A fluid simulation method, device, system and storage medium

Abstract

The present application discloses a fluid simulation method, device, system and storage medium, which relate to the field of electrowetting technology. A fluid simulation method includes: acquiring a simulation data set; defining the initial physical field distribution of the device according to the simulation data set; executing a cycle process until a preset condition is met, and determining the current physical field distribution when the preset condition is met as a steady-state distribution state or a target state; wherein the preset condition is that the current phase field change is less than the preset change or the current cycle number is equal to the preset cycle number. The fluid simulation method of the present application can simulate the electrowetting phenomenon of the fluid more accurately, and the simulation effect is closer to reality.

Description

Technical Field

[0001] The present application relates to the field of electrowetting technology, and in particular to a fluid simulation method, device, system and storage medium. Background Art

[0002] In the related technology, electrowetting devices, also called electrowetting devices or electrofluidic devices, are widely used in the fields of microfluidics and electronic displays because of their low energy consumption and high efficiency. In the process of research and development of electrowetting devices, in order to improve efficiency, electrowetting devices are usually simulated by fluids. Fluid simulation will be applied to mathematics, fluid mechanics and computers. Therefore, computational fluid dynamics, as an interdisciplinary subject between mathematics, fluid mechanics and computers, has been widely used in the simulation process of electrowetting devices.

[0003] At present, the simulation of electrowetting devices by computational fluid dynamics usually uses the finite element method to solve the fluid motion state equation. For example, when solving the Navier-Stokes equation by the finite element method, CFD software (simulation computational fluid dynamics software) will be used to perform relevant numerical calculations of the finite element method. However, the finite element method is a method of performing detailed differential processing on the fluid motion equation. This simulation method has high requirements on computer performance, so it will generate high simulation costs. At the same time, the amount of calculation in the differential processing process is large, and the computer needs to spend a long time to process, which will result in a long modeling time and reduce the efficiency of simulation. In addition, this simultaneous simulation method requires high experience from the model designer, and it takes a long time for first-time users to run in, which increases the time cost and further reduces the efficiency of simulation. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a fluid simulation method, device, system and storage medium, which can more accurately simulate the electrowetting phenomenon of the fluid, and the simulation effect is closer to reality.

[0005] The fluid simulation method according to the first aspect of the present application includes:

[0006] Acquire a simulation data set; wherein the simulation data set includes a first simulated physical quantity of the fluid and a plurality of second simulated physical quantities of the device to be electrowetted;

[0007] Defining an initial physical field distribution of the device according to the first physical simulation quantity and the second physical simulation quantity; wherein the physical field is a two-dimensional network model, and each grid point in the two-dimensional grid model corresponds to a different coordinate;

[0008] A loop process is performed on the simulation data set until a preset condition is met, and the current physical field distribution when the preset condition is met is determined as a steady-state distribution state or a target state, wherein the loop process includes:

[0009] Calculate the chemical potential and the free energy density function according to the first simulated physical quantity, the second simulated physical quantity, the phase field calculated by the previous phase field distribution in the previous physical field distribution, and the density field calculated by the previous density field distribution in the previous physical field distribution;

[0010] Calculating a first pressure of the fluid at each grid point according to the chemical potential, the free energy density function, the phase field, and the density field;

[0011] According to the phase field corresponding to the three-phase contact area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution, the first electric field intensity corresponding to the three-phase contact area is corrected to determine the second electric field intensity of each grid point;

[0012] The first pressure and the second electric field strength are coupled to obtain a second pressure at each lattice point;

[0013] According to the second pressure, a current density equilibrium distribution function and a current phase equilibrium distribution function of the fluid are calculated;

[0014] The current physical field distribution of the fluid at each grid point is calculated according to the current phase equilibrium distribution function and the current density equilibrium distribution function; wherein the current physical field distribution includes the current phase field distribution, the current density field distribution, and the current potential distribution;

[0015] Compare the current phase field variation with the preset variation or compare the current cycle number with the preset cycle number;

[0016] Among them, the preset condition is that the current phase field change is less than the preset change or the current cycle number is equal to the preset cycle number.

[0017] According to some embodiments of the present application, obtaining a simulation data set includes the following steps:

[0018] Acquire a plurality of first actual physical quantities of the fluid and a plurality of second actual physical quantities of the device; wherein the plurality of second actual physical quantities include a lateral length L of the device x , device longitudinal length L y , solid dielectric layer thickness d s , electrode position, grid size δ x , time step δ t , the position of the electrodes and the potential V si ;

[0019] Performing dimensionless normalization processing on each of the first actual physical quantities and each of the second actual physical quantities to obtain the first simulated physical quantity corresponding to the first actual physical quantity and the second simulated physical quantity corresponding to the second actual physical quantity;

[0020] The simulation data set is established according to each of the first simulation physical quantities and each of the second simulation physical quantities.

[0021] According to some embodiments of the present application, the initial physical field distribution defined according to the first physical simulation quantity and the second physical simulation quantity includes:

[0022] Define the initial velocity, initial phase field, and initial potential.

[0023] According to some embodiments of the present application, calculating the first pressure of the fluid at each grid point according to the chemical potential and the free energy density function includes:

[0024] The first pressure of the fluid at each grid point is calculated based on the preset wetting potential, the free energy density corresponding to the phase field, the free energy density function, the chemical potential, the first simulated physical quantity, the second simulated physical quantity, and the density field.

[0025] According to some embodiments of the present application, the phase field corresponding to the three-phase contact line region on the two-dimensional grid model, the previous potential distribution in the previous physical field distribution, and the correction of the first electric field strength corresponding to the three-phase contact line region to determine the second electric field strength of each grid point include:

[0026] When the phase field corresponding to the three-phase contact line region falls within a preset range, the first electric field intensity corresponding to the phase field is enhanced according to the previous potential distribution and the preset enhancement formula to obtain the second electric field intensity at each grid point; wherein the enhancement formula is:

[0027] E(φ)=E(φ)*B; where E represents the electric field intensity, φ represents the phase field, E(φ) represents the relationship between the phase field and the electric field intensity, B represents the enhancement coefficient, θ0 represents the contact angle of the fluid when it is stable at the solid interface, δ x Represents the size of each grid point.

[0028] According to some embodiments of the present application, coupling the first pressure and the second electric field strength to obtain the second pressure at each lattice point includes:

[0029] According to the formula Obtaining a joint dielectric constant; wherein ε represents the joint dielectric constant, φ represents the phase field, ε1 represents the first dielectric constant, and ε2 represents the second dielectric constant;

[0030] The second pressure of the fluid at each grid point is calculated based on the joint dielectric constant, the second electric field strength, and the first pressure.

[0031] According to some embodiments of the present application, before executing a loop process on the simulation data set until a preset condition is satisfied and determining the current physical field distribution when the preset condition is satisfied as a steady-state distribution state or a target state, the method includes:

[0032] When the grid point is a boundary point, a rebound algorithm is performed on the velocity parameter in the density distribution function to correct the previous density field distribution of the boundary point.

[0033] According to some embodiments of the present application, before executing a loop process on the simulation data set until a preset condition is satisfied and determining the current physical field distribution when the preset condition is satisfied as a steady-state distribution state or a target state, the process further includes:

[0034] When the grid point is a boundary point, a rebound algorithm is performed on the velocity parameter in the phase distribution function to correct the previous phase field distribution of the boundary point.

[0035] A fluid simulation system according to an embodiment of the third aspect of the present application includes:

[0036] at least one memory;

[0037] at least one processor;

[0038] at least one program;

[0039] The programs are stored in the memory, and the processor executes at least one of the programs to implement the fluid simulation method as described in the embodiment of the first aspect.

[0040] According to the computer-readable storage medium of the fourth aspect embodiment of the present application, the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the fluid simulation method as described in the first aspect embodiment.

[0041] The fluid simulation method according to the embodiment of the present application has at least the following beneficial effects: first, a simulation data set is obtained; wherein the simulation data set includes multiple first simulated physical quantities of the fluid and multiple second simulated physical quantities of the device to be electrowetted; an initial physical field distribution of the device is defined according to the first physical simulation quantity and the second physical simulation quantity; wherein the physical field is a two-dimensional network model, and each grid point in the two-dimensional grid model corresponds to a different coordinate; thereafter, a loop process is performed on the simulation data set until a preset condition is met, and the current physical field distribution when the preset condition is met is determined as a steady-state distribution state or a target state, the loop process comprising: calculating the chemical potential and the free energy density function according to the first simulated physical quantity, the second simulated physical quantity, the phase field calculated by the previous phase field distribution in the previous physical field distribution, and the density field calculated by the previous density field distribution in the previous physical field distribution; and calculating the chemical potential, the free energy density function, the phase field, and the density field according to the chemical potential, the free energy density function, the phase field, and the density field. degree field, and calculate the first pressure of the fluid at each grid point; according to the phase field corresponding to the three-phase contact area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution, correct the first electric field strength corresponding to the three-phase contact area to determine the second electric field strength of each grid point; couple the first pressure and the second electric field strength to obtain the second pressure of each grid point; according to the second pressure, calculate the current density equilibrium distribution function and the current phase equilibrium distribution function of the fluid; according to the current phase equilibrium distribution function and the current density equilibrium distribution function, calculate the current physical field distribution of the fluid at each grid point; wherein the current physical field distribution includes the current phase field distribution, the current density field distribution, and the current potential distribution; compare the current phase field change with the preset change or compare the current number of cycles with the preset number of cycles; wherein the preset condition is that the current phase field change is less than the preset change or the current number of cycles is equal to the preset number of cycles. The fluid simulation method of the present application couples the second electric field strength and the first pressure to obtain the second pressure, and then the density distribution can be calculated through the second pressure; on the one hand, the calculation process is greatly simplified, and the high performance requirements for the computer are reduced by simplifying the amount of calculation; on the other hand, the operator only needs to set the corresponding actual physical quantity to perform the simulation, which greatly reduces the operator's requirements and saves the time cost of learning; finally, by correcting the electric field strength and then coupling the electric field with the fluid field, the parameters obtained by the simulation are more accurate, making the simulated fluid electrowetting phenomenon in the device closer to reality. Therefore, the fluid simulation method of the present application can simulate the electrowetting phenomenon of the fluid more quickly and accurately, and the simulation effect is closer to reality.

[0042] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present application is further described below with reference to the accompanying drawings and embodiments, wherein:

[0044] Figure 1 A schematic diagram of the structure of a fluid simulation system provided by one embodiment of the present application;

[0045] Figure 2 A schematic diagram of a flow chart of a fluid simulation method provided in an embodiment of the present application;

[0046] Figure 3 A schematic diagram showing a comparison of curves of voltage and wetting angle before and after correction of the electric field strength provided in an embodiment of the present application;

[0047] Figure 4 A diagram showing the relationship between dielectric constant distribution and phase field provided in the embodiments of the present application;

[0048] Figure 5 A schematic structural diagram of a fluid simulation system provided in another embodiment of the present application.

[0049] Reference numerals:

[0050] Conductive fluid 100 , dielectric fluid 110 , solid dielectric layer 120 , memory 200 , processor 300 . DETAILED DESCRIPTION

[0051] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as limiting the present application.

[0052] In the description of the present application, it should be understood that descriptions involving orientation, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0053] In the description of this application, "several" means more than one, "more" means more than two, "greater than", "less than", "exceed", etc. are understood to exclude the number itself, and "above", "below", "within", etc. are understood to include the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0054] In the description of this application, initial means the moment when the simulation calculation starts, previous means the moment when the previous cycle ends, and current means the moment corresponding to the current cycle.

[0055] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0056] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0057] The terms in this application are explained below.

[0058] Electrowetting:

[0059] It refers to the phenomenon that the wettability of the droplet on the substrate is changed (i.e., the contact angle is changed) by changing the voltage between the liquid and the insulating substrate, causing the droplet to deform and move. The electrowetting display device was first developed by Liquavista, a professional display manufacturer under Philips, and its research results were published in the journal Nature in 2003. The electrowetting display device usually consists of two structural layers, the upper structural layer consists of an upper substrate, a conductive layer, a support column and a sealing frame, and the lower structural layer consists of a lower substrate, a conductive layer, a hydrophobic insulating layer, and a weakly hydrophilic pixel wall. The pattern of the pixel wall defines the pixels of the display device. The area between the pixel walls is the display area. The pixels are filled with two immiscible fluids, ink and electrolyte solution. The display effect is produced by applying voltage to make the two fluids move. Specifically, when no voltage is applied, the ink spreads on the surface of the hydrophobic layer to display the color of the ink; when voltage is applied, the ink shrinks to display the color of the lower substrate.

[0060] Lattice Boltzmann:

[0061] The Lattice Boltzmann Method (LBM) is a computational fluid dynamics method based on mesoscopic simulation scale. Compared with other traditional CFD calculation methods, this method has the characteristics of a mesoscopic model between a microscopic model and a macroscopic continuous model, so it has the advantages of simple description of fluid interactions, easy setting of boundary conditions, and parallel calculation.

[0062] Free Energy Model:

[0063] The free energy model is based on phase field theory, where the free energy functional is used to account for interfacial tension effects and to describe the evolution of the interfacial dynamics in a thermodynamically consistent manner.

[0064] Young-Lippmann equation:

[0065] describes the change in the wetting angle of a conductive droplet on a parallel substrate before and after the application of an electric potential, where θ and θ0 represent the stable wetting angle of the droplet after the potential difference exists and the equilibrium wetting angle when there is no potential, respectively. s represents the dielectric constant in vacuum and the relative dielectric constant of the solid dielectric layer, V is the potential difference between the positive and negative electrodes, γ is the surface tension of the interface between the two fluids, and d s is the thickness of the solid dielectric layer.

[0066] The numerical simulation method based on lattice Boltzmann theory is used to simulate fluid flow and fluid physics modeling. Different from the traditional numerical method based on solving macroscopic continuous fluid equations, its basic idea is to establish a simplified fluid dynamics model, which greatly improves the calculation speed.

[0067] CFD software (simulation computational fluid dynamics software) for multi-physics field coupling models such as COMSOL, ANSYS, or open source OpenFOAM. The finite element method is used to solve the partial differential decomposition of the fluid motion state equation, such as the Navier Stokes equation (NS equation). Taking COMSOL as an example, the basic process of finite element numerical calculation is: first, the solution domain is divided into several finite element grids; then, the interpolation basis function is used to construct the approximate solution of the quantity to be solved; finally, the weighted residual method or variational principle is used to transform the partial differential equation into a discrete algebraic equation. When the finite element method is used for numerical solution, the field quantity at any point in the solution domain can be obtained by using node interpolation. This method of performing detailed differential processing on the fluid motion equation has high requirements on computer performance and low computational efficiency. At the same time, the mesh division during modeling requires high application experience for the model designer.

[0068] Refer to the following Figure 1 A fluid simulation system according to an embodiment of the present application is described.

[0069] It is understandable that if Figure 1 As shown, the fluid simulation system comprises:

[0070] A device to be electrowetted, the device being provided with a solid dielectric layer 120;

[0071] Fluid, the fluid includes a conductive fluid 100 and a dielectric fluid 110;

[0072] The solid dielectric layer 120, the conductive fluid 100 and the dielectric fluid 110 together form a fluid field.

[0073] In this fluid field, the grid size δ x , time step δ t , the position of the electrodes, the potential V si , the lateral length L of the device x , device longitudinal length L y , solid dielectric layer thickness d s As the second actual physical quantity, it needs to be defined and assigned here. The specific parameters are referenced by the initial technical solution of the device, which can also be understood as a preliminary solution for simulation. Similarly, in this fluid field, the fluid density ρ si , fluid contact interface mobility M si , the surface tension of the two fluid contact surfaces γ si and kinematic viscosity v si , the interface thickness l of the two fluid contact surfaces si , the stable contact angle θ0 of the fluid at the solid interface, the dielectric constant ε1 of the conductive fluid and the dielectric constant ε2 of the dielectric fluid, the size R of the fluid, and the dielectric constant ε of the solid dielectric layer s As the first actual physical quantity of the fluid, they all need to be defined and assigned here. It is worth noting that the above physical quantities are all defined in the International Standard Unit System.

[0074] Refer to the following Figure 2 A fluid simulation method according to an embodiment of the present application is described.

[0075] It is understandable that if Figure 2 As shown, the fluid simulation method includes:

[0076] Step S100, obtaining a simulation data set; wherein the simulation data set includes a first simulated physical quantity of the fluid and a plurality of second simulated physical quantities of the device to be electrowetted.

[0077] It can be understood that obtaining a simulated data set includes the following steps:

[0078] Acquire multiple first actual physical quantities of the fluid and multiple second actual physical quantities of the device; wherein, Figure 2 As shown, the second actual physical quantities include the device lateral length L x , device longitudinal length L y , solid dielectric layer thickness d s , grid size δ x , time step δ t , the position of the electrodes, the potential Vsi ;

[0079] Performing dimensionless normalization processing on each first actual physical quantity and each second actual physical quantity to obtain a first simulated physical quantity corresponding to the first actual physical quantity and a second simulated physical quantity corresponding to the second actual physical quantity;

[0080] A simulation data set is established according to each first simulation physical quantity and each second simulation physical quantity.

[0081] It should be noted that the simulation parameters of the lattice Boltzmann are dimensionless numbers. In order to combine the actual device units with the simulation parameters, a reference unit system needs to be introduced. For each basic physical quantity of the simulation, a corresponding normalized reference value is set. The simulated physical quantity is equal to the dimensionless number obtained by dividing the actual physical quantity by the normalized reference value. Set the normalized reference value ρ of the physical quantity ref , mobility reference value M ref , kinematic viscosity reference value ν ref =(δ x ) 2 / δ t , surface tension reference value γ ref =ρ ref *(δ x ) 3 / (δ t ) 2 And the voltage reference value V ref The reference value is used to normalize the simulated physical quantity. In principle, the specific size of the selected reference value should not affect the actual simulation effect.

[0082] It should be noted that the first simulation physical quantity and the second simulation physical quantity are defined as follows:

[0083] The first simulation physical quantities include: fluid density ρ(x, t), kinematic viscosity ν, dielectric constant ε of the fluid, fluid contact interface mobility M, surface tension γ, interface thickness l of the two fluid contact surfaces, relaxation time τ; wettability of each solid boundary to the fluid θ0, and size R of the fluid; where τ represents the time it takes for the particle distribution to reach an equilibrium state from a non-equilibrium state.

[0084] The second simulated physical quantity includes: device lateral length L x , device longitudinal length L y , solid dielectric layer thickness d s , the position of the electrodes, the potential V app ; Wherein, the electrodes include a positive electrode and a negative electrode.

[0085] All first actual physical quantities and second actual physical quantities are dimensionlessly normalized to obtain first simulated physical quantities corresponding to the first actual physical quantities and second simulated physical quantities corresponding to the second actual physical quantities. The dimensionless physical quantity is equal to the physical quantity of the corresponding actual device divided by the normalized reference value. Physical quantity A=A si / A ref For example, kinematic viscosity ν = ν si / v ref ; Mobility M = M si / M ref , density ρ(x,t)=ρ si / ρ ref , electrode potential V app =V si / V ref , and then the dimensionless values ​​of the above simulated physical quantities are obtained. For example, in practice, the density of the first fluid is ρ si =800KG / m 3 , then the density reference value is set to ρ ref =1000KG / m 3 , the density ρ of the first fluid in numerical simulation is 0.8.

[0086] Step S110, defining the initial physical field distribution of the device according to the first physical simulation quantity and the second physical simulation quantity; wherein the physical field is a two-dimensional network model, and each grid point in the two-dimensional grid model corresponds to a different coordinate.

[0087] It should be noted that, through step S100, a two-dimensional model of the fluid simulation system has been preliminarily built. At this time, the two-dimensional model is subjected to a homogenized grid process to obtain a two-dimensional network model. x , basic time step δ t , the boundary position of the rectangular model, the initial position of the two fluids in the model, the shape and position of the solid material components, and the electrode position. The simulation grid distribution is obtained, and the grid points in the grid are defined as the positions of the particles in the discretized motion. Among them, x and y represent the horizontal and vertical coordinates of the grid points on the simulation grid I (x, y), respectively, and x∈(1,L x / δ x ,y∈(1,L y / δ x ). In the following expressions, x is used to represent the position coordinates (x, y).

[0088] It is worth noting that the initial physical field distribution includes the initial density field distribution, the initial phase field distribution and the initial electric potential distribution. The physical field includes density field, phase field, velocity field and electric potential. The distribution of density field, phase field, velocity field and electric potential in a set area is called physical field distribution. Furthermore, by establishing a network in the set area, a two-dimensional network model can be obtained.

[0089] It can be understood that defining the initial physical field distribution of the device according to the first physical analog quantity and the second physical analog quantity includes:

[0090] Define the initial velocity, initial phase field, and initial potential.

[0091] It is worth noting that by defining the initial velocity, initial phase field and initial electric potential, we can obtain the initial density field distribution, initial phase field distribution and initial electric potential distribution.

[0092] It should be noted that before simulation, the initial values ​​of the parameters need to be defined, and the initial state of the phase field needs to be defined. The initial phase field:

[0093] Where x0=(L x / 2, R0) is the initial center position of the central droplet, and R0 is the droplet radius.

[0094] Define the initial velocity u(x,t=0)=0, the initial electrode potential V app (x, t = 0) = 0, the initial electrode potential V app The variation law with time t is as follows:

[0095]

[0096] In order to ensure the correctness of the electric field iteration, the initial electrode potential V app Gradually increase to V max , and the time used is T Vsetp .

[0097] It should be noted that V max The initial potential V is preset for each simulation. app The dimensionless value of the actual maximum value of .

[0098] The simulation data set is looped until the preset conditions are met, and the current physical field distribution when the preset conditions are met is determined as a steady-state distribution state or a target state. The loop process includes:

[0099] Step S120, calculating the chemical potential and free energy density function according to the first simulated physical quantity, the second simulated physical quantity, the phase field calculated by the previous phase field distribution in the previous physical field distribution, and the density field calculated by the previous density field distribution in the previous physical field distribution.

[0100] It should be noted that the previous physical field distribution can be understood as the initial physical field distribution during the first cycle.

[0101] It should be noted that the free energy model in the lattice-Boltzmann theory is used to treat two immiscible fluids. In order to distinguish the two fluids, the phase fields φ of the conductive fluid and the dielectric fluid are defined as φ = 1 and φ = -1, respectively, so as to quickly distinguish the two fluids during numerical simulation. When -1<φ<1, it is a mixed state of the two fluids, which is mainly concentrated in the contact interface area of ​​the two phase fluids.

[0102] It should be noted that the D2Q9 model (two-dimensional, nine discrete velocity directions) is used to define the discrete physical quantities of the fluid, and the fluid motion velocity is e i , i is the direction sequence of the particle velocity (9 integers of i∈[0,8]), representing the 9 velocity directions of the particle motion, and then the following velocity formula is obtained:

[0103]

[0104] ω i Indicates the weight coefficient corresponding to each direction. According to the thermodynamic conservation law, ω0 = 4 / 9, ω1 = ω2 = ω3 = ω4 = 1 / 9,

[0105] ω5=ω6=ω7=ω8=1 / 36. Set the grid sound velocity c s :

[0106] It should be noted that when defining the initial physical field distribution, what is defined is the initial values ​​of the phase field, density field, velocity field, and electric field, that is, the initial phase field, initial density field, initial velocity field, and initial electric field. Therefore, it is necessary to calculate the phase distribution function g based on the phase field. i (x, t), phase distribution function g i The meaning of (x, t) can be understood as the probability value of the phase field φ of the fluid existing at each grid point x at each time point; and the phase equilibrium distribution function g i eq The meaning of (x, t) can be understood as the value of the phase field φ of the fluid at the position x corresponding to each grid point when the system is in equilibrium; in addition, the phase equilibrium distribution function is also calculated after defining the phase field, and needs to be calculated based on relevant parameters such as chemical potential and phase field. Based on the phase distribution function and the phase equilibrium distribution function, the phase field evolution formula is as follows, also called the phase field distribution:

[0107]

[0108] The phase field relaxation time is usually defined as: g=1; and, in the phase field evolution formula, is the collision process, g i (x+e i δ t ,t+δ t )-g i (x,t) is the migration process.

[0109] At the macroscopic level, the discrete phase field distribution and macroscopic quantities follow the following restrictions:

[0110]

[0111]

[0112]

[0113] In the formula In, e i and u are both matrices, then and u T are all transposes in matrix operations, I represents the simulation network, φ is the phase field, μ is the chemical potential, M' is the viscosity term, Therefore, the phase equilibrium distribution function is given by the formula And the parameters in the formula, such as phase field φ and chemical potential μ, are obtained through comprehensive calculation.

[0114] The gradient and Laplace function of the phase field define the relationship between the phase field and time t and position x, expressed as:

[0115]

[0116]

[0117] It should be noted that u is defined as the velocity field u(x, t) of the fluid, which represents the velocity distribution of each grid point;

[0118] It should be noted that the calculation of the velocity field needs to be based on the restrictive relationship between the phase field equilibrium distribution function and the macroscopic phase function or the restrictive relationship between the density field equilibrium distribution function and the macroscopic density.

[0119] It is worth noting that the phase equilibrium distribution function is the ideal value when the fluid state reaches a stable equilibrium state. Fluid particles tend to the equilibrium state from the current state through continuous collision and migration. In other words, the value of the current phase distribution function tends to the value of the phase equilibrium distribution function through continuous evolution, and finally reaches a stable state. That is, as mentioned below, when the current phase field change is less than the preset change (differential threshold), it can be considered that the phase distribution function and the phase equilibrium distribution function at this time are infinitely close, that is, the fluid reaches a stable state.

[0120] It should be noted that, similarly, after defining the initial density field, it is necessary to calculate the density distribution function f according to the density field. i (x, t), density equilibrium distribution function f i eq (x, t); for the density distribution function f i The meaning of (x, t) can be understood as the probability value of the density ρ distribution of the fluid particles at the position x corresponding to each grid point at each time; for the density equilibrium distribution function f i eq The meaning of (x, t) can be understood as the value of the density ρ of the fluid particles at the position x corresponding to each grid point at each time; the density distribution function f i (x, t) and the density equilibrium distribution function f i eq (x, t) needs to satisfy the restriction relationship with the macroscopic density ρ(x, t):

[0121]

[0122]

[0123]

[0124] The particle motion in the grid is divided into two parts: collision and migration. As collision and migration continue, the fluid field evolves over time until the equilibrium state of particle distribution is reached. The fluid field is in a macroscopically stable state. The collision-migration formula that represents the collision-migration motion, that is, the density field distribution, is as follows:

[0125]

[0126] where f i (x, t) is the distribution state of the particle in the i-th direction at x at time t, f i (x+e i δ t ,t+δ t ) is δ t After time, the particle migrates to x+e by collision i δ t The distribution function in the direction of position i, the kinematic viscosity of the fluid satisfies represents the collision process, f i (x+e i δ t ,t+δ t )-f i (x,t) represents the migration process.

[0127] It should be noted that f i (x, t) is equal to f at the initial t = 0i eq (x, t), then at this moment f i (x+e i δ t ,t+δ t ) The next moment (t = 1) f i (x, t = 1), then it is calculated by the collision migration formula, and so on. i (x,t) and f i (x+e i δ t ,t+δ t ) are obtained by iterative calculation in sequence. i (x, t) has the same calculation method.

[0128] It is worth noting that the density equilibrium distribution function is the ideal value when the fluid state reaches a stable equilibrium state. Fluid particles tend to the equilibrium state from the current state through continuous collision and migration. In other words, the value of the current density distribution function tends to the value of the density equilibrium distribution function through continuous evolution, and finally reaches a stable state. That is, as mentioned below, when the current phase field change is less than the preset change (differential threshold), it can be considered that the density distribution function at this time is infinitely close to the density equilibrium distribution function, that is, the fluid reaches a stable state.

[0129] It should be noted that the calculation of phase field by phase field distribution and density field by density field distribution have been introduced above. For chemical potential and free energy density function, the calculation process is as follows:

[0130] The chemical potential is calculated based on the phase field of the fluid, the first simulated physical quantity, and the second simulated physical quantity; the chemical potential function is as follows:

[0131] Chemical potential:

[0132] It should be noted that the free energy density function is calculated based on the phase field of the fluid, the first simulated physical quantity, the second simulated physical quantity, and the density field of the fluid; wherein the density field has an indirect relationship with the free energy through the pressure, therefore, the influence of the density field on the free energy needs to be considered; the free energy density function is as follows:

[0133]

[0134] According to the phase field, chemical potential, the first simulated physical quantity, the second simulated physical quantity, and the free energy density function of the fluid, the free energy F of the fluid field can be calculated when there is no electric field:

[0135]

[0136] Where Ω is the volume of the fluid region and S is the surface area of ​​the fluid region.

[0137] Wetting potential:

[0138]

[0139] Determines the wetting ability of the fluid on the surface of the solid dielectric layer.

[0140] Step S121, calculating the first pressure of the fluid at each grid point according to the chemical potential, the free energy density function, the phase field and the density field.

[0141] It should be noted that the first pressure of the fluid at each grid point can be calculated based on the phase field, density field, the first simulated physical quantity, the second simulated physical quantity, chemical potential, and free energy density function.

[0142] The pressure tensor P of the fluid is a mechanical factor that affects the movement of the fluid. It is the volume density of energy. When no electric field is applied, it is the first pressure, and the expression is:

[0143]

[0144] Step S122, correcting the first electric field strength corresponding to the three-phase contact area according to the phase field corresponding to the three-phase contact area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution to determine the second electric field strength of each grid point.

[0145] It should be noted that the introduction of the potential distribution function h i (x,y,t), to represent the probability of the potential changing at time t at the position (x,y) represented by x and in the direction i:

[0146]

[0147] The distribution function in equilibrium state can also be called potential equilibrium distribution function: τ h =1.

[0148] Set the initial potential V(x,t=0), then h i eq (x, t = 0), set the initial state h i (x,t=0)=h i eq (x,t=0).

[0149] It should be noted that the phase field threshold φ0 of the conductive fluid phase and the dielectric fluid phase is set. In actual situations, when the conductivity of the two-phase fluid differs greatly, the average intermediate state of φ=0 cannot be used as a reference for distinguishing the fluid conductivity of the two-phase fluid mixing area. According to the conductivity of the two-phase fluid in the actual electrowetting device, the corresponding phase field threshold φ0 is determined. Furthermore, the two-phase fluids are water with a relative dielectric constant of 78 and a dielectric ink with a relative dielectric constant of 2, respectively. The threshold φ0=0.45 is set. When φ≥0.45, the fluid is considered to be a dielectric fluid, and when φ<0.45, the fluid is considered to be a conductive fluid.

[0150] For the dielectric fluid phase, the potential ∑ i h i =V, the dielectric fluid follows The distribution of the electric potential V in the dielectric fluid follows:

[0151] Represents the phase function of φ corresponding to different V.

[0152] The conductive fluid is defined as a perfect conductor, and the potential V of the conductive fluid phase is equal to the electrode potential V app ,but When the conductive fluid is defined as a perfect conductor, the electric field strength of the conductive fluid phase according to Calculation shows that the electric field strength of the conductive fluid phase is E=0.

[0153] It should be noted that the Debye length of the double layer in the dielectric fluid is much smaller than the lattice length, and the potential difference U is the regional difference caused by the uneven potential distribution in the device.

[0154] It should be noted that the potential balance distribution function It represents the potential at time t at the position (x, y) represented by x and in the direction i; the potential distribution at time t is represented by the potential balance distribution function, the potential balance distribution function.

[0155] It can be understood that, according to the phase field corresponding to the three-phase contact area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution, the first electric field intensity corresponding to the three-phase contact area is corrected to determine the second electric field intensity of each grid point, including:

[0156] When the phase field corresponding to the three-phase contact area falls within the preset range, the first electric field intensity corresponding to the phase field is enhanced according to the previous potential distribution and the preset enhancement formula to obtain the second electric field intensity of each grid point; wherein the enhancement formula is: E(φ)=E(φ)*B; wherein, E represents the electric field intensity, φ represents the phase field, E(φ) represents the relationship between the phase field and the electric field intensity, B represents the enhancement coefficient, θ0 represents the contact angle of the fluid when it is stable at the solid interface, δ x Represents the size of each grid point.

[0157] It can be understood that the first electric field strength is calculated according to the following formula:

[0158]

[0159] It can be understood that the potential difference U is calculated according to the electric potential, and the potential difference is differentiated to obtain the first electric field strength.

[0160] It should be noted that the preset range of the phase field φ is φ0∈(0.45,0.8), φ0 is called the threshold. When the phase field falls into the preset range, by combining the size of the phase field φ and the potential distribution, the first electric field strength of the three-phase contact area can be enhanced to obtain the second electric field strength.

[0161] It should be noted that for the area in the fluid that is not near the three-phase contact line, that is, For the part (0.45, 0.8), the electric field strength E(φ) does not undergo the above adjustment and still follows the original numerical solution.

[0162] It is worth noting that the second electric field strength is obtained after the above correction. Of course, the first electric field strength without correction is also used as the second electric field strength to calculate the second pressure. The effects before and after correction are as follows: Figure 3 shown.

[0163] Step S123, coupling the first pressure and the second electric field strength to obtain the second pressure at each grid point.

[0164] It can be understood that the first pressure and the second electric field strength are coupled to obtain the second pressure at each grid point, including:

[0165] According to the formula Obtaining a joint dielectric constant; wherein ε represents the joint dielectric constant, φ represents the phase field, ε1 represents the first dielectric constant, and ε2 represents the second dielectric constant;

[0166] According to the joint dielectric constant, the second electric field strength, and the first pressure, the second pressure of the fluid at each grid point is calculated. It should be noted that this is different from the linear distribution relationship of the dielectric constant of the two-phase fluid with respect to the phase field in the past. This application makes adjustments to the relationship between the dielectric constant and the phase field. The adjusted relationship between the dielectric constant and the fluid phase is as follows: Figure 4 shown.

[0167] It should be noted that after the electric field is introduced, the second pressure of the fluid is used to describe the stress on the fluid, and the expression is:

[0168]

[0169] Step S124: Calculate the current density equilibrium distribution function and the current phase equilibrium distribution function of the fluid according to the second pressure.

[0170] It should be noted that the calculation expression of the current density equilibrium distribution function of the fluid calculated according to the second pressure is as follows:

[0171]

[0172]

[0173] Here, P is the second pressure and is a second-order tensor,

[0174] It is worth noting that the phase equilibrium distribution function is not directly determined by the second pressure, but is indirectly affected by the second pressure, because the pressure determines the stress of the fluid and thus indirectly affects the movement trend of the two-phase fluid, that is, the distribution trend. The expression of the phase equilibrium distribution function is:

[0175]

[0176] in,

[0177] It should be noted that the current density equilibrium distribution function and the current phase equilibrium distribution function represent the ideal numerical solution of the stable distribution of the density field and phase field calculated under the current pressure state, and are not the current distribution state of the density field and phase field, nor the solution when the calculation reaches the steady-state distribution. Its role is that the distribution state of the density field and phase field at the next time step is determined by the actual distribution state at this moment after collision and migration, and the current equilibrium state of the density field and phase field will be used in the calculation process of collision and migration.

[0178] Step S125, calculating the current physical field distribution of the fluid at each grid point according to the current phase equilibrium distribution function and the current density equilibrium distribution function; wherein the current physical field distribution includes the current phase field distribution, the current density field distribution, and the current potential distribution.

[0179] It should be noted that the current physical field distribution also includes the current velocity distribution. At the same time, according to the above formula, the current velocity distribution u(x, t) is closely related to the current phase field distribution and the current density field distribution, respectively, and the current phase field distribution will affect the current potential distribution. As mentioned in the previous article, the calculation of the velocity field needs to be based on the restrictive relationship between the phase field equilibrium distribution function and the macroscopic phase function or the restrictive relationship between the density field equilibrium distribution function and the macroscopic density. Therefore, the current velocity distribution affects the current phase field distribution and the current density field distribution.

[0180] Step S126, comparing the current phase field variation with a preset variation or comparing the current cycle number with a preset cycle number.

[0181] It should be noted that the conditions for preset judgment are as follows: ① Set the maximum number of iterations T max , that is, the preset number of cycles. When the number of iterations, that is, the current number of cycles, reaches T max ② Set the differential threshold errphi of the phase field, that is, the preset change amount. When the change value Δφ of the phase field in the entire fluid system, that is, the current phase field change amount, is less than the differential threshold errphi, the fluid system is judged to have reached a stable state and the loop operation is terminated.

[0182] It should be noted that when the current phase field change is greater than the preset change threshold and the current number of loops is less than the preset number of loops, the calculation will enter the next loop state, the time enters the next time step, and the calculation restarts from step S120. Then, after the current physical field distribution enters the next loop, for the new loop, the current physical field distribution will become the physical field distribution of the previous time step of the new loop, which is called the previous physical field distribution, and the loop operation is performed in this way.

[0183] It should be noted that the current phase field change and the current number of cycles will be recalculated once in each cycle.

[0184] It is understandable that before executing the loop process until the preset condition is met, each loop process also includes:

[0185] When the grid point is a boundary point, the velocity parameter in the density distribution function is processed by a rebound algorithm to correct the previous density field distribution of the boundary point.

[0186] It is understandable that before executing the loop process until the preset condition is met, each loop process also includes:

[0187] When the grid point is a boundary point, the velocity parameter in the phase distribution function is processed by a rebound algorithm to correct the previous phase field distribution of the boundary point.

[0188] It should be noted that the movement of the fluid in the fluid field and the electric field generated when the voltage is applied require the definition of boundary conditions in the two-dimensional network model: the fluid field and the electric field as a whole adopt the no-penetration and no-slip boundary conditions. At the boundary between the liquid and the solid, the density distribution function f of the fluid is i (x, t) and the phase distribution function g i (x, t) is processed by the rebound algorithm, and the speed e is changed first. i , the specific rebound method is as follows:

[0189] Before collision with the boundary → After collision with the boundary

[0190] e0→e0;

[0191] e1→e3; e2→e4; e3→e1; e4→e2;

[0192] e5→e7; e6→e8; e7→e5; e8→e6;

[0193] At the interface (x = x b )’s wetting phase field and velocity boundary conditions are as follows:

[0194]

[0195] u(x b )=0.

[0196] in is the interface unit normal vector.

[0197] The electric potential V(x b )=V b ,V b is the potential at the boundary, V b =V app , V at the negative electrode boundary b = 0, the fluid macro velocity u(x b )=0.

[0198] Step S127, determining the current physical field distribution as a steady-state distribution state or a target state; wherein the preset condition is that the current phase field change is less than a preset change or the current cycle number is equal to a preset cycle number.

[0199] It should be noted that when the phase field variation is less than a preset variation threshold, the current physical field distribution is determined as a steady-state distribution state, or when the current cycle number is equal to a preset cycle number, the current physical field distribution is determined as a target state.

[0200] It should be noted that the current physical field distribution includes the distribution of all physical quantities in the simulation, including:

[0201] Phase field, density field, pressure, electric field, velocity field, first physical simulation quantity, second physical simulation quantity.

[0202] It is understandable that after the loop calculation is completed, the data needs to be saved and the results need to be output.

[0203] The fluid simulation method according to the embodiment of the present application has at least the following beneficial effects: first, a simulation data set is obtained; wherein the simulation data set includes multiple first simulated physical quantities of the fluid and multiple second simulated physical quantities of the device to be electrowetted; an initial physical field distribution of the device is defined according to the first physical simulation quantity and the second physical simulation quantity; wherein the physical field is a two-dimensional network model, and each grid point in the two-dimensional grid model corresponds to a different coordinate; thereafter, a loop process is performed on the simulation data set until a preset condition is met, and the current physical field distribution when the preset condition is met is determined as a steady-state distribution state or a target state, the loop process comprising: calculating the chemical potential and the free energy density function according to the first simulated physical quantity, the second simulated physical quantity, the phase field calculated by the previous phase field distribution in the previous physical field distribution, and the density field calculated by the previous density field distribution in the previous physical field distribution; and calculating the chemical potential, the free energy density function, the phase field, and the density field according to the chemical potential, the free energy density function, the phase field, and the density field. degree field, and calculate the first pressure of the fluid at each grid point; according to the phase field corresponding to the three-phase contact line area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution, correct the first electric field strength corresponding to the three-phase contact area to determine the second electric field strength of each grid point; couple the first pressure and the second electric field strength to obtain the second pressure of each grid point; according to the second pressure, calculate the current density equilibrium distribution function and the current phase equilibrium distribution function of the fluid; according to the current phase equilibrium distribution function and the current density equilibrium distribution function, calculate the current physical field distribution of the fluid at each grid point; wherein the current physical field distribution includes the current phase field distribution, the current density field distribution, and the current potential distribution; compare the current phase field change with the preset change or compare the current number of cycles with the preset number of cycles; wherein the preset condition is that the current phase field change is less than the preset change or the current number of cycles is equal to the preset number of cycles. The fluid simulation method of the present application couples the second electric field strength and the first pressure to obtain the second pressure, and then the density distribution can be calculated through the second pressure; on the one hand, the calculation process is greatly simplified, and the high performance requirements for the computer are reduced by simplifying the amount of calculation; on the other hand, the operator only needs to set the corresponding actual physical quantity to perform the simulation, which greatly reduces the operator's requirements and saves the time cost of learning; finally, by correcting the electric field strength and then coupling the electric field with the fluid field, the parameters obtained by the simulation are more accurate, making the simulated fluid electrowetting phenomenon in the device closer to reality. Therefore, the fluid simulation method of the present application can simulate the electrowetting phenomenon of the fluid more quickly and accurately, and the simulation effect is closer to reality. .

[0204] It should be noted that the simulation value of the wetting angle θ0 obtained by the fluid simulation method of the present application and the theoretical value of the Young-Lippmann equation are as follows: Figure 3 As shown, by using the fluid simulation method of the present application, the simulation value of the wetting angle θ0 obtained is closer to the actual theoretical value, so that in the design and development process of the electrowetting device, on the one hand, it is possible to better observe the parameters designed for the electrowetting device and the change process when the electrowetting phenomenon occurs; on the other hand, by observing the change process and the steady state obtained when the voltage is applied to the electrowetting device to obtain simulation data, it is possible to make design references based on the simulation data, for example, to optimize the parameters, thereby providing a more accurate reference basis for the engineering design of the electrowetting device.

[0205] Refer to the following Figure 5 A fluid simulation system according to an embodiment of the present application is described.

[0206] like Figure 5 As shown, the fluid simulation system of the embodiment of the present application can be any type of smart terminal, such as a mobile phone, a tablet computer, a personal computer, etc.

[0207] Specifically, the fluid simulation system includes:

[0208] at least one memory 200;

[0209] at least one processor 300;

[0210] at least one program;

[0211] Programs are stored in the memory 200 , and the processor 300 executes at least one program to implement the above-mentioned fluid simulation method. Figure 5 Take a processor 300 as an example.

[0212] The processor 300 and the memory 200 may be connected via a bus or other means. Figure 5 Take the example of connecting via a bus.

[0213] The memory 200 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs, and signals, such as program instructions / signals corresponding to the fluid simulation system in the embodiment of the present application. The processor 300 executes various functional applications and data processing by running the non-transient software programs, instructions, and signals stored in the memory 200, that is, implementing the fluid simulation method of the above method embodiment.

[0214] The memory 200 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store relevant data of the above-mentioned fluid simulation method, etc. In addition, the memory 200 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 200 may optionally include a memory remotely arranged relative to the processor 300, and these remote memories may be connected to the fluid simulation system via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0215] One or more signals are stored in the memory 200, and when executed by one or more processors 300, the fluid simulation method in any of the above method embodiments is executed. Figure 2 Method steps S100 to S127 in.

[0216] Refer to the following Figure 5 A computer-readable storage medium according to an embodiment of the present application is described.

[0217] like Figure 5 As shown, the computer-readable storage medium stores computer-executable instructions, which are executed by one or more processors 300, for example, Figure 5 The one or more processors 300 may execute the fluid simulation method in the above method embodiment. Figure 2 Method steps S100 to S127 in.

[0218] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., may be located in one place, or may be distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0219] Through the description of the above embodiments, it can be understood by those skilled in the art that all or some steps and systems in the above disclosed methods can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include computer storage media and communication media. As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer. In addition, it is known to those skilled in the art that communication media generally contain computer-readable signals, data structures, program modules or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0220] The embodiments of the present application are described in detail above in conjunction with the accompanying drawings, but the present application is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in the relevant technical field without departing from the purpose of the present application. In addition, the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

Claims

1. A fluid simulation method, characterized in that: include: Acquire a simulation data set; wherein the simulation data set includes a plurality of first simulation physical quantities of the fluid and a plurality of second simulation physical quantities of the device to be electrowetted; Defining an initial physical field distribution of the device according to the first physical simulation quantity and the second physical simulation quantity; wherein the physical field is a two-dimensional network model, and each grid point in the two-dimensional grid model corresponds to a different coordinate; A loop process is performed on the simulation data set until a preset condition is met, and the current physical field distribution when the preset condition is met is determined as a steady-state distribution state or a target state, wherein the loop process includes: Calculate the chemical potential and the free energy density function according to the first simulated physical quantity, the second simulated physical quantity, the phase field calculated by the previous phase field distribution in the previous physical field distribution, and the density field calculated by the previous density field distribution in the previous physical field distribution; Calculating a first pressure of the fluid at each grid point according to the chemical potential, the free energy density function, the phase field, and the density field; According to the phase field corresponding to the three-phase contact area on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution, the first electric field intensity corresponding to the three-phase contact area is corrected to determine the second electric field intensity of each grid point; The first pressure and the second electric field strength are coupled to obtain a second pressure at each lattice point; According to the second pressure, a current density equilibrium distribution function and a current phase equilibrium distribution function of the fluid are calculated; The current physical field distribution of the fluid at each grid point is calculated according to the current phase equilibrium distribution function and the current density equilibrium distribution function; wherein the current physical field distribution includes the current phase field distribution, the current density field distribution, and the current potential distribution; Compare the current phase field variation with the preset variation or compare the current cycle number with the preset cycle number; Among them, the preset condition is that the current phase field change is less than the preset change or the current cycle number is equal to the preset cycle number.

2. The fluid simulation method according to claim 1, characterized in that: The obtaining of the simulation data set comprises: Acquire a plurality of first actual physical quantities of the fluid and a plurality of second actual physical quantities of the device; wherein the plurality of second actual physical quantities include a lateral length L of the device x , device longitudinal length L y , solid dielectric layer thickness d s , grid size δ x , time step δ t , the position of the electrodes and the potential V si ; Performing dimensionless normalization processing on each of the first actual physical quantities and each of the second actual physical quantities to obtain the first simulated physical quantity corresponding to the first actual physical quantity and the second simulated physical quantity corresponding to the second actual physical quantity; The simulation data set is established according to each of the first simulation physical quantities and each of the second simulation physical quantities.

3. The fluid simulation method according to claim 1, characterized in that: Defining the initial physical field distribution of the device according to the first physical analog quantity and the second physical analog quantity includes: Define the initial velocity, initial phase field, and initial potential.

4. The fluid simulation method according to claim 1, characterized in that: The step of calculating the first pressure of the fluid at each grid point according to the chemical potential and the free energy density function comprises: The first pressure of the fluid at each grid point is calculated based on the preset wetting potential, the free energy density corresponding to the phase field, the free energy density function, the chemical potential, the first simulated physical quantity, the second simulated physical quantity, and the density field.

5. The fluid simulation method according to claim 3, characterized in that: The method of correcting the first electric field strength corresponding to the three-phase contact line region according to the phase field corresponding to the three-phase contact region on the two-dimensional grid model and the previous potential distribution in the previous physical field distribution to determine the second electric field strength of each grid point includes: When the phase field corresponding to the three-phase contact line region falls within a preset range, the first electric field intensity corresponding to the phase field is enhanced according to the previous potential distribution and the preset enhancement formula to obtain the second electric field intensity at each grid point; wherein the enhancement formula is: E(φ)=E(φ)*B; where E represents the electric field intensity, φ represents the phase field, E(φ) represents the relationship between the phase field and the electric field intensity, B represents the enhancement coefficient, θ0 represents the contact angle of the fluid when it is stable at the solid interface, δ x Represents the size of each grid point.

6. The fluid simulation method according to claim 1, characterized in that: The coupling of the first pressure and the second electric field strength to obtain the second pressure of each lattice point includes: According to the formula Obtaining a joint dielectric constant; wherein ε represents the joint dielectric constant, φ represents the phase field, ε1 represents the first dielectric constant, and ε2 represents the second dielectric constant; The second pressure of the fluid at each grid point is calculated based on the joint dielectric constant, the second electric field strength, and the first pressure.

7. The fluid simulation method according to claim 1, characterized in that: Before executing a loop process on the simulation data set until a preset condition is satisfied and determining the current physical field distribution when the preset condition is satisfied as a steady-state distribution state or a target state, the method includes: When the grid point is a boundary point, a rebound algorithm is performed on the velocity parameter in the density distribution function to correct the previous density field distribution of the boundary point.

8. The fluid simulation method according to claim 6, characterized in that: Before executing a loop process on the simulation data set until a preset condition is satisfied and determining the current physical field distribution when the preset condition is satisfied as a steady-state distribution state or a target state, the method further includes: When the grid point is a boundary point, a rebound algorithm is performed on the velocity parameter in the phase distribution function to correct the previous phase field distribution of the boundary point.

9. A fluid simulation system, characterized in that: include: at least one memory; at least one processor; at least one program; The programs are stored in the memory, and the processor executes at least one of the programs to implement the fluid simulation method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the fluid simulation method according to any one of claims 1 to 8.

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