A numerical simulation method and system for two-phase flow heat transfer

Abstract

The application relates to a two-phase flow heat transfer numerical simulation method and system, which comprises the following steps: S01, according to simulation content, setting physical parameters, grid parameters and calculation parameters of the simulation content, and initializing a grid; S02, initializing a two-phase parameter field, a velocity field and a temperature field, and giving a boundary condition; S03, using a two-phase flow model to calculate time evolution conditions of the two-phase parameter field, the velocity field and a pressure field; S04, based on the time evolution conditions of the obtained velocity field, calculating the time evolution conditions of the temperature field through a convection-diffusion equation; and S05, combining the time evolution conditions of the obtained two-phase parameter field, velocity field, pressure field and temperature field, and outputting required simulation data. On the basis of an 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 improved, the reliability of simulation results 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 system, and particularly relates to a numerical simulation method and system of two-phase flow heat transfer. BACKGROUND

[0002] Two-phase flow and heat transfer system of fluid and fluid widely exist in nature, industry, agriculture, medicine and people's daily life. In the above two-phase flow heat transfer system, the most common one is two-phase flow carrying liquid droplets or gas bubbles; for the heat transfer problem of two-phase flow carrying liquid droplets or gas bubbles, complex changes in a short time can be concerned, at this time the temperature can be regarded as a passive scalar of complex evolution of two-phase flow field. Two-phase flow heat transfer numerical simulation is a method of using computational fluid dynamics technology to numerically simulate the heat transfer process in two-phase fluid. With the rapid development of computer storage capacity and operation speed in recent years and the progress of fluid mechanics calculation method, numerical simulation has become an important means to study two-phase flow problem.

[0003] Direct numerical simulation of two-phase flow is more difficult than single-phase flow, mainly because two-phase flow has more complex multi-scale effects; further, direct numerical simulation of liquid-liquid and gas-liquid two-phase flow is more challenging than liquid-solid and gas-solid two-phase flow to some extent, mainly because of the complex deformation and topological change at the double-fluid interface, and the two-phase interface scale reaches the molecular level, and if the heat transfer between fluids is combined, the calculation amount, complexity and analysis difficulty are greater.

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

[0005] (1) Simple case: Simplify the droplet / bubble model, such as regarding it as a point particle or keeping its shape always spherical, and assuming that the temperature inside the droplet / bubble is uniform or symmetrically distributed about the spherical center;

[0006] (2) Complex case: Considering the influence of condensation, evaporation and even boiling, considering the mass change caused by the Stefan flow of phase change, or considering the Marangoni effect of surface tension gradient caused by temperature difference, but not only focusing on single heat transfer process.

[0007] For the above simple case, it is difficult to judge how much error the simplification of droplet / bubble model brings to the result, and its applicable range is not clear; the influence of two-phase flow details is largely ignored in the related analysis, but it may be dominant in practical applications, especially in turbulent flow field, the two-phase interface increases the complexity of small-scale structure, affects the energy transfer process, and then changes the energy spectrum of the whole field. For the above complex case, various factors such as heat transfer, phase change, surface tension change, etc. are intertwined, making it difficult to discuss, which is not conducive to the basic analysis of the change of heat caused by the two-phase interface.

[0008] In summary, the existing method is either too simple, simplifying the droplet / bubble, and not showing the complex effect of interface change in two-phase flow, with poor reliability; or too complex, considering phase change and other processes together, which makes it difficult to accurately distinguish the influence of two-phase flow on heat transfer process, with poor feasibility. SUMMARY

[0009] In order to solve the problems existing in the prior art, the present application aims to provide a numerical simulation method and system for two-phase flow heat transfer. The present application adds the temperature field into the flow field as a passive scalar on the basis of adaptive mesh, which improves the applicable range of the numerical simulation method, the reliability of the simulation results, and the convenience of analyzing problems.

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

[0011] S01, according to the simulation content, setting the physical parameters, mesh parameters and calculation parameters of the simulation content, and initializing the mesh;

[0012] S02, initializing the two-phase parameter field, velocity field and temperature field, and giving the 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 time evolution of the obtained velocity field, the time evolution of the temperature field is obtained by calculating the convection-diffusion equation;

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

[0016] Preferably, 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 phase content, interfacial transfer coefficient and gravitational acceleration of each phase;

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

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

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

[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 comprises:

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

[0024] The time evolution of the physical parameter is calculated using a linear formula in the two-phase model;

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

[0026] Preferably, step S04 comprises:

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

[0028]

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

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

[0031]

[0032] wherein V represents a volume range for integration, and dV represents a microelement volume;

[0033] According to Gauss theorem, the volume integral of the convection term is converted into a flux area integral, which is expressed as:

[0034]

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

[0036] The diffusion term in the convection-diffusion equation is discretized by using a time-implicit backward Euler difference and is expressed as:

[0037]

[0038] wherein Δt represents a time step, T n represents a temperature field at a current time step, T n+1 represents a temperature field at a next time step;

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

[0040] Preferably, step S05 further comprises:

[0041] It is judged whether the calculation number and / or the convergence of the simulation data meet the preset requirement, and if yes, the simulation process is ended, and if not, the iteration is continued to step S03.

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

[0043] A preset temperature gradient threshold is set, the real-time temperature gradient of each region is calculated, it is judged whether the real-time temperature gradient of the region is greater than the temperature gradient threshold, if yes, the grid density of the region is set to a first density, and if not, the grid density of the region is set to a second density, wherein the first density is greater than the second density.

[0044] The numerical simulation system for two-phase flow heat transfer comprises:

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

[0046] An initialization module is configured to initialize two-phase parameter fields, velocity fields and temperature fields, and give boundary conditions;

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

[0048] A second calculation module is configured to obtain the time evolution of the temperature field by calculation of a convection-diffusion equation based on the time evolution of the obtained velocity field.

[0049] an output module for outputting the required simulation data in combination with the time evolution of the resulting two-phase parameter field, velocity field, pressure field and temperature field.

[0050] A computer device of the present application comprises a signal-connected processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being executed by the processor when loaded to perform the numerical simulation method as described above.

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

[0052] The two-phase flow and heat transfer numerical simulation method and system described in the present application has the following advantages:

[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, and the influence of the temperature field on fluid motion can be ignored, which can be regarded as a passive scalar. For example, the typical duration of millimeter-sized droplet collision is on the order of ten milliseconds, and the typical duration of evaporation is on the order of seconds, so the phase change problem of millimeter-sized droplet collision process can be ignored. The simulation method of the present application 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 interact with each other, the relationship between the two is difficult to analyze clearly. The present application regards temperature as a passive scalar to a certain extent for such complex problems, and the method can be used to 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 process of various passive scalars in the two-phase flow field, and has high portability. For example, the spread and diffusion of pollutants in two-phase flow, as long as the reaction of the pollutants on the two-phase flow is ignored and the evolution equation of the passive scalar is satisfied, the simulation method of the present application is applicable. Therefore, the invention of the present application is not only necessary in fluid mechanics and heat transfer, but also has a fundamental role and promoting effect on energy saving and emission reduction (heat energy utilization), environmental improvement (pollution control) and other issues related to national strategy, national economy and sustainable development. BRIEF DESCRIPTION OF DRAWINGS

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

[0057] Figure 2is a three-dimensional interface shape diagram of a certain moment in the process of simulating bubble rising heat transfer according to the embodiment of the application;

[0058] Figure 3 is Figure 2 a temperature distribution diagram of a central section at a corresponding moment;

[0059] Figure 4 is a structural schematic diagram of the computer device.

[0060] Legend: 101-processor, 102-memory. DETAILED DESCRIPTION

[0061] As Figure 1 shown, the numerical simulation method of two-phase flow heat transfer according to the application is mainly based on the adaptive mesh technology in Basilisk, in order to highlight the influence of two-phase flow on the heat transfer process, the fluid dynamics equation and the interface equation are mainly solved, and the temperature field is added to 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-free condition, which is expressed as:

[0063]

[0064] The momentum equation is expressed as:

[0065]

[0066] In the formula, ρ, t, p, μ, 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, and the embodiment does not involve other body forces such as electromagnetic force, so F is the sum of gravity G and interface force F s , in the scenario where gravity G is not considered, then F=F s .

[0068] In the embodiment, since the Volume-Of-Fluid method has good mass conservation, can capture the complex topological structure change of the two-phase interface, and the calculation resource consumption is not high, the Volume-Of-Fluid method is used for numerical simulation.

[0069] In the Volume-Of-Fluid method, the volume fraction (phase fraction) φ V of the grid occupied by a certain phase fluid is used to represent the distribution of two-phase flow and interface, and its evolution equation depends on the convection of the fluid:

[0070]

[0071] where φ V = 1, represents one phase A, φ V = 0, represents the other phase B, 0 < φ V <1 is the phase interface, the density and dynamic viscosity of the fluid can be represented 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] where ρ A , ρ B , μ A , μ B represent the density and dynamic viscosity of the two phases A and B, respectively;

[0074] The interfacial force is:

[0075] F s = σKn V

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

[0077]

[0078] The above-mentioned velocity divergence 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, bidirectional coupling, forming a complex enough motion system.

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

[0080]

[0081] where T represents temperature, t represents evolution time, u represents the obtained velocity field, represents the gradient operator, and D represents the thermal diffusion coefficient. Illustratively, the two-phase flow equation is not affected by T, so T essentially represents the evolution of a passive scalar.

[0082] As can be known from the above introduction, the control equation group used in the simulation method of the embodiment is composed of the above-mentioned velocity divergence 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 in the process of droplet collision, heat transfer in the process of bubble rising in the gravitational field, heat transfer in the process of droplet breaking in the turbulent flow, etc., setting the physical parameters, grid parameters and calculation parameters of the simulation content, and initializing the grid; wherein 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 phase content, interfacial 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 the boundary conditions, such as periodic boundary, wall boundary, constant temperature wall or adiabatic wall; in this step, the advantage of grid self-adaptation is used to adjust the grid, and the distribution of the grid is changed according to the characteristics of the flow field, and the grid is encrypted in the area with rich structure (such as near the two-phase interface or the wall boundary), so as to improve the accuracy of numerical simulation, on the other hand, without significantly increasing the calculation amount.

[0088] Specifically, according to the characteristics of the flow field, the distribution of the grid can be adjusted statically, dynamically, or a combination of the two.

[0089] Static adjustment specifically refers to: before numerical simulation, according to the structural richness of each region of the expected flow field, setting the grid density, for example, dividing the structural richness into several levels, each level corresponds to different grid density, according to the level corresponding to the structural richness of each region of the expected flow field, setting the grid density, so as to realize setting different grid densities for regions with different structural richness.

[0090] Dynamic adjustment specifically refers to: according to the real-time change of the structural richness of each region of the flow field in the simulation process, dynamically adjusting the grid density.

[0091] In the process of static adjustment and dynamic adjustment, the grid density is positively correlated with the structural richness, that is, in the region with higher structural richness, the grid density is set higher, so as to ensure that in the region with more structure, the accuracy of capturing physical changes is higher.

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

[0093] When multiple indexes are used to represent the structural richness of the region, an index fusion strategy can be considered, for example, configuring a weight coefficient of the index according to the influence degree of each index on the structural richness, standardizing each index to make each index have a unified dimension and numerical range, applying principal component analysis (PCA) to fuse the standardized indexes into a comprehensive index, and using the comprehensive index to represent the structural richness of the region. Compared with a single index, the comprehensive index can represent the structural richness more comprehensively.

[0094] In addition, the flow field can be divided into a key region and a non-key region according to the importance of the region to the simulation result. In the embodiment, since the core idea of the application is to add the temperature field as a passive scalar into the flow field, the temperature should be taken as the main index when distinguishing the key region and the non-key region. Specifically, a temperature gradient threshold is preset, the real-time temperature gradient of each region is calculated, and it is judged whether the real-time temperature gradient of the region is greater than the temperature gradient threshold. If yes, it indicates that the temperature change of the region is relatively rapid, and the grid density of the region is set to a first density. Otherwise, it indicates that the temperature change of the region is relatively gentle, and the grid density of the region is set to a second density. 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 regions, and the computing resources can be reasonably allocated.

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

[0096]

[0097] The time evolution of the physical parameter is calculated using a linear formula in the two-phase model; the linear formula is represented 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 equation is represented as:

[0101]

[0102] S04, based on the time evolution of the resulting velocity field, the time evolution of the temperature field is obtained by calculating the convection-diffusion equation;

[0103] Specifically, as known from the foregoing, the temperature field satisfies the convection-diffusion equation, which is expressed as:

[0104]

[0105] where T represents temperature, t represents evolution time, u represents the resulting velocity field, represents a gradient operator, and D represents a thermal diffusion coefficient;

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

[0107]

[0108] where V represents the volume range for integration, and dV represents the infinitesimal volume;

[0109] According to Gauss's theorem, the volume integral of the convection term is converted into the area integral of the flux, which is 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 discretized using a time-implicit backward Euler difference, which is expressed as:

[0113]

[0114] where Δt represents the time step, T n represents the temperature field at the current time step, and T n+1 represents the temperature field at the next time step;

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

[0116] S05, in combination with the time evolution of the resulting two-phase parameter field, velocity field, pressure field, and temperature field, the required simulation data is output.

[0117] Through steps S01-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, simulation data can be output according to requirements. For example, to observe the dynamic cloud chart, the velocity field and pressure field can be output, and the vorticity field, momentum field, dissipation rate field, pseudo-vortex energy field and other full-field data can 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 situation of a line or a 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 the simulation data is output in step S05, it is also necessary to determine whether the calculation step number and / or the convergence of the simulation data meets the preset requirements, if yes, the simulation process is ended, if not, the iteration is continued to step S03.

[0119] Specifically, if the simulation content is a steady-state problem, it is mainly checked whether the convergence meets the calculation requirements of the physical problem, and for a transient problem, it is mainly checked whether the calculation step number meets the requirements of the problem.

[0120] Based on the numerical simulation method of the embodiment, the inventors simulate the bubble rising and heat transfer on the Basilisk platform. The specific implementation steps are as follows:

[0121] 【1】Preparation of conventional algorithm for incompressible two-phase flow direct numerical simulation. For this purpose, the numerical discrete algorithm of NS equation and the two-phase flow model algorithm (volume of fluid method) are called.

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

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

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

[0125] 【5】Initialization. The main initialized quantities are: velocity field, pressure field, phase fraction field describing two phases, and passive scalar representing temperature field. The initialization results are closely related to the specific physical problem studied. For the bubble rising problem, the initial time can be set as: 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 the gravitational acceleration. Since the bubble rises and floats up due to the action of gravity, the gravitational acceleration is added here.

[0127] 【7】Under the action of the control equation, the velocity field, pressure field, phase fraction field and temperature field evolve iteratively with time steps.

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

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

[0130] The present application adds the temperature field as a passive scalar into the flow field on the basis of the adaptive grid, which improves the application range of the numerical simulation method, the reliability of the simulation results, and the convenience of analyzing the problem.

[0131] The embodiment also provides a numerical simulation system of two-phase flow heat transfer, which comprises:

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

[0133] An initialization module is configured to initialize two-phase parameter fields, velocity fields and temperature fields, and give boundary conditions;

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

[0135] A second calculation module is configured to calculate the time evolution of the temperature field by using a convection-diffusion equation based on the time evolution of the velocity field;

[0136] A simulation output module is configured to output the required simulation data by combining the time evolution of the two-phase parameter fields, velocity fields, pressure fields and temperature fields.

[0137] The system of the embodiment and the method described above belong to the same inventive concept, and can be understood by referring to the description above, which will not be repeated here.

[0138] As Figure 4 shown, the embodiment also provides a computer device including a processor 101 and a memory 102 connected by a bus signal, and the memory 102 stores at least one instruction or at least one program, and the at least one instruction or the at least one program is executed by the processor 101 to perform the numerical simulation method as described above. The memory 102 can be used to store software programs and modules, and the processor 101 performs 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 operating systems, 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 magnetic disk storage device, a flash memory device, or other volatile solid-state memory device. Accordingly, the memory 102 can also include a memory controller to provide access for the processor 101 to the memory 102.

[0139] The method provided by the embodiment of the application can be executed in a computer terminal, a server or a similar computing device, that is, the computer device can include a computer terminal, a server or a similar computing device. The internal structure of the computer device can include but is not limited to a processor, a network interface and a memory. The processor, the network interface and the memory in the computer device can be connected by a bus or other means.

[0140] The processor 101 (or CPU (Central Processing Unit)) is the computing core and control core of the computer device. The network interface can optionally include a standard wired interface, a wireless interface (such as WI-FI, a mobile communication interface, etc.). The memory 102 is a memory device in the computer device, used to store programs and data. It can be understood that the memory 102 here can be a high-speed RAM storage device, or a non-volatile memory device, for example, 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 that stores an operating system of the electronic device, which can include but is not limited to: a Windows system (an operating system), a Linux (an operating system), an Android (a mobile operating system) system, an IOS (a mobile operating system) system, etc., and the present application does not make any limitation thereto; 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 application, 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 application also provides a computer readable storage medium having at least one instruction or at least one program stored thereon, which is loaded by the processor 101 to execute the numerical simulation method as described above. 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 application is implemented.

[0142] According to the embodiment of the present application, the computer readable storage medium can be a non-volatile computer readable storage medium. For example, it can 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 of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program, which can be used by or in conjunction with an instruction execution system, device or apparatus.

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

Claims

1. A numerical simulation method of two-phase flow heat transfer, which uses a volume of fluid method for numerical simulation, characterized by, The numerical simulation method comprises the following steps: S01, according to the simulation content, setting the physical parameters, grid parameters and calculation parameters of the simulation content, and initializing the grid; S02, initializing the two-phase parameter field, velocity field and temperature field, and giving the boundary condition; S03, calculating the time evolution of the two-phase parameter field, velocity field and pressure field using a two-phase flow model; S04, based on the time evolution of the obtained velocity field, calculating the time evolution of the temperature field by solving the convection-diffusion equation; S05, combining the time evolution of the obtained two-phase parameter field, velocity field, pressure field and temperature field, outputting the required simulation data; Step S04 comprises: The temperature field satisfies the convection-diffusion equation, which is expressed as: ； where T denotes the temperature, t denotes the evolution time, u denotes the resulting velocity field, denotes the gradient operator, D denotes the thermal diffusion coefficient; the convection term in the convection-diffusion equation is expressed by the volume integral ； wherein V represents the volume range over which the integration is performed, represents the volume of the infinitesimal volume element; According to Gauss theorem, the volume integral of the convection term is converted into a flux area integral, expressed as: ； wherein S denotes a boundary surface of the volume range V, element vector representing the boundary surface S; The diffusion term in the convection-diffusion equation is discretized using a time-implicit backward Euler difference is represented as ； wherein, denotes a time step, denotes the temperature field of the current time step, denotes the temperature field of the next time step; The convection term and the diffusion term in the same time step are calculated, and the time evolution of the temperature field is obtained by solving the convection-diffusion equation.

2. The method of numerical simulation of 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 phase content, interfacial 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 method of claim 1, wherein Further comprising: In step S02, according to the structural richness of each region of the expected flow field, the grid density is set, and / or in step S03 and step S04, according to the real-time change of the structural richness of each region of the flow field in the simulation process, the grid density is dynamically adjusted, 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 method of numerical simulation of two-phase flow heat transfer according to claim 1, characterized in that, Step S03 comprises: The fluid volume method is used to calculate the two-phase parameter field to obtain the time evolution of the shape and topological structure of the interface; The linear formula in the two-phase model is used to calculate the time evolution of the physical parameters; The continuity equation and Navier-Stokes equation are used to calculate the time evolution of the velocity field and pressure field.

5. The method of numerical simulation of two-phase flow heat transfer according to claim 1, characterized in that, Step S05 further comprises: Judging whether the calculation step number and / or the convergence of the simulation data meets the preset requirement, if yes, ending the simulation process, if not, returning to step S03 for iteration.

6. The method of numerical simulation of two-phase flow heat transfer according to claim 3, characterized in that, According to the real-time change of the structural richness of each region of the flow field in the simulation process, the grid density is dynamically adjusted, which specifically comprises: A temperature gradient threshold is preset, the real-time temperature gradient of each region is calculated, it is judged whether the real-time temperature gradient of the region is greater than the temperature gradient threshold, if yes, the grid density of the region is set to a first density, otherwise the grid density of the region is set to a second density, wherein the first density is greater than the second density.

7. A numerical simulation system of two-phase flow heat transfer, characterized by, Comprise: A parameter setting module for setting the physical parameters, grid parameters and calculation parameters of the simulation content according to the simulation content, and initializing the grid; An initialization module for initializing the two-phase parameter field, velocity field and temperature field, and giving the boundary condition; a first calculation module for calculating time evolution of the two-phase parameter field, velocity field and pressure field using a two-phase flow model; a second calculation module for calculating time evolution of the temperature field by solving a convection-diffusion equation based on time evolution of the obtained velocity field; an output module for outputting simulation data required by combining time evolution of the obtained two-phase parameter field, velocity field, pressure field and temperature field; the temperature field satisfies a convection-diffusion equation, which is expressed as: ； where T denotes the temperature, t denotes the evolution time, u denotes the resulting velocity field, denotes the gradient operator, D denotes the thermal diffusion coefficient; the convection term in the convection-diffusion equation is expressed by the volume integral ； wherein V represents the volume range over which the integration is performed, represents the volume of the infinitesimal volume element; According to Gauss theorem, the volume integral of the convection term is converted into a flux area integral, expressed as: ； wherein S denotes a boundary surface of the volume range V, element vector representing the boundary surface S; The diffusion term in the convection-diffusion equation is discretized using a time-implicit backward Euler difference is represented as ； wherein, denotes the time step, denotes the temperature field of the current time step, denotes the temperature field of the next time step; the time evolution of the temperature field is calculated by solving the convection-diffusion equation.

8. A computer device comprising a processor and a memory connected by a signal, characterized in that, the memory stores at least one instruction or at least one program, which is loaded by the processor to execute the numerical simulation method according to any one of claims 1-6.

9. A computer-readable storage medium having stored thereon, at least one instruction or at least one piece of program, characterized in that, the at least one instruction or the at least one program is loaded by the processor to execute the numerical simulation method according to any one of claims 1-6.

Images