Micro-channel fluid simulation method and system
The D2Q9 model was constructed using the lattice Boltzmann method to initialize and simulate the flow field, temperature field, and phase field. This solved the problems of accuracy and efficiency in fluid simulation at the microscale and enabled high-precision simulation of microchannel flow and heat transfer.
Patent Information
- Application Number
- CN202511348663.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-21
- Publication Date
- 2026-01-27
AI Technical Summary
Existing fluid dynamics simulation methods struggle to accurately handle complex boundaries at the microscale, are highly dependent on mesh generation, and are complex to handle multi-physics coupling, especially when dealing with two-phase interface evolution, temperature gradient-driven processes, or capillary force-dominated processes, resulting in poor simulation accuracy.
The D2Q9 model is constructed using the lattice Boltzmann method. The distribution functions of the flow field, temperature field, and phase field are initialized, boundary conditions are set, and the motion of fluid particles and energy transfer are simulated using the single-relaxation lattice Boltzmann method. Macroscopic physical quantities are calculated, and the simulation results are output.
It improves the accuracy and computational efficiency of microchannel flow simulation, simplifies the handling of complex boundary conditions, and is applicable to microchannel flow and heat transfer processes, thereby enhancing simulation accuracy and efficiency.
Smart Images
Figure CN121413482A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of fluid mechanics technology, and in particular relates to a microchannel fluid simulation method and system. Background Technology
[0002] Microchannel fluid flow has wide applications in cutting-edge fields such as microfluidics, biomedicine, electronic cooling, energy systems, and micro / nano fabrication. Because the characteristic scale of microchannel structures is typically on the micrometer to millimeter scale, the flow process exhibits significant microscale effects, including interface dominance, enhanced wall effects, strong sensitivity to two-phase transitions, and significant temperature gradients. Therefore, how to efficiently and accurately model and numerically simulate fluid behavior within microchannels is a key problem that urgently needs to be solved in current research and engineering practice.
[0003] Currently, fluid dynamics simulation methods, such as the finite element method, finite difference method, or finite volume method, have achieved success in many fluid flow simulations. However, under microscale conditions, these methods face many challenges, such as difficulty in handling complex boundaries, strong mesh generation dependence, complexity in handling multiphysics coupling, numerical instability and low computational efficiency when capturing two-phase interfaces and thermally driven behavior. In particular, the accuracy of microchannel fluid simulations is poor when dealing with two-phase interface evolution, temperature gradient driven processes, or capillary force-dominated processes. Summary of the Invention
[0004] In view of this, embodiments of the present invention provide a microchannel fluid simulation method and system to solve the problem of poor accuracy in current microchannel fluid simulation.
[0005] In a first aspect of the present invention, a microchannel fluid simulation method is provided, comprising: Based on the microchannel geometry to be simulated, a D2Q9 model is constructed using the lattice Boltzmann method. The basic parameters of the D2Q9 model are set, and the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions, are initialized. Based on the single-relaxed lattice Boltzmann method, collision and propagation operations are performed on the distribution functions of the flow field, temperature field and phase field respectively to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface. Set the boundary conditions for the D2Q9 model, and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. When the D2Q9 model meets the preset simulation termination conditions, the simulation results of the D2Q9 model will be output in a standard data format.
[0006] In a second aspect of the present invention, a microchannel fluid simulation system is provided, comprising: The model building module is used to construct a D2Q9 model based on the microchannel geometry to be simulated using the lattice Boltzmann method, and to set the basic parameters of the D2Q9 model, initialize the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions. The collision evolution module is used to perform collision and propagation operations on the distribution functions of the flow field, temperature field and phase field based on the single relaxed lattice Boltzmann method, respectively, to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface; The fluid simulation module is used to set the boundary conditions of the D2Q9 model and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. The results output module is used to output the simulation results of the D2Q9 model in a standard data format when the D2Q9 model meets the preset simulation termination conditions.
[0007] In a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect of the present invention.
[0008] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present invention.
[0009] In this embodiment of the invention, a D2Q9 model is constructed using the lattice Boltzmann method, various distribution functions are evolved, boundary conditions are set, and macroscopic physical quantities such as velocity field, pressure field, temperature field, and order parameter are calculated and output based on the evolution results, thereby realizing microchannel fluid simulation. This not only improves the accuracy of flow simulation inside microchannels, but also ensures computational efficiency, reduces computational complexity, and simplifies the handling of complex boundary conditions, thus better meeting the actual needs of microchannel flow simulation. Attached Figure Description
[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0011] Figure 1 A schematic flowchart of a microchannel fluid simulation method provided in one embodiment of the present invention; Figure 2This is a schematic diagram of the velocity direction of the D2Q9 model provided in one embodiment of the present invention; Figure 3 This is a schematic diagram of microchannel fluid operation provided in one embodiment of the present invention; Figure 4 A schematic diagram of a fluid velocity field provided for one embodiment of the present invention; Figure 5 A schematic diagram of a fluid temperature field provided in one embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of a microchannel fluid simulation system provided in one embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. Detailed Implementation
[0012] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0013] It should be understood that the terms "comprising" and other similar expressions in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, or apparatus that includes a series of steps or units and is not limited to the listed steps or units. Furthermore, "first" and "second" are used to distinguish different objects and are not intended to describe a specific order.
[0014] Please see Figure 1 A flowchart illustrating a microchannel fluid simulation method provided in this embodiment of the invention includes: S101. Based on the microchannel geometry to be simulated, construct the D2Q9 model using the lattice Boltzmann method, set the basic parameters of the D2Q9 model, and initialize the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions. The lattice Boltzmann method is a computational fluid dynamics method that simulates fluid motion by solving the discrete Boltzmann equations at the mesoscale. The D2Q9 model is a two-dimensional discrete velocity model in the lattice Boltzmann method, which has nine velocity directions and can be used for two-dimensional fluid motion simulation.
[0015] The basic parameters include time step, grid spacing, relaxation time, and other parameters.
[0016] Specifically, a two-dimensional computational domain is constructed, and the model is discretized into a uniform grid using a D2Q9 lattice structure.
[0017] A two-dimensional computational domain is constructed using a D2Q9 lattice structure. In the D2Q9 model, each fluid element is simplified to nine particle distribution directions, and their discrete velocity directions are defined as follows:
[0018]
[0019] like Figure 2 As shown, direction c0 represents rest, directions c1 to c4 correspond to the four basic horizontal and vertical directions (right, up, left, down), and directions c5 to c8 correspond to the diagonal directions (upper right, upper left, lower left, lower right). Each direction has a corresponding velocity vector. Its length is one grid, that is, a unit distance. Examples include images of microchannel geometry, such as... Figure 3 As shown, the computational domain is discretized into There are 1 grid points, and the droplet radius is 1 grid point. The center of the droplet is located The bottom base is constructed using a D2Q9 lattice structure. Boundary conditions include: a constant low temperature at the top. The bottom has a linear temperature gradient, that is Apply boundary conditions to the sidewalls .
[0020] At each grid point, initialize the following physical parameters: fluid density Initial velocity Initial order parameters and specific heat capacity These parameters can be replaced by the following dimensionless parameters, including: Reynolds number. capillary number Marangoni number And Bond Number ,in, Represents the characteristic velocity of the system. g It is gravity, and A and B represent two different fluids. Represents reference temperature T c The surface tension below.
[0021] Simultaneously, initialize the flow field distribution function. Phase field distribution function and temperature field distribution function ; Initialize the flow field equilibrium distribution function ,in, Initialize the phase field equilibrium distribution function. and the equilibrium distribution function of the temperature field ,in, p It's pressure. ρ It is density, u is the velocity vector, that is , It is an ordinal parameter. T It's temperature. It is the weighting coefficient. It is the speed of sound in the lattice, defined as follows in lattice units: To ensure numerical accuracy and stability, the weighting coefficients... The possible values are as follows: .
[0022] S102. Based on the single-relaxed lattice Boltzmann method, collision and propagation operations are performed on the distribution functions of the flow field, temperature field and phase field respectively to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface. In the lattice Boltzmann method, the collision step is a key process for simulating the interaction of fluid particles. It can be described as the process in which fluid particles interact on grid nodes within a discrete time step and redistribute the particle velocity distribution according to local density and velocity. The propagation (or migration) step is the process of propagating the distribution function after the collision step to adjacent grid nodes according to the discrete velocity model. This step simulates the movement of fluid particles in space, so that the distribution function can move to the next grid point along a specific direction.
[0023] Optionally, a relaxation time can be set for each type of physical field, and an external force term related to the temperature gradient and interfacial tension can be added during the evolution process.
[0024] Setting appropriate relaxation times for each type of physical field and introducing external force terms related to temperature gradients, interfacial tensions, etc. during the evolution process can improve the stability and accuracy of the model under multi-physics coupling conditions.
[0025] The flow field distribution function is evolved to solve for the velocity and pressure fields. The specific evolution formula is as follows: ; In the formula, and The distribution function and equilibrium distribution function of the flow field, and the relaxation time. , It is kinematic viscosity. External force term. ,in, G represents surface tension, I represents volume force, and G represents unit tensor.
[0026] The temperature field distribution function is evolved to obtain the temperature field distribution. The specific evolution formula is as follows: ; In the formula, and Represents the distribution function and equilibrium distribution function of the temperature field, and the relaxation time. External force item .
[0027] The phase field distribution function is evolved to describe the two-phase interface; the specific evolution formula is as follows: ; In the formula, and Represents the phase field distribution function and equilibrium distribution function, relaxation time. , It is the phase-field mobility. External force term. ,in, W Indicates the interface thickness.
[0028] S103. Set the boundary conditions of the D2Q9 model, and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after the collision propagation. Boundary conditions are crucial for simulating the interaction between fluids and solid walls or other boundaries, affecting computational accuracy and physical realism. The macroscopic physical quantities include velocity, pressure, temperature, and phase sequence parameters. Calculating these macroscopic physical quantities at each moment describes the overall behavior of the fluid.
[0029] In this model, no-slip flow boundaries, adiabatic / isothermal thermal boundaries, and contact angle wetting boundaries are set as boundary conditions. Setting multiple physical boundary conditions, such as no-slip flow boundaries, adiabatic or isothermal thermal boundaries, and contact angle wetting boundaries, at the microchannel boundaries ensures that the simulation process accurately reflects microscale boundary behavior.
[0030] Preferably, a contact angle wetting boundary condition is set at the phase interface, as shown in the following formula: ; In the formula, , The order parameters below the first mesh layer can be represented by... Calculated.
[0031] Based on the updated particle distribution and motion, the macroscopic physical quantities at each grid point are updated according to the evolution rules of the lattice Boltzmann model, including: speed ; pressure ; temperature ; Ordinal parameters .
[0032] S104. When the D2Q9 model meets the preset simulation termination conditions, the simulation results of the D2Q9 model will be output in a standard data format.
[0033] The simulation termination condition is preset to ensure that the simulation process terminates after reaching a steady state. If the condition is met, the simulation ends; otherwise, iterative calculations of the macroscopic physical quantities of the fluid continue for the next time step.
[0034] The preset simulation termination conditions are: the number of iteration steps reaches a predetermined maximum limit, the iteration residual reaches a preset standard value, or the velocity change of all grid points satisfies the convergence condition.
[0035] The number of iterations reaches the maximum limit or a stable state, such as Γ steps; the velocity changes at all grid points satisfy the convergence criterion: Where Γ represents the maximum number of iterations, preferably 1,000,000 steps. ε This represents a preset error threshold, preferably 10. -6 .
[0036] Optionally, the velocity field, temperature field, and two-phase interface structure can be visualized using visualization technology. The simulation results are output in a standard data format, and the velocity field, temperature field, and two-phase interface structure are visualized using visualization technology, providing a reference for microchannel design and performance optimization.
[0037] Preferably, the results are graphically displayed using Tecplot post-processing software, such as the velocity field. Figure 4 As shown, the black lines represent the streamlines of the flow field, the red lines represent the droplet interface, and the blue arrows represent the velocity field distribution. The temperature field is as follows. Figure 5 As shown, the black lines represent the temperature field distribution, and the red lines represent the droplet interface.
[0038] In this embodiment, a two-dimensional computational domain is constructed and discretized using a D2Q9 lattice structure; the distribution functions of the flow field, temperature field, and phase field are initialized; various distribution functions are evolved based on a single-relaxation-time lattice Boltzmann model, while introducing relevant external force terms such as temperature gradient and interfacial tension; boundary conditions are set to reflect microscale wetting, thermal boundary, and flow boundary behavior; macroscopic physical quantities such as velocity field, pressure field, temperature field, and order parameter are calculated; the simulation is terminated according to a preset convergence criterion; and the results are output for visualization. This method has a simple structure, high numerical stability, and is easy to handle complex boundaries and multiphysics coupling, making it suitable for high-precision numerical simulation of two-phase flow and heat transfer processes in microchannels. This method can effectively improve computational efficiency and, while ensuring simulation accuracy, simplify the handling of complex boundary conditions, thus better meeting the practical needs of microchannel flow simulation. It overcomes the limitations of traditional methods in simulating complex microscale coupling behavior and improves simulation efficiency and accuracy.
[0039] Meanwhile, its inherent advantages in handling complex geometric boundaries and two-phase interfaces significantly improve the accuracy of flow simulation within microchannels; by introducing external force terms, it enhances the model's response to temperature gradients and interface effects, which helps to accurately capture flow behavior driven by thermocapillaries; this method is easy to implement in parallel computing, is suitable for large-scale numerical simulation tasks, has high computational efficiency, and is suitable for practical engineering applications.
[0040] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. Figure 6 This is a schematic diagram of a microchannel fluid simulation system provided in an embodiment of the present invention. The system 60 includes: The model building module 610 is used to construct a D2Q9 model based on the microchannel geometry to be simulated using the lattice Boltzmann method, and to set the basic parameters of the D2Q9 model, initialize the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions. The construction of the D2Q9 model using the lattice Boltzmann method includes: A two-dimensional computational domain is constructed, and the model is discretized into a uniform grid using a D2Q9 lattice structure.
[0041] The collision evolution module 620 is used to perform collision and propagation operations on the distribution functions of the flow field, temperature field and phase field based on the single relaxed lattice Boltzmann method, respectively, to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface. Optionally, a relaxation time can be set for each type of physical field, and an external force term related to the temperature gradient and interfacial tension can be added during the evolution process.
[0042] The fluid simulation module 630 is used to set the boundary conditions of the D2Q9 model and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. The boundary conditions for setting the D2Q9 model include: The D2Q9 model uses no-slip flow boundary, adiabatic / isothermal thermal boundary, and contact angle wetting boundary as boundary conditions.
[0043] The macroscopic physical quantities include velocity, pressure, temperature, and order parameters.
[0044] The result output module 640 is used to output the simulation results of the D2Q9 model in a standard data format when the D2Q9 model meets the preset simulation termination conditions.
[0045] Optionally, the preset simulation termination condition is that the number of iteration steps reaches a predetermined maximum limit, the iteration residual reaches a preset standard value, or the velocity change of all grid points satisfies the convergence condition.
[0046] Optionally, the result output module 640 includes: The visualization unit is used to display the velocity field, temperature field, and two-phase interface structure through visualization technology.
[0047] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0048] Figure 7 This is a schematic diagram of an electronic device according to an embodiment of the present invention. The electronic device is used for microchannel fluid simulation. Figure 7 As shown, the electronic device 7 of this embodiment includes a memory 710, a processor 720, and a system bus 730. The memory 710 includes an executable program 7101 stored thereon. As those skilled in the art will understand, Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0049] The following is combined with Figure 7 A detailed introduction to each component of the electronic device: The memory 710 can be used to store software programs and modules. The processor 720 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 710. The memory 710 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as cached data), etc. In addition, the memory 710 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.
[0050] The memory 710 contains an executable program 7101 with a network request method. The executable program 7101 can be divided into one or more modules / units, which are stored in the memory 710 and executed by the processor 720 to perform microchannel fluid simulation, etc. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, describing the execution process of the computer program 7101 in the electronic device 7. For example, the computer program 7101 can be divided into functional modules such as a model building module, a collision evolution module, a fluid simulation module, and a result output module.
[0051] The processor 720 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 710, and by calling data stored in the memory 710, it performs various functions and processes data, thereby monitoring the overall status of the electronic device. Optionally, the processor 720 may include one or more processing units; preferably, the processor 720 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, application programs, etc., and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 720.
[0052] The system bus 730 is used to connect various functional components within the computer, transmitting data, address, and control information. Its type can be, for example, a PCI bus, an ISA bus, or a CAN bus. Instructions from the processor 720 are transmitted to the memory 710 via the bus, and the memory 710 sends data back to the processor 720. The system bus 730 handles the data and instruction exchange between the processor 720 and the memory 710. Of course, the system bus 730 can also connect to other devices, such as network interfaces and display devices.
[0053] In this embodiment of the invention, the executable program executed by the processor 720 included in the electronic device includes: Based on the microchannel geometry to be simulated, a D2Q9 model is constructed using the lattice Boltzmann method. The basic parameters of the D2Q9 model are set, and the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions, are initialized. Based on the single-relaxed lattice Boltzmann method, collision and propagation operations are performed on the distribution functions of the flow field, temperature field and phase field respectively to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface. Set the boundary conditions for the D2Q9 model, and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. When the D2Q9 model meets the preset simulation termination conditions, the simulation results of the D2Q9 model will be output in a standard data format.
[0054] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0055] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0056] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A microchannel fluid simulation method, characterized in that, include: Based on the microchannel geometry to be simulated, a D2Q9 model is constructed using the lattice Boltzmann method. The basic parameters of the D2Q9 model are set, and the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions, are initialized. Based on the single-relaxed lattice Boltzmann method, collision and propagation operations are performed on the distribution functions of the flow field, temperature field and phase field respectively to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface. Set the boundary conditions for the D2Q9 model, and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. When the D2Q9 model meets the preset simulation termination conditions, the simulation results of the D2Q9 model will be output in a standard data format.
2. The method according to claim 1, characterized in that, The construction of the D2Q9 model using the lattice Boltzmann method includes: A two-dimensional computational domain is constructed, and the model is discretized into a uniform grid using a D2Q9 lattice structure.
3. The method according to claim 1, characterized in that, The collision and propagation operations performed on the distribution functions of the flow field, temperature field, and phase field based on the single-relaxation lattice Boltzmann method include: Set the relaxation time for each type of physical field, and add external force terms related to temperature gradient and interfacial tension during the evolution process.
4. The method according to claim 1, characterized in that, The boundary conditions for setting the D2Q9 model include: The D2Q9 model uses no-slip flow boundary, adiabatic / isothermal thermal boundary, and contact angle wetting boundary as boundary conditions.
5. The method according to claim 1, characterized in that, The preset simulation termination conditions are: the number of iteration steps reaches a predetermined maximum limit, the iteration residual reaches a preset standard value, or the velocity change of all grid points satisfies the convergence condition.
6. The method according to claim 1, characterized in that, The macroscopic physical quantities include velocity, pressure, temperature, and order parameters.
7. The method according to claim 1, characterized in that, The step of outputting the D2Q9 model simulation results in a standard data format also includes: The velocity field, temperature field, and two-phase interface structure are displayed using visualization technology.
8. A microchannel fluid simulation system, characterized in that, include: The model building module is used to construct a D2Q9 model based on the microchannel geometry to be simulated using the lattice Boltzmann method, and to set the basic parameters of the D2Q9 model, initialize the distribution functions of the flow field, temperature field, and phase field, as well as the corresponding equilibrium distribution functions. The collision evolution module is used to perform collision and propagation operations on the distribution functions of the flow field, temperature field and phase field based on the single relaxed lattice Boltzmann method, respectively, to simulate the motion between fluid particles, energy transfer and the evolution of the two-phase interface; The fluid simulation module is used to set the boundary conditions of the D2Q9 model and calculate the macroscopic physical quantities of the fluid at each moment to characterize the simulation results based on the evolution of each distribution function after collision propagation. The results output module is used to output the simulation results of the D2Q9 model in a standard data format when the D2Q9 model meets the preset simulation termination conditions.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of a microchannel fluid simulation method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed, it implements the steps of a microchannel fluid simulation method as described in any one of claims 1 to 7.