Glue flow leveling simulation method, glue pressing process parameter determination method and device

Abstract

This application relates to a method for simulating adhesive leveling, a method for determining adhesive bonding process parameters, and an apparatus. The method includes: constructing an adhesive leveling simulation computational domain based on the geometric parameters and adhesive properties of the target process model; the computational domain includes a first bonding wall, a second bonding wall, and a fluid domain located between the first and second bonding walls; dividing the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the distance change between the first and second bonding walls; wherein the first and second edge layer regions use boundary layer meshes with unchanged topology, and the intermediate deformation region uses a dynamic meshing method for mesh updating; simulating the bonding motion based on preset motion boundary conditions, and performing the simulation based on a gas-liquid two-phase interface tracking model. This method can improve the computational efficiency and accuracy of dynamic leveling simulation of the adhesive under pressure while ensuring computational stability.

Description

Technical Field

[0001] This application relates to the field of simulation technology, and in particular to a method for simulating adhesive leveling, a method and apparatus for determining adhesive bonding process parameters. Background Technology

[0002] In precision fields such as touch display manufacturing and semiconductor packaging, the liquid adhesive bonding process between the cover glass and the substrate is crucial. To avoid defects such as microbubble entrapment or uneven thickness, the liquid adhesive bonding process requires precise evaluation of the adhesive's spread under pressure.

[0003] Traditional techniques primarily rely on experimental trial-and-error methods or conventional numerical simulations for evaluation. However, existing experimental observations struggle to continuously capture the evolution of the internal flow field, while conventional numerical simulations are prone to causing highly distorted meshes in the near-wall region when dealing with the intense boundary motion accompanying the leveling of high-viscosity adhesives in narrow slits. This leads to problems such as computational numerical diffusion, poor mass conservation, or computational divergence.

[0004] This shows that traditional techniques still have the problem of difficulty in balancing computational stability, computational efficiency, and accuracy in the dynamic leveling simulation of adhesive under pressure. Summary of the Invention

[0005] Therefore, it is necessary to provide a method and apparatus for simulating the dynamic leveling of adhesive under pressure, which can improve the computational efficiency and accuracy of simulating the dynamic leveling of adhesive under pressure while ensuring computational stability.

[0006] In a first aspect, this application provides a method for simulating adhesive leveling, applied to the process of adhesive being pressurized, the method comprising:

[0007] Based on the geometric parameters and adhesive properties of the target process model, a liquid leveling simulation calculation domain is constructed; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface;

[0008] Along the direction of the change in the distance between the first and second pressed wall surfaces, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region; wherein, the first and second edge layer regions adopt boundary layer meshes with unchanged topology, and the intermediate deformation region adopts a dynamic meshing method for mesh updating;

[0009] Based on preset motion boundary conditions, the relative pressing motion between the first pressing wall surface and the second pressing wall surface is simulated, and based on the gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the liquid leveling simulation results.

[0010] In one embodiment, constructing the adhesive leveling simulation calculation domain based on the dimensions of the target process model includes:

[0011] A three-dimensional fluid computational domain is established based on the geometric dimensions of the target process model; the three-dimensional fluid computational domain includes the first pressing wall surface, the second pressing wall surface, and the fluid domain;

[0012] Identify the set of boundary contours of the three-dimensional fluid computational domain; the set of boundary contours includes at least wall contours and fluid interface contours;

[0013] Based on the boundary contour, the three-dimensional fluid computation domain is divided into multiple regular spaces;

[0014] Based on the shared topology, fluid domain connections are established between the various rule spaces to generate structured or unstructured computational grids, thus obtaining the computational domain for the liquid leveling simulation.

[0015] In one embodiment, dividing the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressed wall surfaces further includes:

[0016] Based on the movement velocity of the first and / or second pressed wall surfaces and the fluid property parameters of the fluid domain, the boundary layer thickness of the first and second edge layer regions is calculated so that the boundary layer grid cell size meets the preset viscous sublayer resolution condition.

[0017] In one embodiment, before simulating the leveling process of the fluid domain during the relative compression motion based on the gas-liquid two-phase interface tracking model, the method further includes:

[0018] The gas-liquid two-phase interface tracking model is constructed based on the fluid volume function method.

[0019] Configuring the gas-liquid two-phase interface tracking model includes: activating and configuring the surface tension model of the gas-liquid two-phase interface tracking model based on a preset surface tension coefficient; setting the gas phase as the main phase and the liquid phase as the secondary phase, and configuring the density and viscosity parameters of the gas phase and the liquid phase, wherein the viscosity parameter of the liquid phase is represented by a power-law model; and determining the flow field boundary conditions based on the wall contact angle and pressure outlet boundary conditions.

[0020] Based on the configuration results of the gas-liquid two-phase interface tracking model, the pressure-velocity coupling algorithm, spatial discretization scheme, and time discretization scheme used for the leveling process simulation are set.

[0021] In one embodiment, the preset motion boundary condition includes a preset pressing speed, and the simulation of the relative pressing motion between the first pressing wall surface and the second pressing wall surface based on the preset motion boundary condition includes:

[0022] The motion conditions of the first pressing wall surface and / or the second pressing wall surface are determined according to the preset pressing speed.

[0023] Using the first pressing wall surface and / or the second pressing wall surface as rigid body motion boundaries, and based on the motion conditions, simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface.

[0024] In one embodiment, the simulation of the leveling process of the fluid domain during the relative pressing motion based on the gas-liquid two-phase interface tracking model, to obtain the liquid leveling simulation results, further includes:

[0025] The fluid domain is mixed and initialized, and based on the preset initial distribution area of ​​the adhesive, a local repair algorithm is used to determine the initial volume fraction of each phase at each location in the fluid domain.

[0026] The time step for the simulation is determined based on the preset Courant number constraint.

[0027] Based on the time step and the initial value of the volume fraction, iterative flow field solution calculation is performed within a preset total number of running steps to obtain flow field data; the iterative flow field solution calculation process also includes: monitoring the residual value of the solution equation based on a preset residual convergence criterion;

[0028] Based on the flow field data, the simulation results of adhesive leveling were obtained.

[0029] In one embodiment, obtaining the adhesive leveling simulation results includes:

[0030] Extract the phase volume fraction distribution cloud map and velocity spatial distribution cloud map of the adhesive in the fluid domain;

[0031] Based on the phase volume fraction distribution cloud map and velocity space distribution cloud map, the liquid leveling simulation results of the adhesive are determined; the liquid leveling simulation results include at least one of the following: spreading area on different cross sections, liquid overflow amount, and wall shear stress.

[0032] Secondly, this application provides a method for determining adhesive bonding process parameters, the method comprising:

[0033] Obtain the geometric structure parameters and adhesive properties parameters of the target product;

[0034] Based on the aforementioned geometric parameters and adhesive properties, simulations were performed using the adhesive leveling simulation method described above to obtain simulation results of adhesive leveling under different combinations of process parameters. The combination of process parameters includes one or more of the following: preset motion boundary conditions, adhesive volume, adhesive viscosity, and initial distribution region of the adhesive.

[0035] The combination of process parameters corresponding to the simulation results of adhesive leveling where the spreading area reaches the preset requirements, the amount of adhesive overflow does not exceed the preset threshold, and there is no air bubble entrainment is taken as the target process parameter combination.

[0036] Thirdly, this application provides an adhesive leveling simulation device, the device comprising:

[0037] A construction module is used to construct a liquid leveling simulation calculation domain based on the geometric structural parameters and liquid physical property parameters of the target process model; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface;

[0038] The partitioning module is used to divide the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressing wall surfaces; wherein the first and second edge layer regions adopt boundary layer meshes with unchanged topology, and the intermediate deformation region adopts a dynamic meshing method for mesh updating;

[0039] The simulation module is used to simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface based on preset motion boundary conditions, and to simulate the leveling process of the fluid domain during the relative pressing motion based on the gas-liquid two-phase interface tracking model, so as to obtain the liquid leveling simulation results.

[0040] Fourthly, this application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0041] Fifthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0042] The aforementioned method for simulating adhesive leveling, method for determining adhesive bonding process parameters, and apparatus construct an adhesive leveling simulation computational domain based on the geometric structural parameters and adhesive physical property parameters of the target process model. Along the direction of the distance change between the first and second pressing walls, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region. The first and second edge layer regions use boundary layer meshes with unchanged topology, while the intermediate deformation region uses a dynamic meshing method for mesh updating. Based on preset motion boundary conditions, the relative pressing motion between the first and second pressing walls is simulated, and based on a gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the adhesive leveling simulation results. By strategically managing the fluid domain... The surface is divided into a first and second edge layer region near the wall, and an intermediate deformation region with large deformation. Differentiated meshing strategies are implemented accordingly. In the near-wall region, a boundary layer mesh with an unchanged topology is used, which can effectively avoid the high distortion of the near-wall mesh caused by violent boundary movement in traditional methods, eliminate numerical diffusion, ensure mass conservation, and guarantee computational stability. At the same time, a dynamic meshing method is used in the intermediate deformation region, which can flexibly adapt to the violent deformation during the spread of the adhesive without global remeshing, thus significantly improving computational efficiency. Combined with the gas-liquid two-phase interface tracking model to accurately capture the evolution of free surfaces, the contradiction between stability, efficiency, and accuracy in the simulation of high-viscosity adhesive slit leveling can be resolved. Thus, the technical effect of improving the computational efficiency and accuracy of dynamic leveling simulation of adhesive under pressure is achieved while ensuring computational stability. Attached Figure Description

[0043] Figure 1 This is a diagram illustrating the application environment of the adhesive leveling simulation method in one embodiment;

[0044] Figure 2 This is a flowchart illustrating a method for simulating adhesive leveling in one embodiment;

[0045] Figure 3 This is a flowchart illustrating a method for determining adhesive bonding process parameters in one embodiment;

[0046] Figure 4 This is a flowchart illustrating the adhesive leveling simulation method in another embodiment;

[0047] Figure 5 This is a schematic diagram of the simulation results of adhesive spreading under different pressing speeds in one embodiment;

[0048] Figure 6 This is a structural block diagram of an adhesive leveling simulation device in one embodiment;

[0049] Figure 7This is a structural block diagram of the device for determining the adhesive bonding process parameters in one embodiment;

[0050] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0052] The adhesive leveling simulation method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on another network server. Terminal 102 receives the geometric parameters and adhesive properties of the target process model from server 104, and constructs an adhesive leveling simulation domain based on these parameters. The adhesive leveling simulation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first and second pressing wall surfaces. Along the direction of the distance change between the first and second pressing wall surfaces, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region. The first and second edge layer regions use boundary layer meshes with unchanged topology, while the intermediate deformation region uses a dynamic meshing method for mesh updating. Based on preset motion boundary conditions, the relative pressing motion between the first and second pressing wall surfaces is simulated, and based on a gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the adhesive leveling simulation results. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0053] In one embodiment, such as Figure 2 As shown, a method for simulating adhesive leveling is provided. Taking the application of this method to the process of adhesive being under pressure as an example, the adhesive leveling simulation method includes:

[0054] Step S110: Construct the liquid leveling simulation calculation domain based on the geometric structure parameters and liquid property parameters of the target process model.

[0055] The target process model can be a process model that requires bonding with adhesive. For example, in scenarios such as touch displays, semiconductor packaging, or flexible cover glass bonding for foldable screens, the target process model can be a process model of the cover glass and substrate being bonded under pressure. It is understood that, based on the geometric parameters of the target process model and the physical properties of the adhesive, a simulation computational domain for adhesive leveling is constructed, thereby providing realistic and specific physical scene boundaries and initial condition constraints for adhesive leveling simulation. Furthermore, depending on the bonding structure morphology and substrate rigidity, the target process model can include, but is not limited to, planar-planar bonding models, curved-surface-planar bonding models, stepped substrate bonding models, and flexible-rigid composite bonding models.

[0056] Geometric parameters can be a set of values ​​that quantitatively describe the spatial dimensions, relative positions, and gap characteristics of each component in the target process model. They are used to define the spatial range of the simulation calculation domain and the initial state of changes in wall spacing. For example, geometric parameters can be extracted from CAD design drawings, obtained by measuring the actual workpiece using a coordinate measuring machine, or obtained by directly importing standard format geometric files and mapping material property parameters. Furthermore, depending on the parameter dimension, geometric parameters can include, but are not limited to, linear dimensional parameters, angular attitude parameters, and radius of curvature parameters.

[0057] The physical properties of the adhesive can be constants or a set of functional relationships characterizing the physical behavior of the liquid adhesive during pressure leveling, and can affect flow resistance and interfacial tension. For example, the liquid adhesive can include Newtonian fluids, and can also include non-Newtonian fluids such as shear-thinning fluids. In an exemplary embodiment, the physical properties of the adhesive can be obtained experimentally by measuring viscosity curves with a rheometer, measuring interfacial energy with a surface tension meter, or by incorporating design parameters of the adhesive. For example, depending on the category of physical properties, the physical properties of the adhesive can include, but are not limited to, one or more of rheological parameters, thermodynamic parameters, and interfacial chemical parameters. Further, rheological parameters can be, for example, viscosity curves, and interfacial chemical parameters can be, for example, surface tension and contact angle.

[0058] The computational domain for liquid leveling simulation can be a virtual spatial region constructed based on geometric structure and physical property parameters, used for discretizing and solving fluid control equations, and served as a carrier for numerical simulation.

[0059] In this embodiment, the simulation calculation domain for adhesive leveling includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface.

[0060] The first pressing wall surface can be a fixed or moving boundary surface representing the cover plate or the upper substrate in the simulation calculation domain, which can be used to apply pressure to drive the flow of adhesive.

[0061] The second bonding wall can be a fixed or moving boundary surface representing the base plate or lower substrate in the simulation calculation domain. It can be used to provide reaction force support or to apply pressure to drive the flow of adhesive.

[0062] For example, depending on the different surface micromorphologies, the first and second pressed wall surfaces can be, but are not limited to, ideal smooth wall surfaces, microtextured wall surfaces, wall surfaces with randomly distributed roughness, etc.; depending on the different material rigidities, the first and second pressed wall surfaces can also be rigid fixed wall surfaces, elastic deformable wall surfaces, composite laminated wall surfaces, etc.

[0063] The fluid domain can be a spatial region located between the first and second pressing walls, filled with liquid adhesive and undergoing continuous medium deformation. In this embodiment, the fluid domain can be used to carry out the gas-liquid two-phase flow process and serve as the core region for mesh generation and flow field solution.

[0064] The computational domain for adhesive leveling simulation is constructed based on the geometric parameters and physical properties of the target process model. This can be done by establishing a three-dimensional fluid computational domain according to the actual geometric dimensions of the process model, and assigning corresponding material properties to the mesh within the three-dimensional fluid computational domain. Furthermore, the computational domain can be generated using parametric modeling software, or by defining coordinate points using a scripting language, or by importing a standard format geometric file and mapping physical property parameters to construct the computational domain. These methods will not be elaborated upon in this embodiment.

[0065] Step S120: Divide the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressing wall surfaces.

[0066] The first edge layer region can be a fluid sub-region corresponding to the first pressing wall surface in the fluid domain. For example, when the second pressing wall surface is fixed and the first pressing wall surface moves towards the second pressing wall surface to press against it, the velocity gradient in the first edge layer region is relatively large. Therefore, high-gradient macroscopic features can be captured by locally refining the mesh. The first edge layer region can be used to analyze the boundary layer effect near the wall, preventing computational divergence caused by mesh distortion.

[0067] The second edge layer region can be a fluid sub-region within the fluid domain corresponding to the second pressed wall surface. For example, the second pressed wall surface may exhibit certain shear stresses, thus high-gradient macroscopic features can be captured by implementing local mesh refinement. The second edge layer region can be used to capture flow field details near the lower wall surface, ensuring the accuracy of mass conservation in the near-wall region.

[0068] The first and second edge layer regions employ boundary layer meshes with unchanged topology. These topology-invariant boundary layer meshes can be discretized mesh systems generated in the near-wall region where mesh cells are not added, deleted, or reconnected throughout the computation. By maintaining a constant topology and node spacing, the stability of the numerical scheme is preserved at high shear rates, avoiding non-physical numerical diffusion caused by mesh distortion and preventing boundary layer mesh disappearance due to dynamic mesh tiling operations.

[0069] For example, the boundary layer network can generate a structured or unstructured boundary layer mesh during the initialization phase, and update only the node coordinates without changing the cell connectivity during the time step, thereby achieving a fixed topology.

[0070] The intermediate deformation zone can be a fluid core region located between the first and second edge layer regions, bearing the main volumetric compression and lateral spreading deformation, and is used to accommodate the large-scale free surface evolution and drastic deformation of the adhesive. In this embodiment, the intermediate deformation zone is configured to use a dynamic meshing method for mesh updating.

[0071] Dynamic meshing can be an adaptive meshing algorithm that automatically adjusts node positions and even local topology according to boundary movement or flow field deformation. It is used to adapt to the large deformation requirements of the intermediate deformation zone and avoid computational interruptions and error accumulation caused by global mesh remapping. For example, the dynamic meshing in this embodiment can adopt methods including but not limited to smoothing, remeshing, and layering, and calculate the new coordinates of internal nodes in real time according to the boundary displacement.

[0072] The direction of the spacing change can be the direction of movement of the first and second pressing walls during the pressing process. Correspondingly, dividing the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the spacing change between the first and second pressing walls can also be done along the direction of movement. In an exemplary embodiment, the direction of the spacing change can be represented by other parallel directions, such as the thickness direction corresponding to the first pressing wall surface, the thickness direction corresponding to the second pressing wall surface, etc.

[0073] In this embodiment, a boundary layer mesh with an unchanged topology is used. This can be achieved by generating a boundary layer mesh that meets the requirements for high gradient capture in the near-wall sub-region, using a format such as a structured hexahedron while maintaining the unchanged topology. This eliminates mesh distortion caused by severe shearing in the near-wall region, thus ensuring the numerical stability and mass conservation of high-viscosity fluid calculations. In other embodiments, unstructured prism-type boundary layer meshes or hybrid-type boundary layer meshes may also be generated; however, this embodiment does not limit this approach.

[0074] The dynamic mesh method is used to update the mesh in the intermediate deformation zone. For example, the mesh can be updated by using the spring approximation method, the diffusion equation method, or the reconstruction method of local element splitting and merging. This allows for flexible handling of large deformations during the adhesive spreading process, avoids frequent global mesh re-dyeing, and significantly improves computational efficiency.

[0075] Step S130: Based on preset motion boundary conditions, simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface, and based on the gas-liquid two-phase interface tracking model, simulate the leveling process of the fluid domain during the relative pressing motion to obtain the liquid leveling simulation results.

[0076] The preset motion boundary conditions can be predefined time-space functions describing the relative motion between the first and second pressing walls. These functions drive the fluid within the simulation domain to generate pressurized flow, simulating the pressing action in actual processes. For example, the motion boundary conditions of the mesh can be compiled using custom functions to drive the flow based on the wall pressing velocity under actual operating conditions.

[0077] A gas-liquid two-phase interface tracking model can be a mathematical model used to capture and reconstruct the evolution process of the gas-liquid interface. It can be used to accurately predict the spreading morphology of the liquid front and the risk of microbubble entrapment, ensuring the accuracy of free surface calculations. For example, the gas-liquid two-phase interface tracking model can determine the interface position by solving volume fraction transport equations, level set equations, etc., combined with geometric reconstruction algorithms.

[0078] The results of adhesive leveling simulation can be a dataset output after the simulation calculation, including data such as flow field velocity, pressure distribution, interface morphology, and defect prediction. This dataset is used to evaluate the feasibility of the process and guide the optimization of actual production parameters to avoid bubbles and uneven thickness. For example, depending on the data presentation format, the results of adhesive leveling simulation can include, but are not limited to, transient flow field cloud map data, interface evolution sequence data, and key indicator statistical reports.

[0079] The relative pressing motion between the first pressing wall and the second pressing wall is simulated based on preset motion boundary conditions. For example, complex motion laws can be loaded by user-defined functions, or the wall motion can be driven by interpolation of tabular data. Alternatively, the wall motion can be calculated in real time by coupling a multibody dynamics solver to reproduce the real pressing process.

[0080] The flow leveling process of the fluid domain during relative compression motion is simulated based on the gas-liquid two-phase interface tracking model. For example, the interface tracking can be performed by using the geometric reconstruction volume fluid method combined with the compression scheme, or by using the high-order level set method combined with the re-initialization technique. Alternatively, the interface evolution simulation can be performed by using the phase field method combined with the finite element method to solve the equations. These methods can capture the dynamic evolution of the free surface with high precision and accurately predict the microbubble entrainment and the uniformity of the adhesive thickness.

[0081] For example, in the scenario of optimizing the bonding process of flexible cover plates for foldable screen phones, during the manufacturing process of foldable screen phones, it is necessary to bond flexible optical adhesive between a glass cover plate with a slight curvature and the display module. The adhesive leveling simulation method in this embodiment can first establish a target process model including the curved cover plate and the planar substrate, inputting the shear-thinning adhesive properties and the geometric parameters of the micron-level gap. After constructing the adhesive leveling simulation calculation domain, the adhesive layer is divided along the pressing direction into a first edge layer region close to the glass, a second edge layer region close to the module, and an intermediate deformation region. The two edge layer regions are then applied... A boundary layer mesh with an unchanged topology ensures that the near-wall mesh does not distort under high pressure and bonding speed. Dynamic meshing technology is applied to the middle region to accommodate the large deformation of the adhesive spreading rapidly from the center to the surrounding areas. Preset motion boundary conditions are set to simulate the pressing process of the indenter, and the adhesive front is calculated in real time using a gas-liquid two-phase interface tracking model. The resulting adhesive leveling simulation results can show the process of adhesive filling corners, thus effectively predicting the risk of edge microbubble entrapment. This provides engineers with a quantitative reference for adjusting the bonding speed and initial adhesive amount, achieving low-defect or even defect-free bonding without increasing experimental costs.

[0082] This embodiment provides a method for simulating adhesive leveling. It constructs an adhesive leveling simulation computational domain based on the geometric parameters and adhesive properties of the target process model. Along the direction of the distance change between the first and second pressing walls, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region. The first and second edge layer regions use boundary layer meshes with unchanged topology, while the intermediate deformation region uses a dynamic meshing method for mesh updates. Based on preset motion boundary conditions, the relative pressing motion between the first and second pressing walls is simulated. Using a gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the adhesive leveling simulation results. This is achieved by strategically dividing the fluid domain into near-... The first and second edge layers of the wall, as well as the intermediate deformation zone with large deformation, are targeted with differentiated meshing strategies. In the near-wall region, a boundary layer mesh with an unchanged topology is used, which can effectively avoid the high distortion of the near-wall mesh caused by violent boundary movement in traditional methods, eliminate numerical diffusion, ensure mass conservation, and guarantee computational stability. At the same time, a dynamic meshing method is used in the intermediate deformation zone, which can flexibly adapt to the violent deformation during the spread of the adhesive without global re-meshing, thus significantly improving computational efficiency. Combined with the gas-liquid two-phase interface tracking model to accurately capture the evolution of free surfaces, the contradiction between stability, efficiency, and accuracy in the simulation of high-viscosity adhesive slit leveling can be resolved. Thus, the technical effect of improving the computational efficiency and accuracy of dynamic leveling simulation of adhesive under pressure is achieved while ensuring computational stability.

[0083] In one embodiment, constructing the adhesive leveling simulation calculation domain based on the dimensions of the target process model includes:

[0084] Based on the geometric dimensions of the target process model, a three-dimensional fluid computational domain is established; the three-dimensional fluid computational domain includes the first pressing wall surface, the second pressing wall surface, and the fluid domain.

[0085] Identify the set of boundary contours of the three-dimensional fluid computational domain;

[0086] Based on the boundary contour, the three-dimensional fluid computational domain is divided into multiple regular spaces;

[0087] Based on the shared topology, fluid domain connections are established between various regular spaces to generate structured or unstructured computational grids, thus obtaining the computational domain for liquid leveling simulation.

[0088] The three-dimensional fluid computational domain can be a three-dimensional virtual space region constructed based on the geometric dimensions of the target process model, used for discretizing and solving the fluid control equations. It can serve as the physical carrier for adhesive leveling simulation and record the characteristics of the adhesive distribution area. For example, the three-dimensional fluid computational domain can be enclosed by a first pressing wall and a second pressing wall, containing a fluid domain within it.

[0089] Accordingly, the adhesive leveling simulation calculation domain is constructed based on the dimensions of the target process model. This can be achieved by reading the geometric dimension data of the target process model, initializing the three-dimensional coordinate system, and then defining the spatial range including the pressing wall surface and the fluid domain. Furthermore, the domain can be constructed by directly defining dimensions based on a parametric script, by importing a CAD model and automatically extracting the outer envelope box, or by inputting length, width, and height parameters through an interactive interface. These details will not be elaborated upon in this embodiment.

[0090] The boundary profile set can be a collection of curves or surfaces extracted from the three-dimensional fluid computational domain that describe the geometric features of all physical boundaries. In this embodiment, it serves as a topological reference for spatial segmentation to ensure that the mesh generation process strictly conforms to the actual physical boundaries and prevents geometric distortion.

[0091] In this embodiment, the boundary profile set includes at least the wall profile and the fluid interface profile.

[0092] The wall profile can be a subset describing the geometry of the first and second pressed wall surfaces, and can define the upper and lower boundary constraints of the fluid domain. The fluid interface profile can be a profile describing the initial morphology of the gas-liquid two-phase interface, used to define the initial position of the fluid free surface.

[0093] For example, identifying the set of boundary contours of a three-dimensional fluid computation domain can be achieved by traversing the surface data of the three-dimensional fluid computation domain and classifying and extracting wall contours representing solid walls and fluid interface contours representing gas-liquid interfaces. Furthermore, feature edges can be automatically identified using a curvature threshold algorithm, contours can be manually filtered using user-specified labels, or contours can be extracted using Boolean operations on the geometric kernel, thereby accurately capturing geometric features and providing accurate topological constraints for spatial segmentation.

[0094] A regular space can be a number of sub-regional units with regular geometric topological features, which are divided into three-dimensional fluid computational domains based on boundary contours. It can decompose a complex global domain into easily processed local blocks, reducing the complexity of mesh generation. For example, multiple regular spaces can be obtained by logically cutting the computational domain along the boundary contour normal or tangent using Boolean operations or mapping transformation algorithms.

[0095] Shared topology can be a mechanism for establishing nodes between adjacent regular spaces, which can eliminate discontinuities and numerical errors at the boundaries of regular spaces, ensuring the conservation and stability of flow field variables during cross-regional transmission. In an exemplary embodiment, during the mesh generation stage, adjacent regular spaces can be forced to adopt a consistent node distribution and cell connection index on the common interface to achieve shared topology.

[0096] Structured or unstructured computational grids can be systems of nodes and elements filling a regular space for discretizing fluid control equations. It is understood that high-quality grids can effectively suppress numerical diffusion and improve computational convergence speed and accuracy. In this embodiment, a structured grid can be generated by employing a multi-region meshing strategy within the regular space and setting the mapping or scan type of the internal grid to a hexahedral format. Alternatively, for complex irregular geometries, unstructured grids can be generated by defining boundary transient motions using smoothing and remeshing methods. These grids are then globally assembled using a shared topology and transmitted to the fluid solver.

[0097] Based on the shared topology, fluid domain connections are established between various rule spaces. For example, this can be achieved by analyzing the common interface of adjacent rule spaces, matching node distribution, and establishing a unified connection index, thereby realizing the reuse and seamless splicing of topology structures, ensuring the continuity and conservation of cross-regional flow field calculations, and avoiding numerical oscillations or divergences caused by mesh mismatch.

[0098] This embodiment provides a method for simulating adhesive leveling. It establishes a three-dimensional fluid computational domain based on the geometric dimensions of the target process model, identifies the boundary contour set of the three-dimensional fluid computational domain, divides the three-dimensional fluid computational domain into multiple regular spaces based on the boundary contours, and establishes fluid domain connections between each regular space based on shared topology. This generates structured or unstructured computational meshes, enabling simulation calculations to have a high-fidelity geometric foundation. The mesh generation strategy utilizing regular spaces and topology reuse avoids mesh distortion caused by violent boundary movements. While maintaining the orthogonality and uniformity of the mesh in the near-wall region, it suppresses numerical diffusion and ensures mass conservation, solving the problem of computational divergence to improve stability. Simultaneously, it significantly reduces the computational complexity of mesh updates and solutions to improve efficiency. Therefore, it can achieve high-precision dynamic simulation of the high-viscosity adhesive leveling process in slits, achieving the technical effects of improved stability, efficiency, and accuracy.

[0099] In one embodiment, dividing the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressed wall surfaces further includes:

[0100] Based on the movement velocity of the first and / or second pressed wall surfaces and the fluid properties of the fluid domain, the boundary layer thickness of the first and second edge layer regions is calculated so that the boundary layer mesh cell size meets the preset viscous sublayer resolution condition.

[0101] The movement speed of the first pressing wall surface can be described as the instantaneous movement rate of the first pressing wall surface during the pressure bonding process. The movement speed of the second pressing wall surface can be described as the instantaneous movement rate of the second pressing wall surface during the pressure bonding process.

[0102] The fluid properties parameters of a fluid domain can be a set of data characterizing the properties of liquid colloids within the fluid domain at specific temperatures and pressures. Understandably, these fluid properties parameters can include density, dynamic viscosity, and other fundamental physical constants used to calculate dimensionless distance values ​​and boundary layer thicknesses.

[0103] The boundary layer thickness can be a characteristic length scale of the near-wall region calculated based on the wall velocity and fluid properties under current operating conditions, combined with the target dimensionless distance value. In an exemplary embodiment, the boundary layer thickness can be calculated using the flat plate boundary layer theory formula, substituting real-time velocity and viscosity. Furthermore, the boundary layer thickness can be calculated in real time at each simulation time step or preset iteration interval by reading the current relative wall velocity and fluid viscosity or density data, substituting them into the boundary layer growth model formula, and combining the target dimensionless distance value to obtain the dynamically changing boundary layer thickness.

[0104] A viscous sublayer can be an extremely thin fluid layer adjacent to a solid wall, a physical subregion in which viscous forces dominate, the flow velocity is linearly distributed, and turbulent fluctuations are suppressed.

[0105] The boundary layer mesh element can be a set of discretized meshes with a specific topological structure constructed within the first and second edge layer regions to capture drastic gradient changes in the near-wall fluid. For example, the boundary layer mesh element can be a prism layer mesh stretched along the wall normal direction, or it can be an anisotropic hexahedral mesh; this embodiment does not limit the specific mesh element.

[0106] The preset viscous sublayer resolution condition can be a set of numerical criteria used to constrain the height of the first layer of the boundary layer mesh cells and the interlayer growth rate, to ensure that the mesh nodes fall precisely within the viscous sublayer range defined by hydrodynamics. In an exemplary embodiment, the preset viscous sublayer resolution condition may include one or more of a target dimensionless wall distance threshold and an upper limit for the mesh growth rate.

[0107] This embodiment provides a method for simulating adhesive flow leveling. By calculating the boundary layer thickness of the first and second edge layer regions based on the movement velocity of the first and / or second pressing walls and the fluid properties of the fluid domain, the boundary layer mesh element size is made to meet the preset viscous sublayer resolution condition. By calculating the boundary layer thickness based on the wall movement velocity and fluid properties, rather than using fixed empirical values, and by forcibly constraining the first layer mesh nodes to fall within the viscous sublayer range in fluid dynamics, the linear velocity distribution in this region is directly analyzed. This avoids errors caused by using wall function approximations, prevents distortion in shear stress calculation due to excessively coarse meshes, and avoids numerical rigidity problems caused by excessively fine or unreasonable mesh distributions. Thus, under complex working conditions of severe pressure deformation of high-viscosity adhesives, the convergence and accuracy of flow field simulation are improved, achieving the technical effect of simultaneously optimizing computational stability, efficiency, and accuracy.

[0108] In one embodiment, before simulating the leveling process of the fluid domain during relative compression motion based on the gas-liquid two-phase interface tracking model, the following steps are included:

[0109] A gas-liquid two-phase interface tracking model is constructed based on the fluid volume function method.

[0110] The gas-liquid two-phase interface tracking model is configured, including: activating and configuring the surface tension model of the gas-liquid two-phase interface tracking model based on the preset surface tension coefficient; setting the gas phase as the main phase and the liquid phase as the secondary phase, and configuring the density and viscosity parameters of the gas and liquid phases, wherein the viscosity parameter of the liquid phase is represented by a power law model; and determining the flow field boundary conditions based on the wall contact angle and pressure outlet boundary conditions.

[0111] Based on the configuration results of the gas-liquid two-phase interface tracking model, the pressure-velocity coupling algorithm, spatial discretization scheme, and time discretization scheme used for the leveling process simulation are set.

[0112] The fluid volume function method (FVM) is a numerical calculation method based on an Eulerian grid framework. It reconstructs and tracks the gas-liquid interface location by solving the fluid volume fraction transport equation within each grid cell. The volume fraction parameter can be explicitly formulated and truncated to a minimum value to accurately capture the free surface morphology during leveling processes with drastic topological changes, avoiding calculation errors caused by interface ambiguity. In this embodiment, the FVM solves the volume fraction convection-diffusion equation at each time step, reconstructs the interface geometry based on the volume fraction distribution using a geometric reconstruction algorithm, and employs an implicit volume force scheme, setting the Courant number to a preset reasonable value. In an exemplary embodiment, the FVM can serve as the foundation for a gas-liquid two-phase interface tracking model. By loading a surface tension model and calling a power-law model to calculate local viscosity, the solution is driven by a pressure-velocity coupling algorithm.

[0113] A gas-liquid two-phase interface tracking model can be constructed based on the fluid volume function method. For example, a multiphase flow model framework based on the fluid volume function method can be selected, a geometric reconstruction interface can be activated, a solution strategy for the volume fraction transport equation can be defined, and a free surface tracking infrastructure capable of handling topological splitting and merging can be established.

[0114] Based on the preset surface tension coefficient, activate and configure the surface tension model of the gas-liquid two-phase interface tracking model.

[0115] The preset surface tension coefficient can be a constant or temperature-dependent physical constant characterizing the magnitude of intermolecular attraction per unit length at the gas-liquid interface. It can be used to quantify the influence of interfacial tension on the spreading morphology of the adhesive front and the stability of microbubbles, preventing non-physical interface breakage. In an exemplary embodiment, the preset surface tension coefficient can be determined by the pendant drop method or obtained by importing material property data.

[0116] The surface tension model can be a numerical calculation module that transforms the surface tension coefficient into a source term of the momentum equation. It can be implemented using the continuous surface force method, and furthermore, the pressure interpolation term can employ a higher-order scheme. Furthermore, the surface tension model is used to apply the correct capillary force near the interface to simulate contact angle hysteresis and the meniscus formation process.

[0117] The surface tension model is activated and configured based on a preset surface tension coefficient for the gas-liquid two-phase interface tracking model. This can be achieved by inputting experimentally measured surface tension values, enabling the continuous surface force calculation option, and setting the interface curvature calculation accuracy.

[0118] The gas phase is set as the main phase and the liquid phase as the secondary phase. The density and viscosity parameters of the gas and liquid phases are configured. The viscosity parameter of the liquid phase is represented by a power-law model.

[0119] In this context, the gas phase can be a fluid medium occupying unfilled spaces in the simulation domain, such as air or other gases. The liquid phase can be the target medium undergoing flow deformation in the simulation domain; in this embodiment, it can be a liquid optical adhesive, encapsulating adhesive, or other adhesive.

[0120] Density is a physical quantity representing the mass of a fluid per unit volume. It participates in the calculation of the inertial and gravitational terms in the momentum equation, affecting the fluid's acceleration response. Viscosity parameters are a set of physical quantities describing the internal frictional resistance characteristics of a fluid, characterizing the ease of fluid flow and energy dissipation.

[0121] A power-law model can be a constitutive equation describing the nonlinear relationship between shear stress and shear rate in a non-Newtonian fluid. It is used to characterize the dynamic changes in viscosity of a liquid as it flows, where the viscosity model is set to laminar flow. In this embodiment, the power-law model can be used to accurately simulate the shear thinning or thickening behavior of a high-viscosity liquid under pressure in a slit due to changes in shear rate, thus improving the physical realism of the flow field calculation.

[0122] By setting the gas phase as the primary phase and the liquid phase as the secondary phase, for example, air can be specified as the background fluid in the multiphase flow settings panel, and the adhesive can be defined as the second fluid. This can optimize the volume fraction calculation logic, reduce the calculation redundancy of the initially gas-filled region, and improve the solution efficiency.

[0123] Configure the density and viscosity parameters of the gas and liquid phases. For example, you can input density constants for the gas and liquid phases respectively and select a non-Newtonian viscosity model template for the liquid phase. This will give the fluid realistic physical properties and enable the momentum equation to reflect the actual force conditions.

[0124] Similarly, using a power-law model to represent the viscosity parameters of the liquid phase can be achieved by selecting the power-law model in the liquid phase viscosity settings, inputting the consistency coefficient and flow index, and defining a shear rate reference value. This reflects the viscosity reduction characteristics of high-viscosity adhesives under high-speed shear, avoiding misjudgments of flow resistance caused by the assumption of constant viscosity.

[0125] The flow field boundary conditions are determined based on the wall contact angle and pressure outlet boundary conditions.

[0126] The wall contact angle can be the angle formed at the intersection of the gas-liquid interface and the solid wall surface, characterizing the wettability of the liquid on the substrate or cover plate. For example, the wall contact angle can be used to control the spreading direction and speed of the adhesive on the wall surface, and to predict edge creep or retraction phenomena.

[0127] Pressure outlet boundary conditions can be constraints defining the static pressure value at the boundary of the computational domain, allowing fluid to flow freely in or out to balance the internal pressure. In some exemplary embodiments, the reference gauge pressure for the pressure outlet boundary conditions can be set to 0 Pa. It is understood that pressure outlet boundary conditions can be used to simulate the discharge path of compressed gas, thereby preventing spurious high pressures and computational divergence caused by the inability of gas to escape. Furthermore, pressure outlet boundary conditions can include, but are not limited to, constant static pressure outlets, atmospheric pressure outlets, and time-varying pressure outlets.

[0128] Flow field boundary conditions can be a set of mathematical constraints that limit the distribution of physical quantities such as velocity, pressure, and temperature around the fluid domain and on the walls. They are used to close the control equations and ensure the uniqueness and physical rationality of the numerical solution.

[0129] Correspondingly, the flow field boundary conditions are determined based on the wall contact angle and pressure outlet boundary conditions. This can be achieved by setting static or dynamic contact angle values ​​at all solid wall boundaries and setting the static pressure value at the exhaust area boundary to the ambient pressure, thereby obtaining the flow field boundary conditions. This allows for a true reproduction of the wetting behavior of the adhesive and the substrate, as well as the gas exhaust path, preventing non-physical reflections or accumulations at the boundaries.

[0130] The pressure-velocity coupling algorithm can be an iterative solution strategy used in numerical simulations of incompressible or low Mach number fluids to simultaneously solve the momentum equation and continuity equation, thereby eliminating the mismatch between the pressure and velocity fields. In a specific embodiment, an implicit pressure splitting operator algorithm combined with a momentum sub-relaxation factor can be used to improve convergence. Exemplary examples include pressure-velocity coupling algorithms such as split-solution algorithms, coupled-solution algorithms, and semi-implicit pressure correlation algorithms. In a specific embodiment, the pressure-velocity coupling algorithm can employ the PISO (Pressure Implicit with Splitting of Operators) algorithm to solve incompressible fluid flow problems.

[0131] Spatial discretization schemes can be numerical approximations of spatial derivative terms in partial differential equations, transforming them into a system of algebraic equations. These schemes can determine the computational accuracy of convection and diffusion terms, influencing interface sharpness and the magnitude of numerical dissipation. In an exemplary embodiment, the momentum equation spatial discretization can employ a second-order upwind scheme.

[0132] A time-discretion scheme can be a numerical method that transforms the time derivative term into a difference form to advance transient calculations, thereby controlling the stability and accuracy of the time step and adapting to rapidly changing compression processes. In an exemplary embodiment, the time term discretization can employ a first-order implicit scheme.

[0133] Furthermore, the pressure interpolation term and momentum sub-relaxation factor can be set according to the configuration results of the gas-liquid two-phase interface tracking model. In a specific embodiment, the pressure interpolation term can be in PRESTO! format, and the momentum sub-relaxation factor can be set to 0.3.

[0134] This embodiment provides a method for simulating the flow leveling of adhesives. It constructs a gas-liquid two-phase interface tracking model based on the fluid volume function method. The configuration of this model includes activating and configuring a surface tension model based on a preset surface tension coefficient; setting the gas phase as the dominant phase and the liquid phase as the secondary phase and configuring density and viscosity parameters expressed using a power-law model; determining flow field boundary conditions based on wall contact angle and pressure outlet boundary conditions; and setting a pressure-velocity coupling algorithm, spatial discretization scheme, and temporal discretization scheme based on the configuration results. This establishes a free surface tracking infrastructure capable of handling topological splitting and merging. This method introduces capillary forces to accurately simulate interface bending and bubble stability at the microscale, endowing the fluid with realistic physical properties and precisely characterizing the viscosity reduction characteristics of high-viscosity adhesives under high-speed shear. It can realistically reproduce the wetting behavior of the adhesive and the substrate and the gas discharge path, thereby minimizing numerical dissipation while ensuring computational stability and convergence. Under the premise of avoiding computational divergence caused by mesh distortion, it achieves efficient and high-precision simulation of the dynamic leveling process of the adhesive, effectively controlling the prediction accuracy of microbubble entrapment risk and edge spreading morphology, and achieving the technical effect of improving the convergence and stability of the calculation process.

[0135] In one embodiment, the preset motion boundary conditions include a preset pressing speed. Based on the preset motion boundary conditions, simulating the relative pressing motion between the first pressing wall surface and the second pressing wall surface includes:

[0136] The motion conditions of the first pressing wall surface and / or the second pressing wall surface are determined according to the preset pressing speed.

[0137] Using the first pressing wall surface and / or the second pressing wall surface as rigid body motion boundaries, the relative pressing motion between the first pressing wall surface and the second pressing wall surface is simulated based on motion conditions.

[0138] The preset pressing speed can be a scalar or vector parameter pre-set in the adhesive leveling simulation, describing the rate at which the first and second pressing walls approach each other. In a specific embodiment, the pressing speed can be a mesh motion condition determined by compiling a user-defined function and used as a direct input variable to drive the relative pressing motion. This quantifies the complex physical pressing process into defined boundary driving conditions, eliminating the uncertainty of motion definition and ensuring the repeatability and controllability of the simulation process. For example, depending on the change in pressing acceleration, the preset pressing speed can be one or more of the following: constant rate pressing speed, segmented variable speed pressing speed, sinusoidal oscillating pressing speed, etc.

[0139] The motion conditions of the first pressing wall can be derived from a preset pressing speed, and are mathematical expressions used to constrain the displacement and velocity vector of the first pressing wall within the simulation time step. This allows for precise control of the dynamic behavior of the upper wall, ensuring it strictly follows the predetermined process trajectory and providing accurate upper boundary excitation for the fluid domain. Similarly, the motion conditions of the second pressing wall can be derived from a preset pressing speed, and are mathematical expressions used to constrain the displacement and velocity vector of the second pressing wall within the simulation time step. This allows for precise control of the dynamic behavior of the lower wall, which, together with the first pressing wall, constructs a relative compression environment.

[0140] The motion conditions of the first pressing wall surface and / or the second pressing wall surface are determined according to the preset pressing speed. For example, the motion conditions may correspond to a single-wall drive mode, a double-wall symmetrical drive mode, an asymmetrical proportional drive mode, etc.

[0141] Rigid body motion boundary can be a type of boundary that is given rigid constraint properties in numerical simulation. Its internal mesh nodes maintain their relative positions during motion, and only the whole body translates or rotates. This can fundamentally avoid mesh distortion caused by non-physical deformation of the wall itself, greatly reduce the computational complexity of mesh update algorithms, and prevent numerical diffusion caused by mesh quality deterioration.

[0142] Correspondingly, simulating relative pressing motion using the first and / or second pressing walls as rigid body motion boundaries can be achieved by setting the specified pressing walls as rigid body properties in the solver, applying the determined motion conditions to update the overall coordinates of the wall mesh, while keeping the topology of the wall mesh unchanged, and driving the adjacent fluid domain mesh to perform corresponding layering, smoothing, or reconstruction. This improves the convergence speed and stability of the solver while ensuring the accuracy of the physical motion trajectory, and avoids computational divergence caused by wall mesh distortion.

[0143] This embodiment provides a method for simulating adhesive leveling. By determining the motion conditions of the first and / or second pressing walls based on a preset pressing speed, and simulating relative pressing motion using the first and / or second pressing walls as rigid body motion boundaries, the method quantifies the complex physical pressing process into definite input variables. This allows for accurate determination of the motion conditions of the first and / or second pressing walls, eliminating the uncertainty in the definition of boundary motion. By defining the pressing walls as rigid body motion boundaries for simulation, and because the wall mesh only undergoes overall displacement without deformation during the calculation process, the problem of mesh distortion caused by wall deformation is fundamentally avoided. This significantly reduces the computational complexity of the mesh update algorithm and prevents numerical diffusion or computational divergence caused by mesh quality deterioration. Thus, it achieves the technical effect of effectively improving the computational efficiency and accuracy of dynamic leveling simulation of adhesive under pressure while ensuring computational stability.

[0144] In one embodiment, based on a gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during relative compression motion is simulated, and the simulation results of adhesive leveling further include:

[0145] The fluid domain is mixed and initialized, and based on the preset initial distribution area of ​​the adhesive, a local repair algorithm is used to determine the initial volume fraction of each phase at each location in the fluid domain.

[0146] The time step for the simulation is determined based on the preset Courant number constraint.

[0147] Based on the initial values ​​of the time step and volume fraction, iterative flow field calculations are performed within a preset total number of running steps to obtain flow field data; the iterative flow field calculation process also includes: monitoring the residual values ​​of the solution equations based on preset residual convergence criteria;

[0148] Based on the flow field data, the simulation results of adhesive leveling were obtained.

[0149] Hybrid initialization can be a preprocessing operation mode that, during the numerical simulation startup phase, defines the internal liquid and air spaces based on the three-dimensional coordinate eigenvalues ​​of the computational domain, simultaneously assigning initial volume fraction distributions of fluid and gas phases to all mesh elements within the computational domain. It can be understood that hybrid initialization can quickly construct an initial flow field environment containing a gas-liquid coexistence state, employing implicit volume force schemes and explicit volume fraction formulas.

[0150] The initial distribution region of the adhesive can be a logical region predefined in the simulation calculation domain based on three-dimensional coordinate characteristic values, representing the actual spatial range or geometric shape occupied by the liquid adhesive before the start of pressing. It can serve as a spatial constraint condition for determining the volume fraction of each phase and defining the initial boundary between the adhesive and air. For example, the initial distribution region of the adhesive can include, but is not limited to, a central single-point dripping region, a multi-point multi-source dispersion region, a ring-shaped pre-coating region, and a strip-shaped linear distribution region.

[0151] The initial volume fraction can be a set of real numbers representing the proportion of the liquid phase and the air phase within each discrete grid cell in the fluid domain. It is understood that the initial volume fraction of each phase at each location in the fluid domain can be used to accurately reconstruct the gas-liquid interface topology at the initial moment, avoiding non-physical numerical oscillations caused by discontinuities in the initial field. In a specific embodiment, the initial volume fraction of each phase at each location in the fluid domain can be calculated by a local repair algorithm based on the initial distribution region of the liquid phase, and used as the initial boundary condition input for iterative flow field solution calculation.

[0152] Local patching algorithms can be computationally optimized by performing geometric reconstruction and volume fraction redistribution to address the problem of blurred or inaccurate interfaces after hybrid initialization. This eliminates the artificial step effect of the initial field, sharpens the gas-liquid interface, improves the accuracy of interface tracking from the source, and suppresses initial calculation oscillations. In a specific embodiment, local patching techniques can be used to assign a volume fraction of 1 to the liquid region and a value of 0 to the air space.

[0153] The preset Courant number constraint can be a dimensionless threshold criterion set to ensure the stability of the explicit volume fraction formula, limiting the maximum proportion of mesh cells traversed by the fluid within a time step. This dynamically constrains the upper limit of the time step, preventing numerical solution divergence due to excessively high flow velocity or overly fine mesh, thus balancing computational stability and efficiency. The preset Courant number constraint can be based on the CFL (Courant-Friedrichs-Lewy) condition, calculating the maximum allowable time step by multiplying the time step by the minimum value of the ratio of the mesh size to the velocity. In a specific embodiment, the Courant number can be set to 0.25.

[0154] The time step in simulation calculations can be a specific numerical value that discretizes continuous physical time into a series of small time intervals based on a given calculation time step during the solution of unsteady flow fields. It can be used to determine the frequency and accuracy of flow field state updates, affecting the ability to capture transient interface evolution and the total computation time. In a specific embodiment, the time step in simulation calculations can be dynamically adjusted according to a preset Courant number constraint and used as a parameter to advance physical time in iterative flow field solution calculations.

[0155] For example, the time step of the simulation calculation can be determined according to the preset CFL number constraint. Before the start of each time step, the maximum allowable time step that meets the stability condition can be calculated and determined according to the CFL condition and the time step calculation formula, thereby realizing the adaptive adjustment of the time step.

[0156] The preset total number of running steps can be the maximum number of iterations set in the simulation task, representing the total physical duration covered by the simulation process or one of the termination criteria, ensuring that the simulation automatically stops when the expected process time point or convergence state is reached.

[0157] The flow field data can be a multidimensional dataset containing each time step generated during the iterative solution process, used to record the complete dynamic evolution history of the adhesive under pressure leveling. In one exemplary embodiment, the data file can be automatically saved every 200 time steps. In another exemplary embodiment, the flow field data is generated by iterative flow field solution calculations, its quality is monitored by residual convergence criteria, and it is ultimately transformed into adhesive leveling simulation results. Exemplarily, the flow field data may include, but is not limited to, velocity vectors, pressure scalars, laminar parameters, and volume fraction distributions of each phase.

[0158] The residual value of the solved equation can be the error norm between the calculation results on both sides of the discretized fluid control equation in each iteration. It is used to quantitatively evaluate the convergence of the numerical solution in the current time step and determine whether the flow field has reached a mathematical equilibrium state. In this embodiment, the residual value of the solved equation can be compared with the residual convergence criterion. If the criterion is not met, a sub-iteration in the current time step or adjustment of the relaxation factor can be triggered.

[0159] The residual convergence criterion can be a pre-defined threshold range or descent rate rule used to determine whether the residual values ​​of the solved equations meet the accuracy requirements. This serves as one of the termination criteria for the iterative loop, ensuring that the flow field solution at each step has sufficient mathematical accuracy and preventing error accumulation that could lead to distortion in subsequent calculations. Furthermore, the residual convergence criterion can include, but is not limited to, one or more of the following: absolute residual threshold criterion, relative residual descent rate criterion, and multi-equation weighted convergence criterion.

[0160] Based on the initial values ​​of time step and volume fraction, iterative flow field calculations are performed within a preset total number of running steps. The corrected volume fraction can be used as the initial value, and physical time can be advanced according to the given calculation time step. The viscous model is set as laminar flow, and the solution is iterated until the upper limit of the total number of running steps is reached, so as to fully reproduce the transient flow behavior of the adhesive during the pressure process and generate continuous time series flow field data.

[0161] The residual values ​​of the solved equations are monitored based on the preset residual convergence criteria. In each iteration's internal loop, the residual norms of the continuity equation, momentum equation, and volume fraction transport equation are calculated in real time and compared with the preset convergence criteria. The residual curves are monitored synchronously to determine whether to continue the sub-iteration or enter the next time step.

[0162] The flow field data is used to obtain the flow leveling simulation results of the adhesive. This can be achieved by post-processing and extracting the flow field data such as velocity, pressure and volume fraction stored during the iteration process, and quantifying and outputting parameters such as the adhesive spreading area, phase volume fraction, adhesive overflow amount and wall shear stress of different cross sections, thus obtaining the adhesive flow leveling simulation results.

[0163] This embodiment provides a method for simulating the flow leveling of adhesives. By introducing a local repair algorithm to correct the field after mixing and initialization, it can accurately set the initial volume fraction value that conforms to the physical reality, avoiding calculation oscillations caused by abrupt changes in the initial field and ensuring the stability of the calculation from the source. By dynamically and adaptively determining the time step using the Courant number constraint, it can prevent numerical divergence caused by excessively large step sizes and avoid redundant calculations caused by fixed small step sizes. Thus, it can significantly improve the calculation efficiency while ensuring accuracy. At the same time, during the iteration process, the residual value of the solution equation is monitored in real time based on the residual convergence criterion, which can ensure the mathematical convergence and physical reality of the flow field solution at each step. Through the refined coordinated operation of initialization, time stepping and convergence control, it can overcome the problems of easy divergence and low efficiency of high viscosity adhesives in the simulation of violent deformation. Thus, while ensuring the stability of calculation, it can achieve the technical effect of improving the calculation efficiency and accuracy of dynamic flow leveling simulation of adhesives under pressure.

[0164] In one embodiment, the results of the adhesive leveling simulation include:

[0165] Extract phase volume fraction distribution cloud maps and velocity spatial distribution cloud maps of the colloid in the fluid domain;

[0166] Based on the phase volume fraction distribution cloud map and velocity space distribution cloud map, the liquid leveling simulation results of the adhesive are determined.

[0167] The phase volume fraction distribution cloud map can be a two-dimensional or three-dimensional visualization field data generated based on the calculation results of the gas-liquid two-phase interface tracking model. It uses color gradients to map the proportion of the liquid phase in each grid cell within the fluid domain. Through the phase volume fraction distribution cloud map, the transient changes of the gas-liquid interface, the spatial occupancy of the liquid, and the entrainment position of microbubbles can be intuitively presented during the pressing of the cover plate.

[0168] A velocity spatial distribution cloud map is a visual image representing the spatial distribution of the magnitude and direction of the motion vector of fluid micro-elements at various locations within a fluid domain, reflecting the distribution of the driving force for the flow of the adhesive within the slit. Understandably, the velocity spatial distribution cloud map can reveal the distribution of the driving force for the flow of the adhesive during the pressing process of the cover plate, the location of stagnant zones, and areas of intense shearing, aiding in the analysis of leveling dynamics mechanisms and flow behavior under various operating conditions.

[0169] Extracting the phase volume fraction distribution cloud map and velocity spatial distribution cloud map of the colloid in the fluid domain can be achieved by accessing transient data files generated by simulation calculations combining dynamic mesh technology and boundary layer densification strategy, reading volume fraction scalar field and velocity vector field data, and converting them into a sequence of visualized cloud map images by calling a graphics rendering engine. This transforms abstract numerical matrices into intuitive physical field images, allowing for direct observation of transient changes in the gas-liquid interface during the pressing process, and providing a visualized data foundation for quantitative analysis.

[0170] In this embodiment, the adhesive leveling simulation results include at least one of the following: the spreading area on different cross sections, the amount of adhesive overflow, and the wall shear stress.

[0171] The spreading area on different cross sections can be a two-dimensional metric value of adhesive coverage obtained by integrating the areas with a phase volume fraction greater than a threshold on a preset specific geometric plane. This value is used to quantitatively evaluate the uniformity and coverage of the adhesive on the substrate surface, and can determine whether there are unfilled dead corners or voids, providing decision support for optimizing bonding process parameters. In a specific embodiment, the spreading area on different cross sections can be obtained by binarizing the data of a specific cross section in the contour map and performing area integration.

[0172] The amount of adhesive overflow can be the total volume or mass of adhesive exceeding the preset process boundary during the simulation. For example, it can be calculated by accumulating the volume fraction of grid cells outside the boundary, thereby enabling a quantitative prediction of edge adhesive overflow process defects. It is understood that the amount of adhesive overflow can be used to predict the degree of material waste and the risk of adhesive overflow contamination, helping to optimize the initial dispensing amount to avoid excessive overflow or insufficient filling.

[0173] Wall shear stress can be considered as the tangential frictional force per unit area exerted by the adhesive on the first and second pressing walls during the flow process. It can be calculated by multiplying the fluid viscosity by the velocity gradient at the wall. Understandably, wall shear stress can assess the potential mechanical damage risk to precision components from high-speed flow, as well as the possibility of bubble entrapment induced in high-shear zones, thereby ensuring the safety of the pressing process.

[0174] This embodiment provides a method for simulating adhesive leveling. By extracting the phase volume fraction distribution cloud map and velocity spatial distribution cloud map of the adhesive in the fluid domain, the abstract numerical calculation results are transformed into intuitive and quantifiable physical indicators. The method determines the adhesive leveling simulation results based on the phase volume fraction distribution cloud map and velocity spatial distribution cloud map, calculates the spreading area on different cross sections to assess coverage uniformity, calculates the amount of adhesive overflow to predict material waste or defect risks, and analyzes the wall shear stress to determine the potential damage to the substrate or the possibility of bubble entrapment. The simulation results can be converted into key quality parameters corresponding to actual production, significantly improving the accuracy and interpretability of the simulation results for actual process parameters, and realizing the efficient transformation of dynamic leveling simulation of adhesive under pressure from theoretical calculation to engineering decision-making.

[0175] In one embodiment, such as Figure 3 As shown, a method for determining adhesive bonding process parameters is provided. Taking the application of this method to an adhesive leveling simulation scenario as an example, the method for determining adhesive bonding process parameters includes:

[0176] Step S210: Obtain the geometric structure parameters and adhesive property parameters of the target product.

[0177] The target product can be a solid component to be bonded with liquid adhesive. In an exemplary embodiment, it can consist of a cover plate, a substrate, and liquid adhesive filling the space between them.

[0178] Obtaining the geometric parameters and adhesive properties of the target product can be achieved by reading geometric files from a design database to construct a three-dimensional fluid computational domain, and then combining experimental measurement data to set the consistency coefficient and power-law exponent of the adhesive to describe its dynamic viscosity. Furthermore, parameters can be extracted in batches by automated scripts parsing CAD drawings, manually inputting measurement data and calibrating property curves, or through real-time feedback of material and dimensional parameters for the current batch via an online detection system.

[0179] Step S220: Based on the geometric structure parameters and adhesive property parameters, simulation is performed using the adhesive leveling simulation method in any of the above embodiments to obtain the adhesive leveling simulation results under different combinations of process parameters.

[0180] The process parameter combination includes one or more of the following: preset motion boundary conditions, adhesive volume, adhesive viscosity, and the initial distribution area of ​​the adhesive.

[0181] A combination of process parameters can be a set of adjustable production variables used to define the initial state and driving conditions during the adhesive mixing process. These variables serve as independent variables in simulation optimization, and their values ​​are adjusted to find the optimal solution that meets quality requirements. For example, depending on the nature of the variables, the combination of process parameters may include, but is not limited to, motion control parameters (such as dispensing speed), material usage parameters (such as dispensing volume), material property parameters (such as adhesive rheological parameters), and layout planning parameters (such as the initial distribution area of ​​the adhesive).

[0182] Among them, the preset motion boundary conditions can be predefined time-space functions that describe the motion law of the actuator of the pressing equipment. They are used to compile mesh motion conditions through UDF to drive the wall motion in the simulation, and to simulate the pressing action of the pressure head in actual production, providing a power source for the flow of adhesive.

[0183] The volume of the adhesive liquid can be the total volume of liquid adhesive injected between the substrate and the cover plate in a single lamination process. It can affect the degree to which the adhesive liquid covers the bonding area and the amount of overflow.

[0184] The viscosity of an adhesive can be considered as the internal frictional resistance characteristic exhibited by a liquid adhesive at a specific temperature and shear rate. It can affect the spreading speed and bubble expulsion ability of the adhesive under pressure.

[0185] The initial distribution area of ​​the adhesive can be the geometric distribution of the shape, position and coverage of the liquid adhesive on the substrate before the pressing begins. This can affect the symmetry of the flow path of the adhesive after it is pressed and the risk distribution of air entrapment.

[0186] Step S230: The combination of process parameters corresponding to the glue leveling simulation results where the spreading area reaches the preset requirements, the glue overflow amount is not greater than the preset threshold, and there are no air bubbles entangled is taken as the target process parameter combination.

[0187] The spreading area can be the coverage area after the adhesive is fully pressed together. Correspondingly, the preset requirement for the spreading area can be the minimum effective coverage area threshold that the adhesive must reach after full pressing as specified in the process requirements, used to determine whether the adhesive has fully filled the bonding area.

[0188] The amount of adhesive overflow can be measured by the volume or length of excess adhesive that exceeds the boundary of the target bonding area after pressing. It is used to assess the degree of material waste and its impact on subsequent cleaning processes. Understandably, the amount of adhesive overflow should be controlled within the allowable range.

[0189] The preset threshold can be the maximum allowable limit set for the amount of adhesive overflow. Exceeding this value will be considered unqualified. It is used to quantitatively define the process tolerance range and prevent product contamination or assembly interference caused by excessive adhesive overflow.

[0190] Air bubble entrapment is a defect that occurs during the pressure spreading of adhesive, where gas is trapped inside the adhesive layer due to the convergence of the flow front or poor venting. As a negative evaluation indicator, it can be used to determine the usability of process parameters.

[0191] The target process parameter combination can be the optimal set of process variables that has been screened and verified through simulation and can simultaneously meet the requirements of spreading area, overflow limit and no bubble entanglement. It can be used as a parameter setting guide for actual production line to ensure the stability and yield of mass production process.

[0192] This embodiment provides a method for determining adhesive bonding process parameters. By acquiring the geometric structure parameters and adhesive property parameters of the target product, and based on these parameters, simulation is performed using the adhesive leveling simulation method described in any of the above embodiments. Simulation results for different combinations of process parameters are obtained. The process parameter combination corresponding to the simulation results where the spreading area reaches a preset requirement, the adhesive overflow is no greater than a preset threshold, and there is no air bubble entanglement is taken as the target process parameter combination. By using a highly stable and efficient simulation method to replace the traditional time-consuming experimental trial-and-error method, it can quickly traverse multi-dimensional process parameter combinations, including adhesive volume, viscosity, and initial distribution, significantly improving evaluation efficiency. By setting preset requirements for spreading area, adhesive overflow, and no air bubble entanglement, quantitative constraints can be set, allowing for precise identification of the target process parameter combination from massive simulation data. This not only overcomes the inaccuracy problem caused by the instability of traditional numerical simulations but also enables the pre-avoidance of defects such as microbubble entanglement and uneven thickness in a virtual environment. Thus, while ensuring computational stability, it simultaneously achieves the technical effect of improving both process development efficiency and bonding accuracy.

[0193] To more clearly illustrate the technical solution of this application, a detailed embodiment is also provided.

[0194] In precision manufacturing fields such as touch display manufacturing, semiconductor packaging, and assembly of various optical components, the liquid adhesive bonding process between the cover plate and the substrate is a crucial step. In this process, the cover plate is pressed downwards at a certain speed and pressure. The adhesive undergoes shear deformation and radial leveling under the pressure of the compression stress, ultimately forming a uniform adhesive layer. In actual production, as the leveling front advances, defects such as microbubble entrapment, localized adhesive overflow, or uneven thickness distribution can easily occur between the adhesive, gas, and solid walls. Currently, the industry's evaluation of the adhesive spreading state in the cover plate pressing process mainly relies on traditional "trial and error" methods and human experience. However, existing experimental observation methods are extremely difficult to clearly and continuously capture the evolution of the internal flow field of the adhesive between the upper and lower plates and the expansion morphology of the gas-liquid interface, resulting in technical limitations such as high R&D costs, long development cycles, and the "black box" effect of observation. To accurately characterize the spreading morphology and flow field evolution of the adhesive, precise numerical modeling of its inherent unsteady flow process is required.

[0195] With the development of computer-aided engineering technology, computational fluid dynamics (CFD) has become an effective way to reveal the dynamic spreading mechanism of adhesives under pressure by numerically solving the above process. The liquid adhesive spreading process driven by the pressure of the cover plate is a typical gas-liquid two-phase interface fluid dynamics problem driven by moving boundaries. In this process, it is necessary to rigorously solve the unsteady continuity equation and the Navier-Stokes momentum equation, and accurately track the transient evolution of the gas-liquid interface. Among the mainstream numerical methods for handling large deformations of free interfaces in multiphase flows, the Volume of Fluid (VOF) method has become an important means of tracking gas-liquid interfaces due to its strict mass conservation properties and good adaptability to complex topological changes (such as interface fusion and rupture). The VOF method solves the transport equations of each phase volume fraction and uses the surface tension model to handle interphase interactions, avoiding the logical judgment problems related to interface intersection and overlap, and can effectively reconstruct continuous physical interfaces. By determining the position and orientation of the phase interface through phase functions, it can be applied to various phase interface boundary conditions in the calculation, providing convenience for tracking phase interfaces on three-dimensional meshes. To address the computational domain deformation problem caused by moving boundaries, dynamic meshing technology dynamically adjusts the position and topology of internal mesh nodes, enabling the discrete mesh to adaptively conform to the transient boundary of the pressing cover. Currently, mesh updating methods primarily describe the fluid control equations based on arbitrary Lagrange-Euler methods. This method extracts physical quantities from the original mesh using interpolation techniques and maps them onto the updated mesh. Subsequently, the physical quantities are iteratively calculated for each time step to solve the flow problem. With the development of CFD technology, current methods for implementing dynamic mesh updating mainly include the spring approximation method, the cut element method, the elastic body method, and the local mesh reconstruction method.

[0196] However, in the liquid adhesive bonding process between the cover plate and the substrate, the high-viscosity adhesive leveling within the slit is accompanied by significant free surface deformation, and the intense boundary motion easily leads to high distortion of the mesh in the near-wall region. Coupled dynamic meshing techniques and VOF multiphase flow models face bottlenecks such as computational diffusion, poor mass conservation, or computational divergence. Therefore, developing a numerical simulation method that can realistically simulate the movement of the structural boundary and the tracking of the multiphase fluid interface, and accurately predict the dynamic leveling characteristics of the adhesive under pressure at low cost and high efficiency, thereby guiding the optimization of bonding process parameters and reducing adhesive overflow and bubble defects, has significant engineering value in overcoming current process simulation bottlenecks.

[0197] In one embodiment, such as Figure 4 As shown, a method for simulating adhesive leveling is provided. Taking the application of this method in CFD software as an example, the method for simulating adhesive leveling includes the following steps:

[0198] Step S1, construct the simulation calculation domain for adhesive leveling, including the following steps:

[0199] Step S11: Establish a three-dimensional fluid computational domain based on the actual process model geometry.

[0200] Step S12: Extract the boundary contours of the adhesive liquid (corresponding to the fluid domain) and the substrate (corresponding to the second pressing wall surface), the adhesive liquid and the cover plate (corresponding to the first pressing wall surface), and the adhesive liquid in contact with air, and record the characteristic coordinate points (x, y, z) of the adhesive liquid distribution area.

[0201] Step S13: The irregular computational domain is geometrically cut into multiple regular spaces. In the 3D geometric modeling module, the fluid domains of each space are connected by sharing the topology. Different boundary types are grouped and named to generate a highly orthogonal structured mesh (i.e., the liquid leveling simulation computational domain).

[0202] Step S2 involves creating a high-quality mesh for the fluid domain and boundary layer, including the following steps:

[0203] Step S21: Name the fluid computation domain and boundary in the mesh generation module (Mesh), including the internal fluid computation domain (Glue_Air), top surface (Top), bottom surface (Bottom), symmetry plane (Symmetry), side walls (Right_Wall, Left_Wall), pressure outlet (Pressure_Outlet), etc., and set the global mesh cell reference size of the computation domain to 5e-5 m;

[0204] Step S22: Local mesh refinement is performed on the near-wall region of the cover plate and substrate to generate a boundary layer mesh that meets the requirements for capturing high-gradient macroscopic features in the near-wall region. The boundary layer thickness is calculated based on the moving boundary velocity, feature thickness, adhesive properties, and the target y+ value (y+ ≤ 2). A boundary layer mesh is generated on the cover plate and substrate surfaces using the local mesh refinement function (i.e., the boundary layer thickness of the first and second edge layer regions is calculated based on the movement velocity of the first and / or second pressing wall surfaces and the fluid properties of the fluid domain, so that the first layer mesh nodes of the first and second edge layer regions are located within the viscous sublayer). In this embodiment, y+ = 1, the number of boundary layers is 12, and the boundary layer mesh growth rate is 1.1.

[0205] Step S23: Define the node distribution pattern by setting different boundary mesh partition numbers. Specify that the mesh partition number in the middle deformation zone in the model thickness direction is three-ninths, and the size of the remaining boundary mesh elements is 3e-5 m. Set capture curvature constraints for geometric curved edges. Adopt a multi-zone meshing strategy, set the mapping / scan type of the internal mesh to hexahedral format, spatially discretize the overall fluid domain, output the fully structured computational mesh and transfer it to the fluid solver;

[0206] It should be noted that in this embodiment, the fluid domain is further divided into a top layer region, an intermediate deformation region, and a bottom layer region along the thickness direction. Both the top and bottom layers contain pre-defined boundary layer meshes, while the intermediate deformation region employs a layering dynamic meshing method. The purpose of this partitioning strategy is to maintain the topology and node spacing of the high-gradient boundary layer mesh near the wall throughout the pressing process, preventing the boundary layer mesh from disappearing due to dynamic meshing layering operations. This ensures accurate solutions for the gas-liquid interface and wall shear stress distribution during the adhesive flow process.

[0207] Step S3, setting up the computational fluid dynamics solver and boundary conditions, includes the following steps:

[0208] Step S31: Establish a VOF gas-liquid two-phase interface tracking model, whose phase volume fraction governing equation is:

[0209]

[0210]

[0211] In the formula, a qis the volume fraction of the q-th phase fluid, u is the fluid velocity vector, and m is the phase number. An implicit body force scheme is used, with the volume fraction parameter explicitly formulated, the volume fraction cutoff set to 0, and the Courant number set to 0.25. The Reynolds number of the flow is calculated (Re = ρvD / μ), and the viscous model is set to laminar flow.

[0212] Step S32: Activate the surface tension model and select the continuous surface force model. The formula for calculating the surface tension of a two-phase fluid is as follows:

[0213]

[0214] In the formula, ρ1 is the gas phase density, ρ2 is the liquid phase density, σ is the surface tension coefficient, and l is the surface curvature. Enabling the wall adhesion option allows the gas-liquid phase interaction to be characterized by specifying the surface tension coefficient. In this embodiment, the surface tension coefficient F is set based on experimental measurement data. vol It is 0.056;

[0215] Step S33: Define the primary phase (Phase-1) as air and the secondary phase (Phase-2) as the adhesive. Input the air density, air dynamic viscosity, and adhesive density sequentially. Use a power-law model to describe the dynamic viscosity of the adhesive.

[0216]

[0217] In the formula, τ is the shear stress, k is the consistency coefficient, γ is the shear rate, and n is the power-law exponent. Based on experimental measurement data, the consistency coefficient k = 200 and the power-law exponent n = 0.5 were set.

[0218] Step S34: Set the flow field boundary conditions. The wall contact angle of the moving boundary (glass cover) is given as 30°, and the contact angle of the other stationary walls is given as 45°. The open boundary of the flow field is set as the pressure outlet, and the reference gauge pressure is set as 0 Pa.

[0219] Step S35: Set the computational fluid dynamics solution method. The PISO algorithm is selected for pressure-velocity coupling. The momentum equation spatial discretization uses a second-order upwind scheme, the pressure interpolation term uses the PRESTO! format, and the time term discretization uses a first-order implicit scheme. The momentum sub-relaxation factor is set to 0.3 to improve the computational convergence of the moving mesh.

[0220] Step S4, configure dynamic mesh technology to simulate the pressing motion of the cover plate, including the following steps:

[0221] Step S41: Based on the actual pressing speed of the cover plate under working conditions (i.e., the preset pressing speed), the mesh motion conditions are compiled using UDF. In a specific embodiment, the code example of UDF is as follows:

[0222] #include "udf.h"

[0223] DEFINE_CG_MOTION (glass_press_motion, dt, vel, omega, time, dtime)

[0224] {

[0225] NV_S(vel, =, 0.0);

[0226] NV_S(omega, =, 0.0);

[0227] if (time <= 0.26)

[0228] {

[0229] vel[2] = -1.0e-2;

[0230] }

[0231] else

[0232] {

[0233] vel[2] = 0.0;

[0234] }

[0235] / / Message("Time: %f, V_z: %f\n", time, vel[2]);

[0236] }

[0237] Save the above code as a file with the .c extension (e.g., moving_wall.c), which determines the motion conditions. Then, load the UDF file using Compiled in the CFD software.

[0238] Step S42: Activate and configure dynamic meshing technology. Based on the spatial displacement characteristics of internal mesh nodes, set the parameters for smoothing, remeshing, or layering methods. In a specific implementation, for regular compressive deformation regions, the height-based layering method is used to control the mesh update mechanism. Specify the mesh distortion control parameters: the split factor is set to 0.4, and the collapse factor is set to 0.2.

[0239] It should be noted that in this embodiment, the geometric model is entirely divided into regular segments, and the mesh type is entirely structured mesh. Therefore, the Layering dynamic mesh method is used to achieve high-precision, low-divergence boundary tracking; if an unstructured mesh is used for complex and irregular geometry, the transient motion of the boundary is defined by setting the Smoothing and Remeshing methods.

[0240] Step S43: Apply rigid body constraints to the corresponding boundary of the cover plate in Dynamic Mesh Zones, and select glass_press_motion in the Motion UDF drop-down menu to create a dynamic mesh region.

[0241] Step S44: Before the formal calculation, output and save the Case file, set appropriate time steps and number of steps, verify transient region mesh deformation by displaying region motion and previewing mesh motion, and check the robustness of the dynamic mesh update strategy.

[0242] Step S5, iterative calculation and simulation result post-processing, includes the following steps:

[0243] Step S51, flow field initialization. Based on the three-dimensional coordinate eigenvalues ​​of the computational domain, the internal adhesive space and air space are defined. After performing a mixed initialization on the global flow field, a local repair technique is used to assign a volume fraction of 1 to the adhesive region and a value of 0 to the air space.

[0244] Step S52: Adjust the calculation time step according to the Courant number constraint. Based on the Courant-Friedrichs-Lewy condition, the calculation time step is:

[0245]

[0246] In the formula, δt is the time step, λ is the Courant number, and its value is less than or equal to 0.25; r i Let c be the smallest grid cell size in spatial direction i, and c be the fluid velocity.

[0247] Step S53: Set the total number of running steps, set the data file to be automatically saved every 200 time steps, solve the flow field based on the given calculation time step (1e-06) and total number of time steps (30000), and simultaneously monitor the residual curves of the continuity equation, momentum equation and volume fraction transport equation in real time.

[0248] Step S54: After solving, extract the volume fraction and velocity spatial distribution cloud map of the target phase. Quantify and output parameters such as the adhesive spreading area (xOz, yOz, and xOy planes), phase volume fraction, adhesive overflow amount, and wall shear stress at different cross-sections.

[0249] Step S6 involves analyzing the calculation results and providing theoretical guidance for practical engineering problems, including the following steps:

[0250] Step S61: By adjusting the dynamic mesh velocity parameters and adhesive rheological parameters, transient simulations are carried out for different pressing speeds, different structural features, different viscosities, and different dispensing amounts.

[0251] Step S62 quantifies and compares the characteristics of adhesive overflow at the model edge and internal bubble entrapment under various working conditions, providing a highly reliable adhesive dotting area range for the process. For example... Figure 5 As shown, the simulation results of adhesive spreading in the xOz plane are compared with different glass cover pressing speeds. It is found that as the glass cover is pressed down, the adhesive spreads evenly along the axial direction at the straight wall, while the adhesive is prone to overflow on the inner side of the curved wall. Increasing the pressing speed increases the spreading area of ​​the adhesive. Reducing the pressing speed of the glass cover is one of the effective means to suppress adhesive overflow.

[0252] This embodiment provides a method for simulating adhesive leveling. By integrating dynamic meshing technology with a local mesh refinement strategy for the boundary layer near the wall, it improves the adaptability of the 3D model to geometric boundary compression. This effectively overcomes the problem of distortion in the calculation of near-wall flow characteristics caused by severe mesh deformation, significantly enhancing the analytical capability and numerical computation robustness for adhesive viscous dissipation and high-shear flow fields within slits. This embodiment also fully leverages the strict mass conservation advantage of the VOF model when dealing with free, large-deformation interfaces. Through coupling with highly adaptable dynamic meshing technology, it can achieve accurate transient simulation of the dynamic spreading and leveling characteristics of the adhesive during the cap plate pressing process. This embodiment overcomes the limitations of traditional lamination processes that heavily rely on empirical trial and error. It allows for direct observation of transient changes in the gas-liquid interface during lamination, enabling quantitative prediction of edge adhesive overflow defects under multiple operating conditions. Therefore, it can provide a low-cost, high-reliability numerical theoretical basis for optimizing bonding process parameters in optical displays and semiconductor packaging.

[0253] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0254] Based on the same inventive concept, this application also provides an adhesive leveling simulation device for implementing the adhesive leveling simulation method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more adhesive leveling simulation device embodiments provided below can be found in the limitations of the adhesive leveling simulation method described above, and will not be repeated here.

[0255] In one embodiment, such as Figure 6 As shown, an adhesive leveling simulation device is provided, the device comprising:

[0256] Module 110 is used to construct a liquid leveling simulation calculation domain based on the geometric structural parameters and liquid physical property parameters of the target process model; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface;

[0257] The partitioning module 120 is used to divide the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressing walls. The first and second edge layer regions use boundary layer meshes with unchanged topology, while the intermediate deformation region uses a dynamic meshing method for mesh updating.

[0258] The simulation module 130 is used to simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface based on preset motion boundary conditions, and to simulate the leveling process of the fluid domain during the relative pressing motion based on the gas-liquid two-phase interface tracking model, so as to obtain the liquid leveling simulation results.

[0259] In one embodiment, the construction module 110 is further configured to:

[0260] A three-dimensional fluid computational domain is established based on the geometric dimensions of the target process model; the three-dimensional fluid computational domain includes the first pressing wall surface, the second pressing wall surface, and the fluid domain;

[0261] Identify the set of boundary contours of the three-dimensional fluid computational domain; the set of boundary contours includes at least wall contours and fluid interface contours;

[0262] Based on the boundary contour, the three-dimensional fluid computation domain is divided into multiple regular spaces;

[0263] Based on the shared topology, fluid domain connections are established between the various rule spaces to generate structured or unstructured computational grids, thus obtaining the computational domain for the liquid leveling simulation.

[0264] In one embodiment, the partitioning module 120 is further configured to:

[0265] Based on the movement velocity of the first and / or second pressed wall surfaces and the fluid property parameters of the fluid domain, the boundary layer thickness of the first and second edge layer regions is calculated so that the boundary layer grid cell size meets the preset viscous sublayer resolution condition.

[0266] In one embodiment, the simulation module 130 is further configured to:

[0267] The gas-liquid two-phase interface tracking model is constructed based on the fluid volume function method.

[0268] Configuring the gas-liquid two-phase interface tracking model includes: activating and configuring the surface tension model of the gas-liquid two-phase interface tracking model based on a preset surface tension coefficient; setting the gas phase as the main phase and the liquid phase as the secondary phase, and configuring the density and viscosity parameters of the gas phase and the liquid phase, wherein the viscosity parameter of the liquid phase is represented by a power-law model; and determining the flow field boundary conditions based on the wall contact angle and pressure outlet boundary conditions.

[0269] Based on the configuration results of the gas-liquid two-phase interface tracking model, the pressure-velocity coupling algorithm, spatial discretization scheme, and time discretization scheme used for the leveling process simulation are set.

[0270] In one embodiment, the preset motion boundary conditions include a preset downward pressure speed, and the simulation module 130 is further configured to:

[0271] The motion conditions of the first pressing wall surface and / or the second pressing wall surface are determined according to the preset pressing speed.

[0272] Using the first pressing wall surface and / or the second pressing wall surface as rigid body motion boundaries, and based on the motion conditions, simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface.

[0273] In one embodiment, the simulation module 130 is further configured to:

[0274] The fluid domain is mixed and initialized, and based on the preset initial distribution area of ​​the adhesive, a local repair algorithm is used to determine the initial volume fraction of each phase at each location in the fluid domain.

[0275] The time step for the simulation is determined based on the preset Courant number constraint.

[0276] Based on the time step and the initial value of the volume fraction, iterative flow field solution calculation is performed within a preset total number of running steps to obtain flow field data; the iterative flow field solution calculation process also includes: monitoring the residual value of the solution equation based on a preset residual convergence criterion;

[0277] Based on the flow field data, the simulation results of adhesive leveling were obtained.

[0278] In one embodiment, the simulation module 130 is further configured to:

[0279] Extract the phase volume fraction distribution cloud map and velocity spatial distribution cloud map of the adhesive in the fluid domain;

[0280] Based on the phase volume fraction distribution cloud map and velocity space distribution cloud map, the liquid leveling simulation results of the adhesive are determined; the liquid leveling simulation results include at least one of the following: spreading area on different cross sections, liquid overflow amount, and wall shear stress.

[0281] Each module in the aforementioned adhesive leveling simulation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0282] In one embodiment, such as Figure 7 As shown, a device for determining adhesive bonding process parameters is also provided. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the adhesive bonding process parameter determination device provided below can be found in the limitations of the adhesive bonding process parameter determination method above, and will not be repeated here. The adhesive bonding process parameter determination device may include:

[0283] The acquisition module 210 is used to acquire the geometric structure parameters and adhesive physical property parameters of the target product;

[0284] Simulation module 220 is used to perform simulation based on the geometric structure parameters and adhesive property parameters, using the adhesive leveling simulation method described in any of the above embodiments, to obtain adhesive leveling simulation results under different combinations of process parameters; the combination of process parameters includes one or more of the following: preset motion boundary conditions, adhesive volume, adhesive viscosity, and initial distribution area of ​​adhesive.

[0285] The determination module 230 is used to take the process parameter combination corresponding to the glue leveling simulation result where the spreading area reaches the preset requirement, the glue overflow amount is not greater than the preset threshold, and there is no air bubble entrainment as the target process parameter combination.

[0286] In another embodiment, the simulation module 220 can be implemented by embedding the adhesive leveling simulation device described in any of the above embodiments.

[0287] The modules in the aforementioned adhesive leveling simulation device and adhesive bonding process parameter determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0288] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for simulating adhesive leveling. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0289] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0290] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the adhesive leveling simulation method of any of the above embodiments:

[0291] Based on the geometric parameters and adhesive properties of the target process model, a liquid leveling simulation calculation domain is constructed; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface;

[0292] Along the direction of the change in the distance between the first and second pressed wall surfaces, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region; wherein, the first and second edge layer regions adopt boundary layer meshes with unchanged topology, and the intermediate deformation region adopts a dynamic meshing method for mesh updating;

[0293] Based on preset motion boundary conditions, the relative pressing motion between the first pressing wall surface and the second pressing wall surface is simulated, and based on the gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the liquid leveling simulation results.

[0294] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the adhesive leveling simulation method of any of the above embodiments:

[0295] Based on the geometric parameters and adhesive properties of the target process model, a liquid leveling simulation calculation domain is constructed; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface;

[0296] Along the direction of the change in the distance between the first and second pressed wall surfaces, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region; wherein, the first and second edge layer regions adopt boundary layer meshes with unchanged topology, and the intermediate deformation region adopts a dynamic meshing method for mesh updating;

[0297] Based on preset motion boundary conditions, the relative pressing motion between the first pressing wall surface and the second pressing wall surface is simulated, and based on the gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the liquid leveling simulation results.

[0298] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0299] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0300] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0301] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for simulating adhesive leveling, characterized in that, The adhesive leveling simulation method, applied to the process of adhesive being subjected to pressure, includes: Based on the geometric parameters and adhesive properties of the target process model, a liquid leveling simulation calculation domain is constructed; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface; Along the direction of the change in the distance between the first and second pressed wall surfaces, the fluid domain is divided into a first edge layer region, an intermediate deformation region, and a second edge layer region; wherein, the first and second edge layer regions use boundary layer meshes with unchanged topology, and the intermediate deformation region uses a dynamic meshing method for mesh updating; the dynamic meshing method includes dynamically adjusting the position and topology of internal mesh nodes; Based on preset motion boundary conditions, the relative pressing motion between the first pressing wall surface and the second pressing wall surface is simulated, and based on the gas-liquid two-phase interface tracking model, the leveling process of the fluid domain during the relative pressing motion is simulated to obtain the liquid leveling simulation results.

2. The adhesive leveling simulation method according to claim 1, characterized in that, The construction of the adhesive leveling simulation calculation domain based on the dimensions of the target process model includes: A three-dimensional fluid computational domain is established based on the geometric dimensions of the target process model; the three-dimensional fluid computational domain includes the first pressing wall surface, the second pressing wall surface, and the fluid domain; Identify the set of boundary contours of the three-dimensional fluid computational domain; the set of boundary contours includes at least wall contours and fluid interface contours; Based on the boundary contour, the three-dimensional fluid computation domain is divided into multiple regular spaces; Based on the shared topology, fluid domain connections are established between the various rule spaces to generate structured or unstructured computational grids, thus obtaining the computational domain for the liquid leveling simulation.

3. The adhesive leveling simulation method according to claim 1, characterized in that, The method of dividing the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in distance between the first and second pressed wall surfaces further includes: Based on the movement velocity of the first and / or second pressed wall surfaces and the fluid property parameters of the fluid domain, the boundary layer thickness of the first and second edge layer regions is calculated so that the boundary layer grid cell size meets the preset viscous sublayer resolution condition.

4. The adhesive leveling simulation method according to claim 1, characterized in that, The simulation of the leveling process in the fluid domain during the relative compression motion, based on the gas-liquid two-phase interface tracking model, further includes: The gas-liquid two-phase interface tracking model is constructed based on the fluid volume function method. Configuring the gas-liquid two-phase interface tracking model includes: activating and configuring the surface tension model of the gas-liquid two-phase interface tracking model based on a preset surface tension coefficient; setting the gas phase as the main phase and the liquid phase as the secondary phase, and configuring the density and viscosity parameters of the gas phase and the liquid phase, wherein the viscosity parameter of the liquid phase is represented by a power-law model; and determining the flow field boundary conditions based on the wall contact angle and pressure outlet boundary conditions. Based on the configuration results of the gas-liquid two-phase interface tracking model, the pressure-velocity coupling algorithm, spatial discretization scheme, and time discretization scheme used for the leveling process simulation are set.

5. The adhesive leveling simulation method according to claim 1, characterized in that, The preset motion boundary conditions include a preset pressing speed, and the simulation of the relative pressing motion between the first pressing wall surface and the second pressing wall surface based on the preset motion boundary conditions includes: The motion conditions of the first pressing wall surface and / or the second pressing wall surface are determined according to the preset pressing speed. Using the first pressing wall surface and / or the second pressing wall surface as rigid body motion boundaries, and based on the motion conditions, simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface.

6. The adhesive leveling simulation method according to claim 1, characterized in that, The simulation of the flow leveling process of the fluid domain during the relative compression motion, based on the gas-liquid two-phase interface tracking model, and the resulting simulation results of the adhesive flow leveling, further include: The fluid domain is mixed and initialized, and based on the preset initial distribution area of ​​the adhesive, a local repair algorithm is used to determine the initial volume fraction of each phase at each location in the fluid domain. The time step for the simulation is determined based on the preset Courant number constraint. Based on the time step and the initial value of the volume fraction, iterative flow field solution calculation is performed within a preset total number of running steps to obtain flow field data; the iterative flow field solution calculation process also includes: monitoring the residual value of the solution equation based on a preset residual convergence criterion; Based on the flow field data, the simulation results of adhesive leveling were obtained.

7. The adhesive leveling simulation method according to claim 1 or claim 6, characterized in that, The obtained adhesive leveling simulation results include: Extract the phase volume fraction distribution cloud map and velocity spatial distribution cloud map of the adhesive in the fluid domain; Based on the phase volume fraction distribution cloud map and velocity space distribution cloud map, the liquid leveling simulation results of the adhesive are determined; the liquid leveling simulation results include at least one of the following: spreading area on different cross sections, liquid overflow amount, and wall shear stress.

8. A method for determining adhesive bonding process parameters, characterized in that, The method for determining the adhesive bonding process parameters includes: Obtain the geometric structure parameters and adhesive properties parameters of the target product; Based on the geometric structure parameters and adhesive properties, simulation is performed using the adhesive leveling simulation method as described in any one of claims 1 to 7 to obtain adhesive leveling simulation results under different combinations of process parameters; the combination of process parameters includes one or more of the following: preset motion boundary conditions, adhesive volume, adhesive viscosity, and initial distribution region of adhesive. The combination of process parameters corresponding to the simulation results of adhesive leveling where the spreading area reaches the preset requirements, the amount of adhesive overflow does not exceed the preset threshold, and there is no air bubble entrainment is taken as the target process parameter combination.

9. A device for simulating adhesive leveling, characterized in that, The device includes: A construction module is used to construct a liquid leveling simulation calculation domain based on the geometric structural parameters and liquid physical property parameters of the target process model; the liquid leveling simulation calculation domain includes a first pressing wall surface, a second pressing wall surface, and a fluid domain located between the first pressing wall surface and the second pressing wall surface; A partitioning module is used to divide the fluid domain into a first edge layer region, an intermediate deformation region, and a second edge layer region along the direction of the change in the distance between the first and second pressing wall surfaces; wherein, the first and second edge layer regions adopt boundary layer meshes with unchanged topology, and the intermediate deformation region adopts a dynamic meshing method for mesh updating; the dynamic meshing method includes dynamically adjusting the position and topology of the internal mesh nodes; The simulation module is used to simulate the relative pressing motion between the first pressing wall surface and the second pressing wall surface based on preset motion boundary conditions, and to simulate the leveling process of the fluid domain during the relative pressing motion based on the gas-liquid two-phase interface tracking model, so as to obtain the liquid leveling simulation results.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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