Spray cooling simulation method based on Fluent software

Abstract

The invention belongs to the technical field of thermal simulation of internal and external thermal coupling closed cabins, and particularly relates to a spray cooling simulation method based on Fluent software. The method comprises the following steps: step 1, constructing a cabin grid model; step 2, performing simulation on the cabin grid model through Fluent software to obtain a simulation result; and 3, analyzing the simulation result, and obtaining a cabin internal equipment surface temperature distribution cloud picture and a cabin outlet temperature distribution cloud picture. According to the spray cooling simulation method based on Fluent software, the urgent demand of temperature control in a complex flight environment of an airborne equipment cabin is considered, and spray cooling simulation in a narrow area is realized under the condition of comprehensively considering spray model parameter selection, geometric model influence and algorithm convergence and accuracy; the defects of traditional calculation model setting in the aspects of convergence and response speed are overcome, and a flow field temperature field cloud picture of a typical cabin of a computational domain is accurately obtained.

Description

Technical Field

[0001] The present application belongs to the technical field of thermal simulation of closed cabins with internal and external thermal coupling, and in particular relates to a spray cooling simulation method based on Fluent software. Background Art

[0002] Spray cooling is an effective heat transfer technology that uses the atomization and evaporation of liquid to remove heat from the surface of the cooled object by impacting the liquid film on the surface of the cooled object through spray cooling droplets. Figure 1 As shown. It has the characteristics of high heat transfer coefficient, uniform temperature distribution, low superheat, high critical flow rate, and low circulation flow rate. Spray cooling technology plays an important role in cooling applications that require extremely high heat dissipation rates. Industries such as electronics, energy, transportation, manufacturing, aerospace and defense all require high heat dissipation capabilities from cooling systems. High heat dissipation requirements are a common challenge in the industrial field, which has prompted people to continuously seek new or improved cooling processes. In many application scenarios, due to the limited heat transfer capacity of traditional cooling technologies, it is often difficult to meet the growing heat dissipation requirements.

[0003] Spray cooling replaces traditional evaporator cooling. After throttling and reducing the pressure in the condenser, the coolant enters a nozzle, where it is atomized into fine droplets and sprayed onto the surface where heat transfer is required, where it evaporates and transfers heat. This heat transfer process not only reduces coolant usage but also provides more uniform distribution, enhancing heat transfer potential. Spray cooling technology is gaining increasing attention in high-heat flux applications, offering advantages such as high heat transfer, uniform heat removal, low fluid inventory, and low droplet impact velocity. However, research on spray cooling technology has limited application in refrigeration system cycles. This is because spray cooling is a complex heat transfer technology that integrates multivariable, uncertain, complex flow fields, fast time-varying dynamics, and strong coupling. Its application, particularly in complex aircraft cabins, has always been a key and challenging area of ​​research in the aviation field. Currently, flow field microelement trajectory calculations based on the Euler and Lagrangian methods are widely used in flow field simulation due to their robustness and ease of implementation.

[0004] The shortcomings of the simulation calculation method based on traditional theory when conducting cabin cooling simulation are mainly reflected in the following aspects: (1) The transient calculation of complex flow fields converges slowly, and the calculation results are prone to divergence; within a limited flight time, spray cooling cannot guarantee that the temperature reaches the standard quickly within a limited time. (2) Although a lot of work has been done on the research of spray cooling, the research on the areas where spray cooling is restricted is relatively limited. For thermal equipment arranged in narrow spaces, it is difficult to control the temperature to meet the standard with spray cooling. For spray cooling at the edge of cabin equipment close to the external aerodynamic thermal boundary of the aircraft, the temperature control effect is difficult to achieve. (3) During the flight, the external aerodynamic thermal parameters are always changing, and the working conditions are changing. Its parameter adjustment is heavily dependent on external conditions, and the required spray flow rate is difficult to adjust in real time at any time. The adjustment of spray cooling parameters in transient design simulation is time-consuming and labor-intensive.

[0005] Therefore, it is desired to have a technical solution to overcome or at least alleviate at least one of the above-mentioned deficiencies of the prior art. Summary of the Invention

[0006] The purpose of this application is to provide a spray cooling simulation method based on Fluent software to solve at least one problem existing in the prior art.

[0007] The technical solution of this application is:

[0008] A spray cooling simulation method based on Fluent software includes:

[0009] Step 1: Build a cabin grid model;

[0010] Step 2: Simulate the cabin grid model using Fluent software to obtain simulation results;

[0011] Step 3: Analyze the simulation results to obtain a temperature distribution cloud map of the equipment surface inside the cabin and a temperature distribution cloud map of the cabin outlet.

[0012] In at least one embodiment of the present application, in step 1, constructing a cabin grid model includes:

[0013] Get the cabin layout structure;

[0014] Simplifying the cabin layout structure and constructing a cabin geometric model;

[0015] Meshing the cabin geometric model to obtain a cabin mesh model;

[0016] Perform a quality check on the cabin mesh model.

[0017] In at least one embodiment of the present application, the cabin geometric model includes a cabin wall, equipment and an outlet, the equipment is located inside the cabin formed by the cabin wall, the outlet is opened on the cabin wall, and the cabin wall and the outlet are both set to be thin plate structures of negligible thickness.

[0018] In at least one embodiment of the present application, when meshing the cabin geometric model, multiple fluid domains are set according to the equipment inside the cabin, and local mesh encryption is performed on the cabin wall surface and the equipment surface where the outlet is opened.

[0019] In at least one embodiment of the present application, in step 2, simulating the cabin grid model using Fluent software to obtain simulation results includes:

[0020] Importing the cabin grid model into Fluent software;

[0021] Set up flow field simulation examples, including determining the flow field simulation calculation model and setting simulation parameters;

[0022] The cabin grid model is simulated according to the flow field simulation example to obtain simulation results.

[0023] In at least one embodiment of the present application, the flow field simulation calculation model includes a flow calculation model and a discrete phase model.

[0024] In at least one embodiment of the present application, the flow calculation model adopts a Realizable k-ε turbulence model, and the Realizable k-ε turbulence model includes:

[0025] The k equation is:

[0026]

[0027] The ε equation is:

[0028]

[0029] Where ρ is the density, k is the turbulent kinetic energy, μ i is the velocity component, μ is the fluid dynamic viscosity, μ τ is the turbulent viscosity, σ k is an adjustable parameter, P k is the generation term of turbulent kinetic energy, ε is the turbulent dissipation rate, C 1ε 、C 2ε is the model constant.

[0030] In at least one embodiment of the present application, the discrete phase model includes:

[0031] Liquid nitrogen is sprayed into atomized droplets into the interior of the chamber through a swirl nozzle. The diameter distribution of the atomized droplets adopts the Rosin-Rammler distribution model. The Rosin-Rammler distribution equation is:

[0032]

[0033] Among them, V c is the ratio of the volume of droplets with diameters below D to the total volume of droplets, where c and n are both constants;

[0034] The discrete phase momentum equation is:

[0035]

[0036] Among them, m d is the mass of the droplet, is the velocity of the droplet in the i direction, t is the time, μ is the fluid dynamic viscosity, C D is the drag coefficient, Re is the Reynolds number, d p is the droplet diameter, ρ d is the droplet density, is the velocity of the gas phase in the i direction, is the acceleration due to gravity;

[0037] The droplet temperature calculation equation is:

[0038]

[0039] Among them, c p,d is the droplet specific heat capacity, T ∞ is the evaporation temperature, T d is the droplet temperature, f is the correction coefficient for convective heat transfer, h v is the latent heat of vaporization, A d is the surface area of ​​each droplet, h is the droplet heat transfer coefficient, is the energy exchange of the droplet caused by radiation, G c is the incident radiation, ε is the emissivity, and σ is the scattering coefficient;

[0040] Droplet temperature T within Δt time step d Changes to:

[0041]

[0042]

[0043] Among them, θ R is the radiation temperature;

[0044] When the droplet temperature is lower than the evaporation temperature, the endothermic equation is:

[0045]

[0046] When the droplet temperature reaches the evaporation temperature, the evaporation equation is:

[0047] N x =k i (c x,s -c x,∞ )

[0048] Among them, N x is the molar flow rate of steam, k i is the mass transfer coefficient, C x,s is the vapor concentration of the droplet, C x,∞ is the vapor concentration in the gas phase;

[0049] When the droplet temperature reaches the boiling point, the boiling equation is:

[0050]

[0051] Among them, C p,∞ is the gas phase constant pressure specific heat, ρ d is the droplet density, k ∞ is the gas phase thermal conductivity, h fg is the latent heat of vaporization of the liquid film.

[0052] In at least one embodiment of the present application, the simulation parameters include: model parameters, spray cooling parameters, material property parameters, boundary conditions, and calculation speed.

[0053] In at least one embodiment of the present application, step three further includes: analyzing the simulation results to quantitatively determine the temperature of key surfaces, heat transfer coefficient, and liquid nitrogen demand in the cabin.

[0054] The invention has at least the following beneficial technical effects:

[0055] This Fluent-based spray cooling simulation method addresses the urgent need for temperature control in the complex flight environment of an aircraft's equipment compartment. By comprehensively considering spray model parameter selection, geometric model influences, and algorithm convergence and accuracy, it achieves spray cooling simulation within a narrow area. This method overcomes the convergence and response speed limitations of traditional computational model setups, accurately capturing flow and temperature field cloud maps, typical surface temperatures, and heat transfer coefficients within a typical compartment within the computational domain. This approach optimizes cabin liquid nitrogen demand, coordinates with the aircraft's integrated thermal management system, and enhances the efficiency and reliability of the thermal management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a schematic diagram of the existing spray cooling droplets impacting the liquid film;

[0057] Figure 2This is a flow chart of a spray cooling simulation method based on Fluent software according to one embodiment of the present application;

[0058] Figure 3 This is a front view of the central cross section of the cabin in the xz direction according to one embodiment of the present application;

[0059] Figure 4 This is a left side view of the cabin in the yz direction according to one embodiment of the present application;

[0060] Figure 5 This is a schematic diagram of a three-dimensional computational grid inside a cabin according to one embodiment of the present application;

[0061] Figure 6 is a schematic diagram of a global grid setting according to one embodiment of the present application;

[0062] Figure 7 is a schematic diagram of a local grid setting according to an embodiment of the present application;

[0063] Figure 8 This is a schematic diagram of material definition for one embodiment of the present application;

[0064] Figure 9 This is a schematic diagram of adding fluid materials and defining parameters according to one embodiment of the present application;

[0065] Figure 10 is a schematic diagram of the definition of a discrete phase model according to one embodiment of the present application;

[0066] Figure 11 This is a schematic diagram of nozzle parameter definition according to one embodiment of the present application;

[0067] Figure 12 This is a schematic diagram of the pressure outlet boundary condition definition in one embodiment of the present application;

[0068] Figure 13 This is a schematic diagram of the definition of the no-slip boundary condition of the heat dissipation surface of the device according to one embodiment of the present application;

[0069] Figure 14 This is a schematic diagram of the definition of the thermal boundary conditions of the thin shell of the heat dissipation surface of the device in one embodiment of the present application;

[0070] Figure 15 This is a schematic diagram of the definition of the no-slip boundary condition on the outer wall in one embodiment of the present application;

[0071] Figure 16 This is a schematic diagram of the definition of the outer wall temperature boundary condition in one embodiment of the present application;

[0072] Figure 17 This is a schematic diagram of the energy equation for the open state of one embodiment of the present application;

[0073] Figure 18 is a schematic diagram of selecting a turbulence model according to one embodiment of the present application;

[0074] Figure 19 This is a schematic diagram of a solution method definition in one embodiment of the present application;

[0075] Figure 20 is a schematic diagram of the definition of relaxation factors according to one embodiment of the present application;

[0076] Figure 21 This is a schematic diagram of initialization parameter definition for one embodiment of the present application;

[0077] Figure 22 This is a schematic diagram of key flow field parameter definitions for one embodiment of the present application;

[0078] Figure 23 This is a schematic diagram of the arrangement of cabin spray cooling nozzles according to one embodiment of the present application;

[0079] Figure 24 This is a schematic diagram of the temperature change on the surface of a device according to one embodiment of the present application;

[0080] Figure 25 This is a device surface temperature cloud map of one embodiment of the present application. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solutions and advantages of the implementation of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below in conjunction with the drawings in the embodiments of this application. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described embodiments are part of the embodiments of this application, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain this application, and should not be understood as limitations on this application. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. The embodiments of this application are described in detail below in conjunction with the drawings.

[0082] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as limiting the scope of protection of this application.

[0083] The following is combined with Figures 2 to 25 This application is described in further detail.

[0084] This application provides a spray cooling simulation method based on Fluent software, comprising the following steps:

[0085] Step 1: Build a cabin grid model;

[0086] Step 2: Use Fluent software to simulate the cabin grid model and obtain simulation results;

[0087] Step 3: Analyze the simulation results to obtain the surface temperature distribution cloud map of the equipment inside the cabin and the cabin outlet temperature distribution cloud map.

[0088] In a preferred embodiment of the present application, in step 1, constructing a cabin grid model includes:

[0089] Get the cabin layout structure;

[0090] Simplify the design of cabin layout structure and build cabin geometric model;

[0091] Meshing the cabin geometric model to obtain a cabin mesh model;

[0092] Perform quality check on the cabin mesh model.

[0093] In a preselected embodiment of this application, the cabin geometric model includes cabin walls, equipment, and an outlet. The equipment is located within the cabin formed by the cabin walls, and the outlet is located on the cabin walls. Both the cabin walls and the outlet are configured as thin plate structures of negligible thickness. In this embodiment, when meshing the cabin geometric model, multiple fluid domains are preferably configured based on the equipment within the cabin, and local mesh refinement is performed on the cabin walls and equipment surfaces where the outlet is located.

[0094] The spray cooling simulation method based on Fluent software in this application selects geometric features related to the simulation analysis work according to the cabin layout structure, performs simplified design, and then uses Catia software to perform geometric modeling on the simplified cabin layout structure to obtain a cabin geometric model. The cabin geometric model is imported into ICEM software for meshing. When meshing, different equipment inside the cabin are named, and multi-fluid domains are set. The grid size is reasonably selected, and the model features and boundary layers are better captured through local grid encryption. During the mesh drawing process, attention should be paid to the naming and classification of geometric features, multi-fluid division, local grid encryption, internal wall panel setting, etc., to divide the flow field inside the cabin and generate a high-quality structural grid. At the same time, the cabin geometric model and the grid boundary need to be set accordingly. The drawn grid is quality tested and the number of grids is estimated. Finally, a cabin grid model that meets the simulation requirements is obtained. The cabin grid model is exported and converted into an unstructured grid for easy reading into Fluent software.

[0095] In the preselected embodiment of the present application, in step 2, the cabin grid model is simulated using Fluent software to obtain simulation results, including:

[0096] Import the cabin mesh model into Fluent software;

[0097] Set up flow field simulation examples, including determining the flow field simulation calculation model and setting simulation parameters;

[0098] The cabin grid model is simulated according to the flow field simulation example to obtain the simulation results.

[0099] The spray cooling simulation method based on Fluent software in this application imports the obtained cabin grid model into Fluent software for simulation. According to the internal flow characteristics of the cabin and the spray cooling requirements, according to a reasonable flow calculation model and a discrete phase model that characterizes the spray particles, simulation parameters such as model parameters, spray cooling parameters, material characteristic parameters, boundary conditions and calculation speed are set, and the internal flow field characteristics of the cabin are calculated until the simulation results converge.

[0100] In a preferred embodiment of the present application, setting up a flow field simulation example also includes: checking the grid, enabling the energy equation, setting up a simulation for device heating, modifying the relaxation factor, saving the example, initializing the example, etc. Verification through the flow field simulation example ensures the rationality of the example and the accuracy of the calculation results.

[0101] In a preferred embodiment of the present application, the flow field simulation model includes a flow calculation model and a discrete phase model. The flow calculation model utilizes the Realizable k-ε turbulence model, and the discrete phase model utilizes the Coupled algorithm model. In addition to the three conventional continuous phase calculation equations for fluid mechanics, the momentum equation and droplet temperature are calculated using discrete terms for the heat absorption, evaporation, and boiling processes that occur after the refrigerated liquid nitrogen is sprayed into the chamber through a swirl nozzle. Based on the relationship between the droplet temperature and the evaporation and boiling temperatures, the droplet temperature change and boiling evaporation rate within a specific time step are determined, thereby measuring the effectiveness of the spray cooling.

[0102] Specifically, in this embodiment, the nozzle sprays refrigerant into the evaporator cavity at a high velocity, causing turbulent motion in the continuous phase gas. Turbulence models can be divided into two categories: direct numerical simulation (DNS) and Reynolds-averaged turbulence model (RANS). The k equation and ε equation of the RANS Realizable k-ε turbulence model are as follows:

[0103]

[0104] Where ρ is the density, unit is kg / m 3 ; k is the turbulent kinetic energy, m 2 / s 2 ;μ i is the velocity component, unit is m / s; μ is the fluid dynamic viscosity, unit is Pa·s; μ τ is the turbulent viscosity, unit is Pa·s; σ k is an adjustable parameter; P k is the generation term of turbulent kinetic energy, unit is kg / (m·s 3 );ε is the turbulent dissipation rate, unit is m 2 / s 3 ε in the equation C 1ε and C 2ε is the model constant.

[0105] The swirl nozzle is simulated based on the discrete phase model (DPM). The diameter distribution of the atomized droplets adopts the Rosin-Rammler distribution model, and the distribution function is:

[0106]

[0107] Among them, V c It is the ratio of the volume of droplets with diameters below D to the total volume of droplets; c and n are both constants.

[0108] In this embodiment, the discrete phase momentum equation is:

[0109]

[0110] Among them, m d is the mass of the droplet, in kg; is the velocity of the droplet in the i direction, in m / s; t is the time, in s; μ is the dynamic viscosity of the fluid, in Pa·s; C D is the drag coefficient, which is calculated based on the assumption that the droplet is a sphere; Re is the Reynolds number; d p is the droplet diameter, unit is m; ρ d is the droplet density, in kg / m 3 ; is the velocity of the gas phase in the i direction, in m / s; is the acceleration due to gravity, in m / s 2 .

[0111] The droplet temperature is caused by convection, evaporation and radiation heat transfer. The droplet temperature can be calculated using the droplet temperature calculation equation:

[0112]

[0113] Among them, c p,d is the specific heat capacity of the droplet, in J / (kg·℃); T ∞ is the evaporation temperature, T d is the droplet temperature, unit is °C; f is the correction factor for convective heat transfer; h v is the latent heat of vaporization, unit is kJ / kg; A d is the surface area of ​​each droplet, in m 2 ; h is the droplet heat transfer coefficient, unit J / (m 2 ·s·K); is the energy exchange of the droplet caused by radiation, unit is J; G c is the incident radiation; ε is the emissivity; σ is the scattering coefficient;

[0114] The correction factor f for convective heat transfer is:

[0115]

[0116] Where λ is the thermal conductivity in J / (m·s·°C); the Nusselt number Nu is calculated using the Ranz Marshall heat transfer model:

[0117] Nu=2+0.6Re 1 / 2 Pr 1 / 3

[0118]

[0119] Where Pr is the Prandtl number and d is the calculated characteristic length;

[0120] Droplet temperature T within Δt time step dChanges to:

[0121]

[0122]

[0123] Among them, θ R is the radiation temperature, unit is ℃.

[0124] After the refrigerated liquid nitrogen is sprayed into the interior of the cabin through the swirl nozzle, it absorbs heat, evaporates and boils. According to the relationship between the droplet temperature and the evaporation temperature and boiling temperature, it can be divided into several situations.

[0125] When the droplet temperature is lower than the evaporation temperature, only the temperature changes, and the heat absorption equation is:

[0126]

[0127] When the droplet temperature reaches the evaporation temperature, the atomized droplets evaporate, and the evaporation amount of the droplets is controlled by the concentration gradient diffusion between the droplets and the gas phase. The evaporation equation is:

[0128] N x =k i (c x,s -c x,∞ )

[0129] Among them, N x is the molar flow rate of steam, unit is (kg·mol) / (m 2 ·s);k i is the mass transfer coefficient, unit is m / s; C x,s is the vapor concentration of the droplet, unit (kg·mol) / m 3 ; C x,∞ is the vapor concentration in the gas phase, (kg·mol) / m 3 .

[0130] When the droplet temperature reaches the boiling point, the boiling evaporation rate equation is:

[0131]

[0132] Among them, C p,∞ is the specific heat of gas at constant pressure, unit is J / (kg·℃); ρ d is the droplet density, in kg / m 3 ;k ∞ is the gas phase thermal conductivity, unit is W / (m·℃); h fg is the latent heat of vaporization of the liquid film, unit is J / kg.

[0133] This Fluent software-based spray cooling simulation method, based on this application, concludes with post-processing and analysis of the simulation results in step three, generating temperature distribution cloud maps of the equipment surfaces within the cabin and the cabin outlet. By analyzing the spray cooling conditions and flow field characteristics, the temperatures of key surfaces, heat transfer coefficients, and the cabin's liquid nitrogen requirements are quantitatively determined.

[0134] In one embodiment of the present application, the implementation process of the spray cooling simulation method based on Fluent software of the present application is described by taking the aircraft wheel well compartment with a narrow area as an example. Figure 2 As shown, specifically including:

[0135] Step 1: Construct the aircraft wheel well compartment mesh model, including:

[0136] Input the aircraft wheel well compartment layout structure;

[0137] Establish a simplified geometric model of the aircraft wheel well compartment;

[0138] Draw the calculation grid of the flow field inside the aircraft wheel well compartment and obtain the grid model of the aircraft wheel well compartment.

[0139] Step 2: Use Fluent software to simulate the aircraft wheel well compartment mesh model and obtain simulation results, including:

[0140] Import the aircraft wheel well compartment mesh model into Fluent 19.2 software;

[0141] Set the flow field simulation solution method and set the aircraft wheel well compartment calculation domain boundary conditions according to actual conditions;

[0142] Start iterative calculations and pay attention to the residual convergence. If the residual convergence does not meet the requirements, adjust the calculation parameters, modify the calculation grid, and redraw the calculation grid of the flow field inside the aircraft wheel well compartment. If the residual convergence meets the requirements, obtain the simulation results.

[0143] Step 3: Analyze the simulation results and output the aircraft wheel well cabin simulation results.

[0144] In this embodiment, Figure 3-4 As shown, the typical narrow equipment compartment of the aircraft wheel well is designed as a flat cabin of 1000mm*1000mm*200mm, with x-axis coordinates of -500~500mm, y-axis coordinates of -500~500mm, and z-axis coordinates of 0~200mm. The exit is located at the front center and is a circular exit with a radius of 40mm. There are two blocks inside the aircraft wheel well as heating devices, which are set to shell heating, with a shell thickness of 2mm and a heat density of 1000000W / m 3 .

[0145] Analyze the air flow and key geometric features within the cabin, and use these as a reference for subsequent simulation settings. Ignore internal cabin structures that have minimal impact on medium flow and heat transfer, retaining the key geometric features. Based on engineering needs, select appropriate openings to guide the outflow of the spray gas within the cabin. The resulting cabin geometry includes the cabin walls, heat-generating equipment, and gas outlets. The cabin walls and outlets are designed as thin plate structures with negligible thickness.

[0146] Import the established cabin geometry model file into the ICEM software. Be sure to set the model's dimensional units and check the model for errors such as gaps and overlaps. Repair the cabin geometry model and separately establish the volume structure for the cabin interior and heat-generating equipment. Identify and name key geometric components such as volumes, walls, outlets, and equipment to facilitate subsequent operations. Keep the default names for unimportant point and line structures. Once the model is confirmed to be correct, begin meshing.

[0147] First, set the global grid. Select the maximum grid size as 30mm and the grid formation method as Tetra / Mixed. Figure 5 shown.

[0148] Then enter the local grid setting interface to refine the local grid settings. Since the number of grids in the model will affect the calculation speed of subsequent simulations, and the number of grids is closely related to the grid size, the overall grid size is set to be large. However, a large grid size will lead to a decrease in calculation accuracy. Therefore, for some local areas, such as the cabin wall with an exit, the surface of the equipment, etc., the grid size should be appropriately reduced to ensure the accuracy of the simulation of this part. Figure 6 shown.

[0149] After setting the mesh size and mesh generation method, click compute mesh to generate the mesh, such as Figure 7 shown.

[0150] Check the cabin mesh model for any incomplete, missing, or geometrically incompatible features. Once the mesh is complete, perform a mesh quality check. In this example, the minimum quality was 0.32 and the average quality was 0.73, meeting the calculation requirements. Finally, save the drawn cabin mesh model and convert it to mesh format. Import it into Fluent software and check that the cabin mesh model has been imported properly and completely. Once the import is confirmed, proceed with the simulation.

[0151] Import the generated flat narrow cabin mesh into Fluent 19.2 software. After importing, you can check the mesh, adjust the mesh unit, and complete the mesh scaling. Set the boundary conditions and calculation parameters for the flow field simulation. First, you need to define the materials of the solid domain and fluid domain in the calculation domain. Click "Material" in the task tree on the left to define the material, such as Figure 8 shown.

[0152] Taking fluid material as an example, right-click "Fluid" and select Create to enter the definition interface of the fluid material, such as Figure 9 For common materials, such as air, various gas elements, water, and water vapor, you can directly find the corresponding material from the "FluentDatabase" and click to copy it. For uncommon fluid materials, or materials that must be customized due to engineering needs, you can edit the fluid physical properties in the "Properties" box. The parameter definition method can be selected as a constant, or it can be defined as an interpolation or function.

[0153] The spray cooling method requires defining the basic parameters of the spray cooling. Unlike other boundary conditions, the spray cooling parameters need to be set in the model. Click the discrete phase "Discrete Phase" in the task tree on the left, create "injections" and edit them, such as Figure 10 shown.

[0154] In this embodiment, a total of 12 nozzles (s1 to s8, x1 to x4) are set. Taking nozzle s1 as an example, its parameter definition box is as follows: Figure 11 As shown. Select the droplet form in "Particle", and select liquid nitrogen as the spray fluid, and nitrogen as the fluid after evaporation phase change. Next, you need to set the specific parameters of the spray nozzle in "Point Properties". The first three items define the x, y, and z positions of the spray nozzle, and the following "X-Axis", "Y-Axis", and "Z-Axis" define the direction of the nozzle. Then you need to define the temperature of the working fluid ejected from the spray nozzle and its mass flow rate. According to the selected nozzle model, you also need to continue to define the inner diameter of the spray nozzle, the angle of the spray, etc. After defining these basic parameters, the definition of the spray cooling conditions is completed.

[0155] In this embodiment, a pressure swirl nozzle is set for spray cooling, the spray pressure is 1 MPa, the droplet diameter is set to 1 mm, and the spray temperature is -198.15°C. The specific parameters of each nozzle are shown in Table 1.

[0156] Table 1

[0157]

[0158]

[0159] If the cabin does not use spray cooling, but instead uses forced convection to dissipate heat, then a velocity inlet boundary condition can be defined at the location where the cold air enters the cabin. The basic parameters required for the velocity inlet boundary condition are the inflow velocity of the fluid and the temperature of the fluid. Other parameters can be left at their default settings. The pressure outlet boundary condition is defined at the outlet location, such as Figure 12 As shown, generally no modification is required, just keep the 0 gauge pressure boundary setting.

[0160] For the heat dissipation surface of the device, define it as a wall boundary form and set it specifically, such as Figure 13 Generally speaking, the solid domain surface can be left with the default no-slip boundary condition setting.

[0161] Since there is a certain amount of heat generation power on the surface of the equipment, it is necessary to define the thin shell thermal conductivity boundary conditions for the heat dissipation surface of the equipment, such as Figure 14 As shown in the figure, the device surface is set as a 2mm thick aluminum shell, and the heat generation rate is given to complete the definition of the device heat dissipation surface boundary conditions.

[0162] The boundary condition of the cabin wall also adopts the wall boundary form, and the definition box is as follows Figure 15 As shown, keep the default form of no slip.

[0163] like Figure 16 As shown, on the "Thermal" screen, define the temperature of the outer wall. Under "ThermalCondition," select "Temperature" and then set the temperature. This screen also allows you to define the heat generation rate, including any heat sources on the wall. In this example, a harsh operating condition is set: 200°C for the upper and lower walls and 70°C for the remaining walls.

[0164] In the model options of the task tree, the energy equation must be turned on, such as Figure 17 Otherwise, Fluent software will only perform flow field calculations but not heat transfer calculations.

[0165] Next, select the turbulence model in the flow field simulation calculation model, such as Figure 18As shown. In this embodiment, the Realizable k-ε turbulence model is used in the simulation calculation settings. The Realizable k-ε turbulence model is a newly emerged k-ε model. Although it cannot be proved that its performance has surpassed the RNG k-ε model, studies in separated flow calculations and complex flow calculations with secondary flows have shown that the Realizable k-ε turbulence model is the best performing turbulence model among all k-ε models. The main difference between the Realizable k-ε turbulence model and the standard k-ε model is that a new turbulent viscosity formula is adopted in the Realizable k-ε turbulence model; the ε equation is derived from the exact transport equation of the root mean square of the vortex disturbance. The Realizable k-ε turbulence model meets the constraints on the Reynolds stress, so it can maintain consistency with the real turbulence in terms of the Reynolds stress. This is something that neither the standard k-ε model nor the RNG k-ε model can do. The benefit of this feature in calculations is that it can more accurately simulate the diffusion velocity of plane and circular jets. At the same time, in problems such as rotational flow calculations, boundary layer calculations with directional pressure gradients, and separated flow calculations, the calculation results are more consistent with the actual situation.

[0166] Next, select "Methods" in "Solution" to define the solution method, such as Figure 19 As shown in Figure 2 . In this example, the Coupled algorithm was used as the discrete phase model for calculations. Actual simulations found that while the Coupled algorithm was slower than the SIMPLE and SIMPLEC algorithms in each step, the advantage of the coupled algorithm is that it achieves convergence with fewer iterations. Overall, the Coupled algorithm required less computation time than the SIMPLE and SIMPLEC algorithms.

[0167] In the "Controls" interface, define the relaxation factor, such as Figure 20 As shown in the figure, reduce the relaxation factor appropriately to speed up the convergence.

[0168] To initialize the flow field, select Standard Initialization, and the definition box of the initialization parameters is as follows Figure 21 The temperature of the entire flow field is set to be as close to the steady-state value as possible to save calculation time.

[0169] Before the calculation begins, it is also necessary to define some key flow field parameters in the "Report" interface to monitor whether the flow and heat transfer characteristics in the flow field have reached a stable state, such as Figure 22 shown.

[0170] After completing all the above definitions, you can click "Run Calculation" and set the number of iterations to start the CFD simulation of the flow field characteristics.

[0171] During the calculation process, the average temperature of the two equipment surfaces inside the cabin is monitored, as well as the spray quality and the average temperature of the flow field gas. During the calculation, the residual convergence curve and the equipment surface temperature convergence curve tend to be stable and meet the requirements, such as Figure 24 As shown, the simulation results can be post-processed.

[0172] Select all equipment surfaces in the cloud definition box, observe the temperature distribution on the equipment surface, and draw a temperature cloud.

[0173] The above operations can be performed in Fluent or in the post-processing tool of Workbench. By connecting the calculation results of Fluent software with the CFD-Post module, all post-processing operations can be performed directly in CFD-Post.

[0174] During the implementation of the spray cooling simulation method based on Fluent software in this application, the following matters need to be noted:

[0175] (1) The settings of fluid material property parameters and operating pressure should correspond to the actual inspection conditions. For example, the density, viscosity and operating pressure of air should be taken as the values ​​corresponding to the flight altitude.

[0176] (2) When using a pressure outlet, the calculation indicates that there is backflow at the outlet: this is because there is turbulence near the outlet. If the backflow parameters are set correctly and the backflow ratio is not large, the calculation can still be continued. If the backflow ratio is large, it is recommended to extend the outlet section to allow the flow to fully develop and reduce the impact of the backflow at the outlet on the calculation results.

[0177] (3) When using discrete phase spray cooling, it is best not to pause the calculation after it starts, and continue the calculation until it stabilizes. Otherwise, the calculation parameters may suddenly change after the pause.

[0178] (4) If spray cooling is used for heat dissipation, adjusting the spray direction toward the outlet may help stabilize the flow field and temperature field calculation results.

[0179] (5) If the calculation converges too slowly, you can try using a coupled algorithm instead of the SIMPLE / SIMPLEC algorithm, setting a pseudo-transient calculation, and increasing the Timescale factor to accelerate convergence. During the initialization phase, setting the initial cabin temperature appropriately (close to the steady-state temperature) can accelerate the convergence of the calculation results.

[0180] (6) If the calculation convergence curve fluctuates greatly, the pseudo-transient calculation can be turned off, but more calculation iterations may be required for the result to stabilize.

[0181] The spray cooling simulation method described in this application, based on Fluent software, enables excellent observation of the simulation process. By placing a relatively concentrated spray on the upper and lower surfaces of the equipment near the high-temperature wall and setting a small spray angle in narrow areas, the equipment surface can be effectively cooled. Analysis results show that compared with general spray cooling setting algorithms, under given operating conditions, this application can achieve better cooling results. The temperature curve change diagram shows that the calculation results of this application are stable and smooth, with good convergence, and are easy to implement in engineering.

[0182] The spray cooling simulation method based on Fluent software in this application takes into account the urgent need for temperature control in the complex flight environment of the airborne equipment cabin. It realizes spray cooling simulation in a narrow area while comprehensively considering the selection of spray model parameters, the influence of geometric models, and the convergence and accuracy of the algorithm, breaking through the shortcomings of traditional calculation model settings in terms of convergence and response speed. The temperature cooling scheme for the surface of equipment in a narrow area realizes the simulation calculation of a particularly harsh environment under a certain working condition of a given section. This application can well achieve the simulation convergence under given working conditions, and the spray cooling effect is good. While ensuring the convergence of the flow field calculation, the obtained temperature drop curve changes smoothly, which is easy to monitor and implement in engineering. The order of magnitude of the residual is 10 -3 The cooling accuracy is significantly better than that of complex cabin spray cooling. In addition, simulation results show that the temperature control range of the method proposed in this application is good, with the temperature difference within 40 degrees.

[0183] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A spray cooling simulation method based on Fluent software, characterized in that: include: Step 1: Build a cabin grid model; Step 2: Simulate the cabin grid model using Fluent software to obtain simulation results; Step 3: Analyze the simulation results to obtain a temperature distribution cloud map of the equipment surface inside the cabin and a temperature distribution cloud map of the cabin outlet.

2. The spray cooling simulation method based on Fluent software according to claim 1, characterized in that: In step 1, the cabin grid model is constructed, including: Get the cabin layout structure; Simplifying the cabin layout structure and constructing a cabin geometric model; Meshing the cabin geometric model to obtain a cabin mesh model; Perform a quality check on the cabin mesh model.

3. The spray cooling simulation method based on Fluent software according to claim 2, characterized in that: The cabin geometric model includes a cabin wall, equipment and an outlet. The equipment is located inside the cabin formed by the cabin wall. The outlet is opened on the cabin wall. The cabin wall and the outlet are both set to be thin plate structures with negligible thickness.

4. The spray cooling simulation method based on Fluent software according to claim 3, characterized in that: When meshing the cabin geometric model, multiple fluid domains are set according to the equipment inside the cabin, and local mesh encryption is performed on the cabin wall surface where the outlet is opened and the equipment surface.

5. The spray cooling simulation method based on Fluent software according to claim 4, characterized in that: In step 2, the cabin grid model is simulated using Fluent software to obtain simulation results, including: Importing the cabin grid model into Fluent software; Set up flow field simulation examples, including determining the flow field simulation calculation model and setting simulation parameters; The cabin grid model is simulated according to the flow field simulation example to obtain simulation results.

6. The spray cooling simulation method based on Fluent software according to claim 5, characterized in that: The flow field simulation calculation model includes a flow calculation model and a discrete phase model.

7. The spray cooling simulation method based on Fluent software according to claim 6, characterized in that: The flow calculation model adopts the Realizable k-ε turbulence model, which includes: The k equation is: The ε equation is: Where ρ is the density, k is the turbulent kinetic energy, μ i is the velocity component, μ is the fluid dynamic viscosity, μ τ is the turbulent viscosity, σ k is an adjustable parameter, P k is the generation term of turbulent kinetic energy, ε is the turbulent dissipation rate, C 1ε 、C 2ε is the model constant.

8. The spray cooling simulation method based on Fluent software according to claim 7, characterized in that: The discrete phase model includes: Liquid nitrogen is sprayed into atomized droplets into the interior of the chamber through a swirl nozzle. The diameter distribution of the atomized droplets adopts the Rosin-Rammler distribution model. The Rosin-Rammler distribution equation is: Among them, V c is the ratio of the volume of droplets with diameters below D to the total volume of droplets, where c and n are both constants; The discrete phase momentum equation is: Among them, m d is the mass of the droplet, is the velocity of the droplet in the i direction, t is the time, μ is the fluid dynamic viscosity, C D is the drag coefficient, Re is the Reynolds number, d p is the droplet diameter, ρ d is the droplet density, is the velocity of the gas phase in the i direction, is the acceleration due to gravity; The droplet temperature calculation equation is: Among them, c p,d is the droplet specific heat capacity, T ∞ is the evaporation temperature, T d is the droplet temperature, f is the correction coefficient for convective heat transfer, h v is the latent heat of vaporization, A d is the surface area of ​​each droplet, h is the droplet heat transfer coefficient, is the energy exchange of the droplet caused by radiation, G c is the incident radiation, ε is the emissivity, and σ is the scattering coefficient; Droplet temperature T within Δt time step d Changes to: Among them, θ R is the radiation temperature; When the droplet temperature is lower than the evaporation temperature, the endothermic equation is: When the droplet temperature reaches the evaporation temperature, the evaporation equation is: N x =k i (c x,s -c x,∞ ) Among them, N x is the molar flow rate of steam, k i is the mass transfer coefficient, C x,s is the vapor concentration of the droplet, C x,∞ is the vapor concentration in the gas phase; When the droplet temperature reaches the boiling point, the boiling equation is: Among them, C p,∞ is the gas phase constant pressure specific heat, ρ d is the droplet density, k ∞ is the gas phase thermal conductivity, h fg is the latent heat of vaporization of the liquid film.

9. The spray cooling simulation method based on Fluent software according to claim 8, characterized in that: The simulation parameters include: model parameters, spray cooling parameters, material characteristic parameters, boundary conditions and calculation speed.

10. The spray cooling simulation method based on Fluent software according to claim 9, characterized in that: Step three also includes: analyzing the simulation results to quantitatively determine the temperature of key surfaces, heat transfer coefficient, and cabin liquid nitrogen demand.

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