Numerical simulation method and system for two-phase flow heat transfer

Abstract

The invention relates to a numerical simulation method and system for two-phase flow heat transfer, and the method comprises the following steps: S01, setting a physical parameter, a grid parameter and a calculation parameter of simulation content according to the simulation content, and initializing a grid; s02, initializing a two-phase parameter field, a velocity field and a temperature field, and giving boundary conditions; s03, calculating time evolution conditions of the two-phase parameter field, the velocity field and the pressure field by using a two-phase flow model; s04, on the basis of the time evolution condition of the obtained velocity field, calculating and obtaining the time evolution condition of the temperature field through a convective diffusion equation; and S05, outputting required simulation data in combination with the obtained time evolution conditions of the two-phase parameter field, the velocity field, the pressure field and the temperature field. On the basis of the adaptive grid, the temperature field is added into the flow field as a passive scalar, so that the application range of the numerical simulation method is widened, the reliability of the simulation result is improved, and the convenience of analyzing problems is improved.

Description

Technical Field

[0001] The present application relates to the technical field of two-phase flow heat transfer systems, and in particular to a numerical simulation method and system for two-phase flow heat transfer. Background Art

[0002] Two-phase flow and heat transfer systems between fluids are widely present in nature, industry, agriculture, medicine and people's daily lives. Among the above-mentioned two-phase flow heat transfer systems, the most common is the two-phase flow carrying droplets or bubbles; for the heat transfer problem of two-phase flow carrying droplets or bubbles, we can focus on the complex changes in a short period of time. At this time, the temperature can be regarded as a passive scalar of the complex evolution of the two-phase flow field. Numerical simulation of two-phase flow heat transfer is a method that uses computational fluid dynamics technology to numerically simulate the heat transfer process in two-phase fluids. With the rapid development of computer storage capacity and computing speed in recent years and the advancement of fluid mechanics calculation methods, numerical simulation has become an important means to study two-phase flow problems.

[0003] Direct numerical simulation of two-phase flow is more difficult than that of single-phase flow, mainly because two-phase flow has more complex multi-scale effects. Furthermore, direct numerical simulation of liquid-liquid and gas-liquid two-phase flow is more challenging than that of liquid-solid and gas-solid two-phase flow to some extent, mainly because of the complex deformation and changes in topological properties at the two-fluid interface, and the scale of the two-phase interface reaches the molecular level. If combined with heat transfer between fluids, the amount of calculation, complexity and difficulty of analysis will be greater.

[0004] At present, the development time of direct numerical simulation methods for two-phase flow heat transfer is limited. Due to the complexity of numerical simulation methods, existing numerical simulation methods still have some technical defects and deficiencies. For the heat transfer problem of droplets or bubbles, there are related calculation models, but the existing methods are often one of the following two types:

[0005] (1) Simple case: Simplify the droplet / bubble model, for example, treat it as a point particle or keep its shape spherical, and assume that the temperature inside the droplet / bubble is uniform or symmetrically distributed about the center of the sphere;

[0006] (2) Complex situations: Considering the effects of phase change such as condensation, evaporation and even boiling at the same time, considering the Stephen flow caused by phase change, or considering the Marangoni effect where the temperature difference changes the surface tension gradient, instead of focusing on a single heat transfer process.

[0007] For the simple case above, it is difficult to judge how much error the simplification of the droplet / bubble model will bring to the results, and its scope of application has not been studied clearly; the influence of the details of the two-phase flow has been largely ignored in related analyses, but it may dominate in practical applications, especially in turbulent fields. The two-phase interface increases the complexity of the small-scale structure, affects the energy transfer process, and then changes the energy spectrum of the entire field. For the complex case above, multiple factors such as heat transfer, phase change, and surface tension change are intertwined, making it more difficult to discuss, which is not conducive to the basic analysis of heat changes caused by the two-phase interface.

[0008] In summary, the existing methods are either too simple in terms of models, simplifying the droplets / bubbles and failing to show the complex effects of interface changes in two-phase flow, resulting in poor reliability; or too complex, taking processes such as phase change into consideration, making it difficult to accurately distinguish the impact of two-phase flow on the heat transfer process, resulting in poor feasibility. Summary of the invention

[0009] In order to solve the problems existing in the above-mentioned prior art, the purpose of this application is to provide a numerical simulation method and system for two-phase flow heat transfer. Based on the adaptive grid, the present invention adds the temperature field as a passive scalar into the flow field, thereby improving the scope of application of the numerical simulation method, the reliability of the simulation results, and the convenience of analyzing the problem.

[0010] A numerical simulation method for two-phase flow heat transfer described in the present application uses a fluid volume method for numerical simulation, and the numerical simulation method comprises the following steps:

[0011] S01. According to the simulation content, set the physical parameters, grid parameters and calculation parameters of the simulation content, and initialize the grid;

[0012] S02, initializing the two-phase parameter field, velocity field and temperature field, and giving boundary conditions;

[0013] S03, using a two-phase flow model to calculate the time evolution of the two-phase parameter field, velocity field and pressure field;

[0014] S04. Based on the obtained time evolution of the velocity field, the time evolution of the temperature field is calculated by using the convection-diffusion equation;

[0015] S05. Combining the obtained time evolution of the two-phase parameter field, velocity field, pressure field and temperature field, output the required simulation data.

[0016] Preferably, in step S01, the physical parameters include one or more of density, dynamic viscosity, thermal conductivity, specific heat capacity, surface tension, initial temperature, boundary condition temperature, heat source rate, two-phase content, interphase transfer coefficient and gravitational acceleration of each phase;

[0017] The grid parameters include grid type and grid size;

[0018] The calculation parameters include time step and convergence criterion.

[0019] Preferably, the numerical simulation method further comprises: in step S02, setting the grid density according to the expected structural richness of each region of the flow field, and / or, in step S03 and step S04, dynamically adjusting the grid density according to the real-time change of the structural richness of each region of the flow field during the simulation process,

[0020] Wherein, the grid density is positively correlated with the structural richness,

[0021] The structural richness includes one or more of vorticity, vorticity change rate, flow field gradient, turbulence intensity, interface curvature, and interface thickness.

[0022] Preferably, step S03 includes:

[0023] The two-phase parameter field is calculated by using the fluid volume method to obtain the time evolution of the interface shape and topological structure;

[0024] The time evolution of the physical parameters is obtained by calculating the linear formula in the two-phase model;

[0025] The time evolution of the velocity field and the pressure field is calculated using the continuity equation and the Navier-Stokes equation.

[0026] Preferably, step S04 includes:

[0027] The temperature field satisfies the convection-diffusion equation, which is expressed as:

[0028]

[0029] Where T represents temperature, t represents evolution time, and u represents the obtained velocity field. represents the gradient operator, D represents the thermal diffusion coefficient;

[0030] The convection term in the convection-diffusion equation The volume fraction is expressed as:

[0031]

[0032] Wherein, V represents the volume range for integration, and dV represents the microelement volume;

[0033] According to Gauss's theorem, the convection term The volume integral of is converted into the surface integral of flux, expressed as:

[0034]

[0035] Where S represents the boundary surface of the volume range V, and dS represents the element vector of the boundary surface S;

[0036] The diffusion term in the convection-diffusion equation is solved by time-implicit backward Euler difference Discretize it and express it as:

[0037]

[0038] Where Δt represents the time step, T n Represents the temperature field of the current time step, T n+1 represents the temperature field at the next time step;

[0039] The convection term and diffusion term within the same time step are calculated, and the time evolution of the temperature field is obtained by calculating the convection-diffusion equation.

[0040] Preferably, step S05 further includes:

[0041] Determine whether the number of calculation steps and / or the convergence of simulation data meet the preset requirements. If so, end the simulation process. If not, return to step S03 to continue iteration.

[0042] Preferably, the grid density is dynamically adjusted according to the real-time changes in the structural richness of each region of the flow field during the simulation process, specifically including:

[0043] A temperature gradient threshold is preset, the real-time temperature gradient of each area is calculated, and it is determined whether the real-time temperature gradient of the area is greater than the temperature gradient threshold. If so, the grid density of the area is set to the first density, otherwise, the grid density of the area is set to the second density, wherein the first density is greater than the second density.

[0044] A numerical simulation system for two-phase flow heat transfer of the present invention comprises:

[0045] A parameter setting module, which is used to set the physical parameters, grid parameters and calculation parameters of the simulation content according to the simulation content, and initialize the grid;

[0046] An initialization module, which is used to initialize the two-phase parameter field, velocity field and temperature field, and to give boundary conditions;

[0047] A first calculation module, which is used to calculate the time evolution of the two-phase parameter field, velocity field and pressure field using a two-phase flow model;

[0048] A second calculation module is used to calculate the time evolution of the temperature field through the convection-diffusion equation based on the time evolution of the obtained velocity field;

[0049] The simulation output module is used to combine the time evolution of the obtained two-phase parameter field, velocity field, pressure field and temperature field to output the required simulation data.

[0050] A computer device of the present invention comprises a processor and a memory connected by signals, wherein the memory stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by the processor, the numerical simulation method as described above is executed.

[0051] A computer-readable storage medium of the present invention stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by a processor, the numerical simulation method as described above is executed.

[0052] The advantages of the numerical simulation method and system of two-phase flow heat transfer described in this application are:

[0053] (1) In a two-phase heat transfer system, the temperature variation range of some problems is not large and the flow field evolution time is short. The influence of the temperature field on the fluid motion is negligible and can be used as a passive scalar. For example, the typical duration of a millimeter-sized droplet collision is on the order of ten milliseconds, while the typical duration of evaporation is on the order of seconds. Therefore, the phase change problem of the millimeter-sized droplet collision process can be ignored. The simulation method of the present invention can be directly used to solve such problems.

[0054] (2) For complex two-phase heat transfer problems in which the two-phase flow field and the temperature field affect each other, it is difficult to analyze the influence relationship between the two. The present invention uses temperature as a passive scalar to control the variable idea to a certain extent for such complex problems. The method can simulate the influence of the two-phase flow field on the temperature field.

[0055] (3) The application of the simulation method can be extended to the evolution of various passive scalars in two-phase flow fields, and it is highly portable. For example, the propagation and diffusion of pollutants in two-phase flow is applicable to the simulation method of this patent as long as its reaction to the two-phase flow is ignored and the evolution equation of the passive scalar is satisfied. Therefore, the invention of this patent is not only necessary in fluid mechanics and heat transfer, but also plays a fundamental and promoting role in energy conservation and emission reduction (thermal energy utilization), environmental improvement (pollutant control) and other issues related to national strategy, national economy and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of steps of a numerical simulation method of two-phase flow heat transfer described in the present application;

[0057] Figure 2It is a three-dimensional interface morphology diagram at a certain moment in the process of simulating the rising heat transfer of bubbles in the embodiment of the present application;

[0058] Figure 3 yes Figure 2 Temperature distribution diagram of the central section at the corresponding moment;

[0059] Figure 4 It is a schematic diagram of the structure of the computer device described in this embodiment.

[0060] Description of reference numerals: 101 - processor, 102 - memory. DETAILED DESCRIPTION

[0061] like Figure 1 As shown, a numerical simulation method for two-phase flow heat transfer described in the present application is mainly based on the adaptive grid technology in Basilisk. In order to highlight the influence of two-phase flow on the heat transfer process, it is mainly required to solve the fluid dynamics equations and the interface equations, and the temperature field is added into the flow field as a passive scalar.

[0062] Specifically, the two-phase flow problem in practice can often be approximated as incompressible, and the velocity field u satisfies the divergence condition, which can be expressed as:

[0063]

[0064] The momentum equation is expressed as:

[0065]

[0066] Where ρ, t, p, μ, and F represent fluid density, evolution time, pressure, fluid dynamic viscosity, and force, respectively.

[0067] Among them, for the two-phase flow problem, the fluid properties ρ and μ may be different in the two phases, so it is related to the parameters that distinguish the two phases. This embodiment does not involve other volume forces such as electromagnetic force, so F is the gravity G and the interface force F s In the scenario where gravity G is not considered, F = F s .

[0068] In this embodiment, the volume-of-fluid method is used for numerical simulation because it has good mass conservation, can capture the complex topological structure changes of the two-phase interface, and consumes low computing resources.

[0069] In the fluid volume method, the volume fraction of a phase of fluid in the grid (phase fraction) φ V It is used to characterize the distribution of two-phase flow and interface, and its evolution equation depends on the convection of the fluid:

[0070]

[0071] Among them, φ V =1, indicating that one phase A, φ V =0, indicating another phase B, 0<φ V <1 is the phase interface, and the density and dynamic viscosity of the fluid can be expressed as a linear combination of the two phases:

[0072] ρ=φ V ρ A +(1-φ V )ρ B , μ=φ V μ A +(1-φ V )μ B

[0073] In the formula, ρ A , B , μ A , μ B Represent the density and dynamic viscosity of phases A and B respectively;

[0074] The interface force is:

[0075] F s =σKn V

[0076] Among them, σ, K, n V are the surface tension, interface curvature and unit normal between the two phases respectively.

[0077]

[0078] The above-mentioned velocity divergence-free equation, momentum equation and two-phase interface equation constitute an isothermal two-phase flow model for interface analysis. The flow field and the interface interact with each other and couple in both directions, forming a sufficiently complex motion system.

[0079] In order to describe the influence of the above system on temperature T, the temperature equation is expressed as the following convection-diffusion equation:

[0080]

[0081] Where T represents temperature, t represents evolution time, and u represents the obtained velocity field. represents the gradient operator and D represents the thermal diffusivity. Explanatory, the two-phase flow equations are not affected by T, so T essentially represents the evolution of a passive scalar.

[0082] From the above introduction, it can be seen that the control equation group used in the simulation method of this embodiment is composed of the above-mentioned velocity divergence-free equation, momentum equation, two-phase interface equation and temperature field equation.

[0083] The numerical simulation method comprises the following steps:

[0084] S01. According to the simulation content, such as heat transfer during droplet collision, heat transfer during bubble rise in gravity field, heat transfer during droplet breakup in turbulence, etc., set the physical parameters, grid parameters and calculation parameters of the simulation content, and initialize the grid; wherein the physical parameters include density, dynamic viscosity, thermal conductivity, specific heat capacity, surface tension, initial temperature, boundary condition temperature, heat source rate, two-phase content, interphase transfer coefficient and gravitational acceleration of each phase;

[0085] The grid parameters include grid type and grid size;

[0086] The calculation parameters include time step and convergence criterion.

[0087] S02. Initialize the two-phase parameter field, velocity field and temperature field, and give boundary conditions, such as periodic boundary, wall boundary, constant temperature wall or adiabatic wall; in this step, take advantage of the grid adaptability to adjust the grid, change the distribution of the grid according to the characteristics of the flow field, and encrypt the grid in the structure-rich area (such as near the two-phase interface or the wall boundary), thereby improving the accuracy of the numerical simulation without significantly increasing the amount of calculation.

[0088] Specifically, the distribution of the grid can be changed according to the characteristics of the flow field, and static adjustment, dynamic adjustment, or a combination of the two can be used.

[0089] The static adjustment is as follows: before numerical simulation, the grid density is set according to the expected structural richness of each region of the flow field. For example, the structural richness is divided into several levels, each level corresponds to a different grid density, and the grid density is set according to the level corresponding to the structural richness of each region of the expected flow field. In this way, different grid densities can be set for regions with different structural richness.

[0090] The dynamic adjustment is specifically as follows: dynamically adjusting the grid density according to the real-time changes in the structural richness of each area of ​​the flow field during the simulation process.

[0091] During both static and dynamic adjustment processes, the grid density is positively correlated with the structural richness. That is, in areas with higher structural richness, the grid density is set higher to ensure that the physical changes captured in the areas with richer structures are captured with higher accuracy.

[0092] In a feasible embodiment, the structural richness includes one or more of vorticity, vorticity change rate, flow field gradient, turbulence intensity, interface curvature, and interface thickness.

[0093] When multiple indicators are used to characterize the structural richness of a region, an indicator fusion strategy can be considered. For example, the weight coefficient of the indicator can be configured according to the degree of influence of each indicator on the structural richness, and each indicator can be standardized so that each indicator has a unified dimension and numerical range. The principal component analysis (PCA) method can be used to fuse the standardized indicators into a comprehensive indicator, and this comprehensive indicator can be used to characterize the structural richness of the region. Compared with a single indicator, the comprehensive indicator will be more comprehensive in characterizing the structural richness.

[0094] In addition, the flow field can be divided into key areas and non-key areas according to the importance of the area to the simulation results. Specifically in this embodiment, since the core concept of the present invention is to add the temperature field as a passive scalar into the flow field, temperature should be used as the main consideration indicator when distinguishing key areas and non-key areas. The specific method is to preset a temperature gradient threshold, calculate the real-time temperature gradient of each area, and determine whether the real-time temperature gradient of the area is greater than the temperature gradient threshold. If so, it means that the temperature change in the area is relatively drastic, and the grid density of the area is set to the first density. Otherwise, it means that the temperature change in the area is relatively gentle, and the grid density of the area is set to the second density, wherein the first density is greater than the second density. In this way, the grid density can be reasonably set according to the importance of different areas and computing resources can be allocated.

[0095] S03. Using a two-phase flow model to calculate the time evolution of the two-phase parameter field, velocity field and pressure field; specifically, using a fluid volume method to calculate the two-phase parameter field to obtain the time evolution of the shape and topological structure of the interface; the fluid volume method is expressed as:

[0096]

[0097] The time evolution of the physical parameters is calculated using the linear formula in the two-phase model; the linear formula is expressed as:

[0098] ρ=φ V ρ A +(1-φ V )ρ B , μ=φ V μ A +(1-φ V )μ B

[0099] The time evolution of the velocity field and the pressure field is calculated using the continuity equation and the Navier-Stokes equation;

[0100] The Navier-Stokes equations are expressed as:

[0101]

[0102] S04. Based on the obtained time evolution of the velocity field, the time evolution of the temperature field is calculated by using the convection-diffusion equation;

[0103] Specifically, it can be seen from the above that the temperature field satisfies the convection-diffusion equation, which is expressed as:

[0104]

[0105] Where T represents temperature, t represents evolution time, and u represents the obtained velocity field. represents the gradient operator, D represents the thermal diffusion coefficient;

[0106] The convection term in the convection-diffusion equation The volume fraction is expressed as:

[0107]

[0108] Wherein, V represents the volume range for integration, and dV represents the microelement volume;

[0109] According to Gauss's theorem, the convection term The volume integral of is converted into the surface integral of flux, expressed as:

[0110]

[0111] Where S represents the boundary surface of the volume range V, and dS represents the element vector of the boundary surface S;

[0112] The diffusion term in the convection-diffusion equation is solved by time-implicit backward Euler difference Discretize it and express it as:

[0113]

[0114] Where Δt represents the time step, T n Represents the temperature field of the current time step, T n+1 represents the temperature field at the next time step;

[0115] The convection term and diffusion term within the same time step are calculated, and the time evolution of the temperature field is obtained by calculating the convection-diffusion equation.

[0116] S05. Combining the obtained time evolution of the two-phase parameter field, velocity field, pressure field and temperature field, output the required simulation data.

[0117] Through steps S01 to S04, the time evolution of the two-phase parameter field, velocity field, pressure field and temperature field of the simulation process is obtained, and on this basis, the simulation data can be output according to the needs. For example, to observe the dynamic cloud map, the velocity field and pressure field can be output, and the full-field data such as vorticity field, momentum field, dissipation rate field, and pseudo-vortex energy field can also be calculated and output; to observe the distribution of droplets or bubbles, the two-phase parameter field can be output; to observe the heat transfer effect or internal energy distribution, the temperature field can be output; to analyze the flow of a certain line or a certain surface, local data can be output; to make statistics on the flow field, spatial statistical data or time statistical data can be output.

[0118] After outputting the simulation data in step S05, it is necessary to determine whether the number of calculation steps and / or the convergence of the simulation data meet the preset requirements. If so, the simulation process is terminated; otherwise, the process returns to step S03 to continue iteration.

[0119] Specifically, if the simulation content is a steady-state problem, the main check is whether the convergence meets the calculation requirements of the physical problem. For transient problems, the main check is whether the number of calculation steps meets the requirements of the problem.

[0120] Based on the numerical simulation method of this embodiment, the inventor simulated the bubble rise and its heat transfer on the Basilisk platform. The specific implementation steps are as follows:

[0121] 【1】Preparation of conventional algorithms for direct numerical simulation of incompressible two-phase flow. To this end, the numerical discretization algorithm of the NS equations and the two-phase flow model algorithm (fluid volume method) are used.

[0122] 【2】Define the main physical parameters of two-phase flow simulation. Bubble rise is a gas-liquid two-phase flow problem. The density ratio can be set to 1000 and the viscosity ratio can be set to 100. In the fluid volume method, the density and viscosity of the fluid can be defined as linear functions of the phase fraction.

[0123] 【3】Add the solution of passive scalar convection and diffusion to simulate the evolution of temperature field in two-phase flow field. In the convection part, the volume integral is converted into the surface integral of flux, and only the change of mesh surface needs to be considered; in the diffusion part, time implicit backward Euler difference is used to discretize the solution.

[0124] 【4】Combined with the actual problem, set the parameters related to the two-phase flow problem. For example, the main dimensionless parameters, such as Reynolds number Re, Weber number We; calculation time, which can limit the flow time and number of running steps; calculation domain size and specific interval; specific values ​​of two-phase physical property parameters.

[0125] 【5】Initialization. The main quantities to be initialized are: velocity field, pressure field, phase fraction describing two phases, and passive scalar representing temperature field. The results of initialization are closely related to the specific physical problem being studied. For the bubble rising problem, the initial moment can be set as follows: the velocity field is always 0, the pressure field satisfies Laplace's law inside and outside the bubble, the phase fraction is 0 inside the bubble and 1 in the liquid outside the bubble, and the temperature is 1 inside the bubble and 0 outside the bubble.

[0126] 【6】Set gravity acceleration. Since bubbles rise and float due to gravity, gravity acceleration is added here.

[0127] 【7】Under the control equations, the velocity field, pressure field, phase fraction field, and temperature field evolve iteratively with each time step.

[0128] 【8】After solving the problem, output the data for analysis.

[0129] Through the above steps, the required numerical simulation results of bubble rise heat transfer can be obtained after running the program, and the data can be displayed in the form of cloud charts, such as Figure 2 , Figure 3 shown.

[0130] Based on the adaptive grid, the present invention adds the temperature field into the flow field as a passive scalar, thereby improving the application scope of the numerical simulation method, the reliability of the simulation results, and the convenience of analyzing the problem.

[0131] This embodiment also provides a two-phase flow heat transfer numerical simulation system, including:

[0132] A parameter setting module, which is used to set the physical parameters, grid parameters and calculation parameters of the simulation content according to the simulation content, and initialize the grid;

[0133] An initialization module, which is used to initialize the two-phase parameter field, velocity field and temperature field, and to give boundary conditions;

[0134] A first calculation module, which is used to calculate the time evolution of the two-phase parameter field, velocity field and pressure field using a two-phase flow model;

[0135] A second calculation module is used to calculate the time evolution of the temperature field through the convection-diffusion equation based on the time evolution of the obtained velocity field;

[0136] The simulation output module is used to combine the time evolution of the obtained two-phase parameter field, velocity field, pressure field and temperature field to output the required simulation data.

[0137] The system of this embodiment and the above-mentioned method belong to the same inventive concept, which can be understood with reference to the above description and will not be described in detail here.

[0138] like Figure 4 As shown, this embodiment also provides a computer device, including a processor 101 and a memory 102 connected by bus signals, wherein the memory 102 stores at least one instruction or at least one program, and the at least one instruction or at least one program is executed by the processor 101 when loaded. The memory 102 can be used to store software programs and modules, and the processor 101 executes various functional applications by running the software programs and modules stored in the memory 102. The memory 102 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required for functions, etc.; the data storage area can store data created according to the use of the device, etc. In addition, the memory 102 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 102 can also include a memory controller to provide the processor 101 with access to the memory 102.

[0139] The method embodiments provided in the embodiments of the present invention may be executed in a computer terminal, a server or a similar computing device, that is, the above-mentioned computer device may include a computer terminal, a server or a similar computing device. The internal structure of the computer device may include but is not limited to: a processor, a network interface and a memory. Among them, the processor, network interface and memory in the computer device may be connected via a bus or other means.

[0140] Among them, the processor 101 (or CPU (Central Processing Unit)) is the computing core and control core of the computer device. The network interface may optionally include a standard wired interface, a wireless interface (such as WI-FI, a mobile communication interface, etc.). The memory 102 (Memory) is a memory device in the computer device for storing programs and data. It can be understood that the memory 102 here can be a high-speed RAM storage device, or a non-volatile storage device (non-volatile memory), such as at least one disk storage device; optionally, it can also be at least one storage device located away from the aforementioned processor 101. The memory 102 provides a storage space, which stores the operating system of the electronic device, which may include but is not limited to: Windows system (an operating system), Linux (an operating system), Android (Android, a mobile operating system) system, IOS (a mobile operating system) system, etc., and the present invention is not limited to this; and, in the storage space, one or more instructions suitable for being loaded and executed by the processor 101 are also stored, and these instructions can be one or more computer programs (including program codes). In the embodiment of the present specification, the processor 101 loads and executes one or more instructions stored in the memory 102 to implement the numerical simulation method described in the above method embodiment.

[0141] The embodiment of the present invention further provides a computer-readable storage medium, on which at least one instruction or at least one program is stored, and the at least one instruction or at least one program is executed when loaded by the processor 101. The computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0142] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device.

[0143] For those skilled in the art, various other corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all of these changes and deformations should fall within the protection scope of the claims of this application.

Claims

1. A numerical simulation method for two-phase flow heat transfer, using a fluid volume method for numerical simulation, characterized in that: The numerical simulation method comprises the following steps: S01. According to the simulation content, set the physical parameters, grid parameters and calculation parameters of the simulation content, and initialize the grid; S02, initializing the two-phase parameter field, velocity field and temperature field, and giving boundary conditions; S03, using a two-phase flow model to calculate the time evolution of the two-phase parameter field, velocity field and pressure field; S04. Based on the obtained time evolution of the velocity field, the time evolution of the temperature field is calculated by using the convection-diffusion equation; S05. Combining the obtained time evolution of the two-phase parameter field, velocity field, pressure field and temperature field, output the required simulation data.

2. The numerical simulation method for two-phase flow heat transfer according to claim 1, characterized in that: In step S01, the physical parameters include one or more of the density, dynamic viscosity, thermal conductivity, specific heat capacity, surface tension, initial temperature, boundary condition temperature, heat source rate, two-phase content, interphase transfer coefficient and gravitational acceleration of each phase; The grid parameters include grid type and grid size; The calculation parameters include time step and convergence criterion.

3. The numerical simulation method for two-phase flow heat transfer according to claim 1, characterized in that: Also includes: In step S02, the grid density is set according to the expected structural richness of each region of the flow field, and / or, in steps S03 and S04, the grid density is dynamically adjusted according to the real-time changes in the structural richness of each region of the flow field during the simulation process, Wherein, the grid density is positively correlated with the structural richness, The structural richness includes one or more of vorticity, vorticity change rate, flow field gradient, turbulence intensity, interface curvature, and interface thickness.

4. The numerical simulation method for two-phase flow heat transfer according to claim 1, characterized in that: Step S03 includes: The two-phase parameter field is calculated by using the fluid volume method to obtain the time evolution of the interface shape and topological structure; The time evolution of the physical parameters is obtained by calculating the linear formula in the two-phase model; The time evolution of the velocity field and the pressure field is calculated using the continuity equation and the Navier-Stokes equation.

5. The numerical simulation method for two-phase flow heat transfer according to claim 1, characterized in that: Step S04 includes: The temperature field satisfies the convection-diffusion equation, which is expressed as: Where T represents temperature, t represents evolution time, and u represents the obtained velocity field. represents the gradient operator, D represents the thermal diffusion coefficient; The convection term in the convection-diffusion equation The volume fraction is expressed as: Wherein, V represents the volume range for integration, and dV represents the microelement volume; According to Gauss's theorem, the convection term The volume integral of is converted into the surface integral of flux, expressed as: Where S represents the boundary surface of the volume range V, and dS represents the element vector of the boundary surface S; The diffusion term in the convection-diffusion equation is solved by time-implicit backward Euler difference Discretize it and express it as: Where Δt represents the time step, T n Represents the temperature field of the current time step, T n+1 represents the temperature field at the next time step; The convection term and diffusion term within the same time step are calculated, and the time evolution of the temperature field is obtained by calculating the convection-diffusion equation.

6. The numerical simulation method for two-phase flow heat transfer according to claim 1, characterized in that: Step S05 also includes: Determine whether the number of calculation steps and / or the convergence of simulation data meet the preset requirements. If so, end the simulation process. If not, return to step S03 to continue iteration.

7. The numerical simulation method for two-phase flow heat transfer according to claim 3, characterized in that: According to the real-time changes in the structural richness of each area of ​​the flow field during the simulation, the grid density is dynamically adjusted, including: A temperature gradient threshold is preset, the real-time temperature gradient of each area is calculated, and it is determined whether the real-time temperature gradient of the area is greater than the temperature gradient threshold. If so, the grid density of the area is set to the first density, otherwise, the grid density of the area is set to the second density, wherein the first density is greater than the second density.

8. A numerical simulation system for two-phase flow heat transfer, characterized in that: include: A parameter setting module, which is used to set the physical parameters, grid parameters and calculation parameters of the simulation content according to the simulation content, and initialize the grid; An initialization module, which is used to initialize the two-phase parameter field, velocity field and temperature field, and to give boundary conditions; A first calculation module, which is used to calculate the time evolution of the two-phase parameter field, velocity field and pressure field using a two-phase flow model; A second calculation module is used to calculate the time evolution of the temperature field through the convection-diffusion equation based on the time evolution of the obtained velocity field; The simulation output module is used to combine the time evolution of the obtained two-phase parameter field, velocity field, pressure field and temperature field to output the required simulation data.

9. A computer device comprising a processor and a memory connected in a signal connection, characterized in that: The memory stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by the processor, the numerical simulation method according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium having at least one instruction or at least one program stored thereon, characterized in that: When the at least one instruction or the at least one program is loaded by the processor, the numerical simulation method according to any one of claims 1 to 7 is executed.

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