0068] Fifteen sets of temperature and relative humidity detection points were set in the temperature and humidity generator to be optimized. Each set of tests lasted for 60 minutes, with a test interval of 1 minute. Four wireless temperature and humidity sensors were fixedly installed at different locations in the test chamber of the temperature and humidity generator. The data of the four wireless temperature and humidity sensors were tested and recorded every 1 minute to obtain four temperature curves and four relative humidity curves at different times.

[0069] (2) Calculate the average relative error and correlation coefficient between the measured temperature and relative humidity curves and the corresponding simulation curves, and determine whether the calculation results of the simulation model are valid. If the average relative error is less than 5% and the correlation coefficient is greater than 0.8, the calculation results of the simulation model are considered valid. Otherwise, the parameters of the three-dimensional multiphysics coupling model need to be further optimized.

[0070] Step 6: Using the optimized three-dimensional multiphysics coupling model of the temperature and humidity generator obtained in Step 5, the temperature and humidity generator is optimized to obtain the best combination of design parameters that can meet the technical requirements. The process is as follows:

[0071] (1) Change some parameters of the test chamber 8 of the temperature and humidity generator to be optimized, such as the length l and height h, the air velocity of the air inlet 3, and the velocity v0 of the internal circulating fan 13.

[0072] (2) Calculate the time for uniform temperature and humidity distribution in the test room of the temperature and humidity generator to be optimized under different parameters using parametric scanning;

[0073] (3) Based on the optimal response time, the best combination of design parameters for the temperature and humidity generator to be optimized that meets the technical requirements is obtained.

Claims

1. A method for optimizing a portable large-cavity temperature and humidity generator based on CFD, characterized in that, The method includes: S1: Establish a three-dimensional multiphysics coupling model based on non-isothermal flow and moisture transport based on the temperature and humidity generator to be optimized; S2: Mesh the above three-dimensional multiphysics coupling model and set the material property parameters; S3: Determine the boundary conditions and initial conditions for the finite element analysis of the above multiphysics coupling model; S4: Simulation calculations yielded transient distribution curves of temperature and relative humidity of the temperature and humidity generator to be optimized at different times; S5: Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized through experimental measurements. Use the measured curves and the distribution curves obtained from the simulation in S4 to verify and optimize the three-dimensional multiphysics coupling model of the temperature and humidity generator to be optimized. S6: Use the three-dimensional multiphysics coupling model finally optimized in S5 to optimize the design of the temperature and humidity generator, and obtain the best combination of design parameters for the temperature and humidity generator that can meet the technical requirements. S1 includes: S11: Establish a three-dimensional structural model of the temperature and humidity generator to be optimized in COMSOL Multiphysics software. The size of the three-dimensional structural model is 1 / 2 of the temperature and humidity generator to be optimized. S12: Coupling on the 3D structural model in S11 k - ɛ Turbulence model, solid and fluid heat transfer model and air moisture transport model are used as solvers, and coupled with GMRES algorithm as solution algorithm to obtain three-dimensional multiphysics coupled model of temperature and humidity generator to be optimized. The material properties in S2 are: the materials of each local structure of the temperature and humidity generator, as well as the material's density, dynamic viscosity, thermal conductivity, and constant pressure heat capacity; The boundary conditions in S3 include, but are not limited to: natural convection heat transfer boundary conditions, fluid-structure interaction boundary conditions, open boundary conditions, and adiabatic boundary conditions. Initial conditions include: ambient temperature T amb The airflow velocity at the inlet of the temperature and humidity generator to be optimized is: v in The air temperature at the air inlet is Tf The relative humidity of the air at the air inlet is RH and the final relative humidity specified by the temperature and humidity generator. RHf ; S6 includes: S61: Change some parameters of the temperature and humidity generator to be optimized; S62: Calculate the time required for uniform temperature and humidity distribution in the test room of the temperature and humidity generator to be optimized under different parameters using parametric scanning; S63: Based on the optimal response time, obtain the best combination of design parameters for the temperature and humidity generator to be optimized, which meets the technical requirements.

2. The optimization method for a portable large-cavity temperature and humidity generator based on CFD according to claim 1, characterized in that, The grid division in S2 is as follows: S2-1: Automatically generate a polyhedral mesh from the 3D multiphysics coupling model in S1, and set the mesh size to [value missing]. Size ; S2-2: Set the boundary between air and solid in the 3D multiphysics coupling model as a boundary layer mesh, and refine the boundary layer mesh at the angular level, setting the split angle to [value missing]. J ; S2-3: Further refine the mesh of each local structure in the 3D multiphysics coupling model, setting the mesh size to [value missing]. Size 1; S2-4: Verify the divided mesh to determine if the mesh division is qualified. If it is not qualified, the mesh needs to be further refined until it is qualified.

3. The optimization method for a portable large-cavity temperature and humidity generator based on CFD according to claim 2, characterized in that, In S2-4, the condition for judging the mesh division as qualified is: under the boundary condition, when the change of the air Nusselt number on the inner wall of the cavity of the temperature and humidity generator to be optimized is less than 1%, the mesh division is considered qualified.

4. The optimization method for a portable large-cavity temperature and humidity generator based on CFD according to claim 1, characterized in that, The process of calculating the transient distribution of temperature and relative humidity in S4 includes: S41: Based on the design specifications of the temperature and humidity generator to be optimized, provide the heat source function of its temperature control module: In the formula, t Time, in minutes. T heat This is the temperature of the heat source, and its value depends on the power supply. S42: Calculation using heat source function k - ɛ The steady-state solution of the turbulence model, and k - ɛ The steady-state solution of the velocity field of the turbulence model is set as the velocity field in the solid and fluid heat transfer in the three-dimensional multiphysics coupling model and the velocity field in the moisture transport model in the air, respectively. S43: Set all other parameters in the three-dimensional multiphysics coupling model to be the same as those of the temperature and humidity generator to be optimized, and use the set model to calculate the simulated temperature and relative humidity transient distribution of the temperature and humidity generator to be optimized at different times.

5. The optimization method for a portable large-cavity temperature and humidity generator based on CFD according to claim 1, characterized in that, S5 includes: S51: Obtain the measured temperature and humidity distribution curves of the temperature and humidity generator to be optimized. Set 15 sets of temperature and relative humidity detection points in the temperature and humidity generator to be optimized. Each set of tests lasts for 60 minutes, with a test interval of 1 minute. Fix 4 wireless temperature and humidity sensors at different locations in the test chamber of the temperature and humidity generator. Test and record the data of the 4 wireless temperature and humidity sensors every 1 minute to obtain 4 temperature curves and 4 relative humidity measured curves at different times. S52: Calculate the average relative error and correlation coefficient between the measured temperature and relative humidity curves and the corresponding simulation curves, and determine whether the calculation results of the simulation model are valid. If invalid, the three-dimensional multiphysics coupling model needs to be further optimized until the model is valid. If valid, the model is used to optimize the design of the temperature and humidity generator.

6. The optimization method for a portable large-cavity temperature and humidity generator based on CFD according to claim 1, characterized in that, The parameters include the length of the test chamber for the temperature and humidity generator to be optimized. l and height h The airflow velocity at the air inlet is v in and the airflow rate of the internal circulation fan v 0.

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