Method for predicting dynamic evolution behavior of micro-characteristics in neodymium-iron-boron grain boundary diffusion process

Abstract

The application relates to a method and system for predicting the dynamic evolution behavior of micro characteristics in a neodymium-iron-boron grain boundary diffusion process, a computer device and a storage medium. The method comprises the following steps: acquiring different phase component parameters and microstructure distribution characteristics of the neodymium-iron-boron alloy; performing lattice reconstruction on the microstructure distribution characteristics to obtain a polycrystal model of the neodymium-iron-boron; constructing an alloy internal flow heat transfer model and performing Boltzmann discretization on the alloy internal flow heat transfer model according to the polycrystal model and the different phase component parameters, simulating a sintering grain boundary diffusion process of the neodymium-iron-boron; acquiring microstructure parameters at each moment of the grain boundary diffusion process, performing visual processing on the microstructure parameters at each moment, and obtaining the distribution characteristics of different phases and different components in the grain boundary diffusion process of the neodymium-iron-boron. The method solves the problem that the internal micro characteristic evolution behavior in the grain boundary diffusion of the neodymium-iron-boron cannot be observed by experiments, and realizes dynamic display of the change rule of the microstructure and composition in the grain boundary diffusion process of the neodymium-iron-boron.

Description

Technical Field

[0001] This application relates to the field of NdFeB grain boundary diffusion technology, and in particular to a method, system, computer device, and storage medium for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion. Background Technology

[0002] Neodymium iron boron (NdFeB) permanent magnets are widely used in national defense, electronics, and mechanical engineering due to their superior magnetic properties, including high coercivity, high remanence, and high energy product. They are among the most widely used magnetic materials today. In recent years, grain boundary diffusion technology, utilizing heat treatment, has enabled heavy rare earth elements such as Dy / Tb in NdFeB to diffuse from the magnet surface along the molten grain boundary phase into the interior. This results in the formation of a RE-Fe-B core-shell structure in the main phase grains, improving the intrinsic magnetic properties of the magnet. Furthermore, the non-magnetic rare earth components within the grain boundary phase help suppress exchange coupling between main phase grains, thereby increasing the magnet's coercivity. This process also requires less rare earth, effectively conserving heavy rare earth resources. However, during the NdFeB sintering grain boundary diffusion process, the grain boundary phase exhibits a molten flow dynamic, and diffusion segregation of elements occurs. The multiphase, multi-component microstructure within the magnet exhibits an inhomogeneous, irregular, and non-periodic dynamic evolution process. Moreover, the distribution of different phase components has a reaction effect on the element distribution and phase structure formation during the diffusion process, posing a challenge to the rational optimization of the grain boundary diffusion process.

[0003] Traditional experimental methods can only observe the microstructure and elemental distribution characteristics of NdFeB permanent magnets after the grain boundary diffusion process has ended. They cannot achieve in-situ observation because the grain boundary diffusion process needs to be carried out under high temperature conditions. Therefore, it is difficult to use experimental characterization methods to capture the evolution process of multiphase and multicomponents in the magnet and visualize the diffusion process. This is not conducive to subsequent targeted optimization of NdFeB diffusion formulation and diffusion process.

[0004] Therefore, by establishing a reasonable and feasible mesoscale mathematical model through numerical simulation, the dynamic behavior of microstructure and element distribution during grain boundary diffusion can be revealed, making the process visible. This is a great supplement to the existing grain boundary diffusion process and has important practical production guidance significance. Summary of the Invention

[0005] Based on this, it is necessary to provide a mathematical model for numerical simulation to explore the evolution behavior of microstructure and element distribution during the diffusion of NdFeB grain boundaries, as well as a method, system, computer equipment, and computer-readable storage medium for predicting the dynamic evolution behavior of microstructure during the diffusion of NdFeB grain boundaries.

[0006] In a first aspect, this application provides a method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, the method comprising:

[0007] To obtain the phase composition parameters and microstructure distribution characteristics of NdFeB alloys;

[0008] Based on the aforementioned microstructure distribution characteristics, lattice reconstruction was performed to obtain the polycrystalline model of the neodymium iron boron.

[0009] An internal flow and heat transfer model of the alloy is constructed, and the Boltzmann discretization process is performed on the internal flow and heat transfer model of the alloy based on the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of the NdFeB alloy.

[0010] The microstructure parameters at each moment of the sintering crystal boundary diffusion process are obtained, and the microstructure parameters at each moment are visualized to obtain the distribution characteristics of different phases and components of NdFeB during the crystal boundary diffusion process.

[0011] In one embodiment, the step of performing Boltzmann discretization on the internal flow and heat transfer model of the alloy based on the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of the NdFeB alloy includes:

[0012] Based on the structural characteristics of the polycrystalline model, the computational domain of the internal flow and heat transfer model of the alloy and the mesh parameters of the polycrystalline model are initialized; the start and end times and boundary conditions of the NdFeB simulated sintering boundary diffusion process are set; based on the different phase composition parameters of the alloy, the physical properties of the mesh node particles in the computational domain at each moment during the simulated sintering process are obtained; the boundary conditions are executed, and the microstructure parameters of the mesh node particles are extracted based on the physical properties at each moment, until the termination time of the NdFeB simulated sintering boundary diffusion process is reached.

[0013] In one embodiment, the physical properties at each time step include the density distribution function, enthalpy distribution function, and mass fraction distribution function of each grid node, and obtaining the physical properties of the grid node particles at each time step during the simulated sintering boundary diffusion process includes:

[0014] Construct the collision step and migration step equations for the particles in the grid nodes; based on the collision step and migration step equations, obtain the density distribution function, enthalpy distribution function, and mass fraction distribution function in different directions for each grid node.

[0015] In one embodiment, the microstructure parameters include the densities of different phases in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions include no-slip boundary conditions; the execution of the boundary conditions, and the extraction of the microstructure parameters of the grid node particles based on the physical characteristics at each time step, includes:

[0016] Based on the density equilibrium distribution function of each grid node and the migration direction and velocity of the particles at each grid node, the collision step and migration step equations of the particles at each time step are executed to obtain the density distribution function of the particles at each grid node in different directions; the no-slip boundary condition is executed, and the density distribution functions in different directions are summed to obtain the macroscopic density of each grid node; the macroscopic density of each grid node is the density of different phases in the NdFeB simulated sintering crystal boundary diffusion process.

[0017] In one embodiment, the microstructure parameters include the temperature and liquid phase volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions further include iso-wall temperature boundary conditions; the step of executing the boundary conditions and extracting the microstructure parameters of the grid node particles based on the physical characteristics at each time step further includes:

[0018] Based on the enthalpy equilibrium distribution function of each grid node and the migration direction and velocity of the particles at the grid nodes, the collision step and migration step equations of the particles at each time step are executed to obtain the enthalpy distribution function in different directions; the iso-wall temperature boundary condition is executed, and the enthalpy distribution functions in different directions are summed to obtain the enthalpy of each grid node; based on the enthalpy of each grid node, the temperature and liquid phase volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process are obtained.

[0019] In one embodiment, the microstructure parameters include the elemental concentrations within different phases during the NdFeB sintering process, and the boundary conditions include equal-concentration boundary conditions; the step of executing the boundary conditions and extracting the microstructure parameters of the grid node particles based on the physical characteristics at each time step further includes:

[0020] Based on the obtained equilibrium distribution function of mass fraction at each grid node and the migration direction and velocity of the particles at the grid node, the collision step and migration step equations of NdFeB at each time step are executed to obtain the element mass fraction distribution function in different directions; the isoconcentration boundary condition is executed to sum the element mass fraction distribution functions in different directions to obtain the mass fraction of each grid node; based on the mass fraction of each grid node, the element concentration in different phases during the NdFeB sintering process is obtained.

[0021] In one embodiment, constructing the internal flow and heat transfer model of the alloy includes:

[0022] Based on the alloy density and melt flow velocity of the polycrystalline model, a mass conservation equation is constructed for the interior of the alloy. Based on the kinetic viscosity of different phase components in the polycrystalline model, as well as the alloy density and melt flow velocity, a momentum conservation equation is constructed for different phase components of the alloy. Based on the specific heat capacity, temperature, latent heat of solidification, liquid phase volume fraction of different phase components in the polycrystalline model, as well as the alloy density and melt flow velocity, an energy conservation equation is constructed for different phase components of the alloy. Based on the mass conservation equation, momentum conservation equation, and energy conservation equation for different phase components of the alloy, a flow and heat transfer model for the interior of the alloy is constructed.

[0023] Secondly, this application also provides a system for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, the system comprising:

[0024] The parameter structure acquisition module is used to acquire the different phase composition parameters and microstructure distribution characteristics of NdFeB alloys;

[0025] The structure lattice reconstruction module is used to perform lattice reconstruction based on the microstructure distribution characteristics to obtain the polycrystalline model of the neodymium iron boron.

[0026] The grain boundary diffusion simulation module is used to construct an internal flow and heat transfer model of the alloy, and to perform Boltzmann discretization processing on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters, so as to simulate the sintering grain boundary diffusion process of the NdFeB.

[0027] The microstructure visualization module is used to obtain the microstructure parameters at various moments during the sintering grain boundary diffusion process, and to visualize the microstructure parameters at each moment to obtain the distribution characteristics of different phases and components of NdFeB during the grain boundary diffusion process.

[0028] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps corresponding to the method described in the first aspect.

[0029] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps corresponding to the method described in the first aspect.

[0030] In the aforementioned method, system, computer equipment, and storage medium for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, the following steps are taken: First, different phase composition parameters and microstructure distribution characteristics of the NdFeB alloy are obtained. Based on these microstructure distribution characteristics, lattice reconstruction is performed to obtain a polycrystalline model of the NdFeB alloy. Second, an internal flow and heat transfer model of the alloy is constructed. Third, based on the polycrystalline model and the different phase composition parameters, the internal flow and heat transfer model of the alloy is subjected to Boltzmann discretization to simulate the sintering grain boundary diffusion process of the NdFeB alloy. Finally, the sintering process is analyzed. The microstructure parameters at various moments during the grain boundary diffusion process are obtained and visualized to show the distribution characteristics of different phases and components in the NdFeB grain boundary diffusion process. This enables a dynamic display of the changes in the microstructure and composition of NdFeB permanent magnet materials during grain boundary diffusion, which is beneficial for reverse optimization of the NdFeB grain boundary diffusion process. Furthermore, a mesoscale mathematical model is used to solve the complex grain boundary and grain boundary distribution problems during NdFeB grain boundary diffusion, thereby improving the accuracy of the distribution characteristics of each phase and component in the NdFeB grain boundary diffusion process. Attached Figure Description

[0031] Figure 1 This is an application environment diagram of a method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion in one embodiment.

[0032] Figure 2 This is a flowchart illustrating a method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion in one embodiment.

[0033] Figure 3 This is a flowchart illustrating step 203 in one embodiment;

[0034] Figure 4 This is a schematic diagram of the process for obtaining density-related microstructure parameters in one embodiment;

[0035] Figure 5 This is a schematic diagram of the process for obtaining microstructure parameters related to temperature and liquid volume fraction in one embodiment;

[0036] Figure 6 This is a schematic diagram of the process for obtaining microstructure parameters related to elemental concentration in one embodiment;

[0037] Figure 7 This is a schematic diagram of the process for constructing an internal flow and heat transfer model of an alloy in one embodiment;

[0038] Figure 8 This is a simulated structural distribution diagram of a neodymium iron boron alloy in an example embodiment;

[0039] Figure 9This is a schematic diagram illustrating the liquid phase ratio between the main phase and the grain boundary phase regions during grain boundary diffusion in an example embodiment.

[0040] Figure 10 This is an elemental distribution diagram of pure Tb in the grain boundary diffusion process in an example embodiment;

[0041] Figure 11 This is a structural block diagram of a system for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion in one embodiment.

[0042] Figure 12 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0043] 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.

[0044] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. “Multiple” in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character “ / ” generally indicates that the preceding and following related objects are in an “or” relationship. The terms “first,” “second,” “third,” etc., used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0045] The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion provided in this application can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. Data storage system 106 can store the data that server 104 needs to process. Data storage system 106 can be integrated on server 104 or placed on the cloud or other network servers. On server 104, by acquiring the different phase composition parameters and microstructure distribution characteristics of the NdFeB alloy, lattice reconstruction is performed based on the microstructure distribution characteristics to obtain the polycrystalline model of NdFeB; an internal flow and heat transfer model of the alloy is constructed, and Boltzmann discretization is performed on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of NdFeB; microstructure parameters at each moment of the sintering boundary diffusion process are acquired, and the microstructure parameters at each moment are visualized to obtain the distribution characteristics of different phases and components of NdFeB in the grain boundary diffusion process. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc. Server 104 can be implemented using a standalone server or a server cluster composed of multiple servers.

[0046] In one embodiment, such as Figure 2 As shown, a method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion is provided, and this method is applied to… Figure 1 Taking the server side as an example, the explanation includes the following steps:

[0047] Step 201: Obtain the different phase composition parameters and microstructure distribution characteristics of the NdFeB alloy.

[0048] The NdFeB alloy material comprises Nd2Fe14B main phase grains, rare earth-rich grain boundary phases, and a small amount of rare earth oxides. During sintering, the grain boundary diffusers are alloy materials containing heavy rare earth Tb / Dy. The different phase composition parameters of the alloy include, but are not limited to, the volume fraction, density, thermal conductivity, kinetic viscosity, and specific heat capacity of different phases. Since the NdFeB alloy is a multiphase, multi-component material, it is necessary to obtain the different phase composition parameters and the microstructure distribution characteristics of the alloy before simulating grain boundary diffusion during NdFeB sintering.

[0049] Step 202: Based on the structural distribution characteristics, perform lattice reconstruction to obtain the polycrystalline model of the neodymium iron boron.

[0050] Specifically, based on the microstructure distribution characteristics of the alloy, the microstructure of the NdFeB alloy is reconstructed to obtain a polycrystalline model of NdFeB. The methods for reconstructing the microstructure include, but are not limited to, the Thiessen polygonal mesh reconstruction method.

[0051] Step 203: Construct an internal flow and heat transfer model of the alloy, and perform Boltzmann discretization processing on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of the NdFeB.

[0052] Specifically, during the grain boundary diffusion process, NdFeB alloys exhibit multiphase and multi-component characteristics. It is necessary to consider the presence of solid-liquid mixed phases in some regions of the magnet. Therefore, an internal flow and heat transfer model of NdFeB alloys is constructed. Based on the polycrystalline model of NdFeB, the different phase composition parameters of the alloy are imported into the internal flow and heat transfer model of the alloy and subjected to Boltzmann discretization to simulate the sintering grain boundary diffusion process of NdFeB.

[0053] Step 204: Obtain the microstructure parameters at each moment of the sintering crystal boundary diffusion process, and visualize the microstructure parameters at each moment to obtain the distribution characteristics of different phases and components during the NdFeB crystal boundary diffusion process.

[0054] Specifically, the microstructure parameters at each local location at time t during the NdFeB sintering crystal boundary diffusion process are obtained and visualized to generate corresponding visualization charts, thereby obtaining the distribution characteristics of different phases and components in the simulated NdFeB sintering crystal boundary diffusion process.

[0055] In the aforementioned method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, the following steps are taken: First, obtain the different phase composition parameters and microstructure distribution characteristics of the NdFeB alloy. Second, based on the microstructure distribution characteristics, perform lattice reconstruction to obtain a polycrystalline model of the NdFeB. Third, construct an internal flow and heat transfer model of the alloy, and perform Boltzmann discretization processing on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters to simulate the sintering grain boundary diffusion process of the NdFeB. Finally, obtain the sintering grain boundary diffusion... The microstructure parameters at various moments during the diffusion process are obtained and visualized to show the distribution characteristics of different phases and components in the NdFeB sintering process. This dynamically displays the changes in microstructure and composition of NdFeB permanent magnet materials during grain boundary diffusion, which is beneficial for reverse optimization of the NdFeB grain boundary diffusion process. Furthermore, a mesoscale mathematical model is used to solve the complex grain boundary and grain boundary distribution problems during NdFeB grain boundary diffusion, thereby improving the accuracy of the distribution characteristics of each phase and component in NdFeB grain boundary diffusion.

[0056] In one embodiment, such as Figure 3 As shown, step 203 involves performing Boltzmann discretization on the internal flow and heat transfer model of the alloy based on the polycrystalline model and the different phase composition parameters, to simulate the sintering boundary diffusion process of the NdFeB alloy. Specifically, this includes the following:

[0057] Step 301: Based on the structural characteristics of the polycrystalline model, initialize the computational domain of the internal flow and heat transfer model of the alloy and the mesh parameters of the polycrystalline model.

[0058] Step 302: Set the start and end times and boundary conditions for the NdFeB simulated sintering crystal boundary diffusion process.

[0059] Step 303: Based on the different phase composition parameters of the alloy, obtain the physical properties of the grid node particles at each moment during the simulated sintering process.

[0060] Step 304: Execute the boundary conditions and extract the microstructure parameters of the grid node particles according to the physical characteristics at each time point until the termination time of the NdFeB simulated sintering crystal boundary diffusion process is reached.

[0061] Specifically, based on the structural characteristics of the polycrystalline model, such as volume, the computational domain of the internal flow and heat transfer model of the alloy and the mesh parameters of the polycrystalline model are initialized. Simultaneously, the start and end times and boundary conditions of the NdFeB simulation sintering boundary diffusion process are set, with the initial time set to t=1 and the termination time set to t=t. max Based on the different phase composition parameters of the alloy, the physical properties of the mesh node particles at each time t during the sintering process simulated by the internal flow and heat transfer model of the alloy are obtained. These physical properties include the density distribution function, enthalpy distribution function, and mass fraction distribution function of each mesh node.

[0062] Next, boundary conditions are applied, followed by the extraction of microstructure parameters of the mesh node particles, i.e., macroscopic quantities at various local locations during the NdFeB sintering crystal boundary diffusion process, until the termination time t of the simulated NdFeB sintering crystal boundary diffusion process is reached. max .

[0063] In this embodiment, by importing the different composition parameters of NdFeB into the internal flow and heat transfer model of the alloy and performing Boltzmann discretization, the microstructure parameters of the grid node particles are extracted based on the grain boundary phase flow characteristics of the grid node particles at each moment during the simulated sintering process. This yields the distribution of a certain element at a local location during the grain boundary diffusion process of sintered NdFeB, thereby improving the accuracy of the dynamic distribution characteristics of different phases and components of NdFeB during the simulated grain boundary diffusion.

[0064] In one embodiment, step 303 obtains the physical properties of the mesh node particles at each moment during the simulated sintering process, specifically including the following:

[0065] Construct the collision step and migration step equations for the particles in the grid nodes; based on the collision step and migration step equations, obtain the density distribution function, enthalpy distribution function, and mass fraction distribution function in different directions for each grid node.

[0066] More specifically, the microstructure parameters include the densities of different phase components in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions include no-slip boundary conditions. For example... Figure 4 As shown, step 304 executes the boundary conditions and extracts the microstructure parameters of the mesh node particles based on the physical characteristics at each time step. This specifically includes the following steps:

[0067] Step 401: Based on the obtained density equilibrium distribution function on each grid node and the migration direction and migration speed of the particles on the grid node, execute the collision step and migration step equations of the particles at each time step to obtain the density distribution function of the particles on each grid node in different directions.

[0068] Step 402: Execute the no-slip boundary condition and sum the density distribution functions in different directions to obtain the macroscopic density of each grid node. The macroscopic density of each grid node is the density of different phases in the NdFeB simulated sintering crystal boundary diffusion process.

[0069] For example, based on the obtained density equilibrium distribution function f on each grid node i eq Given (x,t) and the migration direction i and migration velocity e of the particles in the grid nodes, execute the collision step and migration step equations for the particles at each time step:

[0070] ;

[0071] ;

[0072] in, This represents the migration process of particles at grid nodes with respect to density. This represents the collision process of particles at grid nodes with respect to density. Let τ be the density distribution function of particles at each grid node in different directions, and let τ represent the relaxation time, which is determined by the dynamic viscosity, density, and other properties of the phase. c represents the time step. s U represents the speed of sound in a lattice. eq The macroscopic velocity of the particle. This represents the net external force acting on a grid node. This represents the weight coefficients for different directions of particles in the mesh node. No-slip boundary conditions are applied. Density distribution functions in different directions Summation yields the macroscopic density of each grid node. That is, the different phase densities in the simulated NdFeB crystal boundary diffusion process:

[0073] ;

[0074] Preferably, the microstructure parameters include the flow characteristics of different phase compositions during the NdFeB simulated sintering-glucopyranosphere diffusion process. Based on the macroscopic density of each grid node, the flow characteristics of the NdFeB alloy during the sintering-glucopyranosphere diffusion process are simultaneously obtained.

[0075] ;

[0076] in, This represents the flow characteristics of NdFeB alloy during the diffusion process at the crystal boundary during sintering, where i represents the migration direction of particles at the mesh nodes. The value represents the migration velocity of the particles at the grid nodes, and u represents the flow velocity of the NdFeB alloy melt.

[0077] More specifically, the microstructure parameters include the temperature and liquid phase volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions also include isowall temperature boundary conditions. For example... Figure 5 As shown, step 304 executes the boundary conditions and extracts the microstructure parameters of the mesh node particles based on the physical characteristics at each time step. Specifically, it also includes the following steps:

[0078] Step 501: Based on the enthalpy equilibrium distribution function of each grid node and the migration direction and migration speed of the particles at the grid nodes, execute the collision step and migration step equations of the particles at each time step to obtain the enthalpy distribution function in different directions.

[0079] The enthalpy distribution function can represent the heat transfer characteristics of particles at each grid node within the computational domain.

[0080] Step 502: Execute the isobaric boundary condition, sum the enthalpy distribution functions in different directions, and obtain the enthalpy of each grid node.

[0081] Step 503: Based on the enthalpy of each grid node, obtain the temperature and liquid phase volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process.

[0082] For example, based on the obtained enthalpy equilibrium distribution function h at each grid node i eq Given (x,t) and the migration direction i and migration velocity e of the mesh node particles, execute the collision step and migration step equations for the particles at each time step:

[0083] ;

[0084] ;

[0085] in, This represents the migration process of particles at grid nodes with respect to enthalpy. This represents the collision process of particles at grid nodes with respect to enthalpy. Let represent the enthalpy distribution function in different directions, and τ represent the relaxation time. c represents the time step. s U represents the speed of sound in a lattice. eq Here, T represents the macroscopic velocity of the particle, and T represents the temperature of different phases of the alloy. This represents the weight coefficients for different directions of particles in a grid node.

[0086] Apply isobaric boundary conditions to the enthalpy distribution functions in different directions. Summing is performed to obtain the enthalpy H of each grid node:

[0087] ;

[0088] Based on the enthalpy H of each grid node, the liquid phase volume fraction f of different phases in the NdFeB simulated sintering crystal boundary diffusion process is obtained. L :

[0089] ;

[0090] Where H1 represents the liquid phase enthalpy threshold and Hs represents the solid phase enthalpy threshold. The enthalpy H of each grid node is compared with the solid-liquid enthalpy threshold to determine the threshold range in which each grid node's enthalpy H falls. When the enthalpy H is less than or equal to the solid phase enthalpy threshold Hs, the liquid phase volume fraction f at the local location represented by that grid node is determined. L The value is 0; when the enthalpy H is greater than the solid phase enthalpy threshold Hs and less than the liquid phase enthalpy threshold H1, the liquid phase volume fraction f at the local location represented by the grid node is 0. L The ratio of the difference between enthalpy H and the solid phase enthalpy threshold Hs to the difference between the liquid phase enthalpy threshold H1 and the solid phase enthalpy threshold Hs; the liquid volume fraction f at the local location represented by the grid node when enthalpy H is greater than or equal to the liquid phase enthalpy threshold H1. L The value is 1.

[0091] Based on the enthalpy H of each grid node, the temperatures T of different phases in the simulated NdFeB sintering crystal boundary diffusion process are obtained:

[0092] ;

[0093] Where Ts represents the solid-state temperature between the main phase and the grain boundary phase in the NdFeB alloy, T L c represents the liquidus temperature between the main phase and the grain boundary phase in NdFeB alloys. pThis represents the specific heat capacity of the NdFeB alloy. The enthalpy H of each grid node is compared with the liquid phase enthalpy threshold and the solid phase enthalpy threshold to determine the threshold range in which the enthalpy H of each grid node falls. When enthalpy H is less than or equal to the solid phase enthalpy threshold Hs, the temperature T of the local location represented by this grid node is the first temperature obtained; when enthalpy H is greater than the solid phase enthalpy threshold Hs and less than the liquid phase enthalpy threshold H1, the temperature T of the local location represented by this grid node is the second temperature obtained; when enthalpy H is greater than or equal to the liquid phase enthalpy threshold H1, the temperature T of the local location represented by this grid node is the third temperature obtained.

[0094] More specifically, the microstructure parameters include the elemental concentrations of different phase components in the NdFeB sintering process, and the boundary conditions include isoconcentration boundary conditions. For example... Figure 6 As shown, step 304 executes the boundary conditions and extracts the microstructure parameters of the mesh node particles based on the physical characteristics at each time step. Specifically, it also includes the following steps:

[0095] Step 601: Based on the obtained mass fraction equilibrium distribution function on each grid node and the migration direction and migration speed of the particles at the grid node, execute the collision step and migration step equations of the NdFeB at each moment to obtain the element mass fraction distribution function in different directions.

[0096] The element mass fraction distribution function represents the element migration characteristics of particles at each grid node within the computational domain.

[0097] Step 602: Execute the isoconcentration boundary conditions, sum the mass fraction distribution functions in different directions, and obtain the mass fraction of each grid node.

[0098] Step 603: Obtain the element concentrations in different phases during the NdFeB sintering process based on the mass fraction of each grid node.

[0099] For example, based on the obtained mass fraction equilibrium distribution function g at each grid node i eq Given (x,t) and the migration direction i and migration velocity e of the grid node particles, execute the collision step and migration step equations for the NdFeB at each time step:

[0100] ;

[0101] ;

[0102] in, This represents the migration process of particles at grid nodes with respect to their mass fraction. This represents the collision process of particles at grid nodes with respect to their mass fraction. Let represent the mass fraction distribution function in different directions, and τ represent the relaxation time. c represents the time step. s U represents the speed of sound in a lattice. eq The macroscopic velocity of the particle. Represents the diffusion coefficient of elements in different phases. This represents the weight coefficients for different directions of particles in a grid node.

[0103] An isoconcentration boundary condition is applied. When describing the concentration of a specific element in a local region of the alloy, the isoconcentration boundary condition is set as follows: the diffusion surface boundary is the high-concentration boundary with a dimensionless value of 1, and the non-diffusion surface boundary is the low-concentration boundary with a dimensionless value of 0. The element mass fraction distribution function in different directions is then applied. Summing yields the mass fraction G for each grid node:

[0104] ;

[0105] Based on the mass fraction of each grid node, the elemental concentrations of different phase components in the NdFeB sintering process are obtained. :

[0106] .

[0107] In one embodiment, such as Figure 7 As shown, step 203 involves constructing an internal flow and heat transfer model for the alloy, specifically including the following steps:

[0108] Step 701: Based on the alloy density and alloy melt flow rate of the polycrystalline model, construct the mass conservation equation inside the alloy.

[0109] Step 702: Based on the kinetic viscosity of different phase components in the polycrystalline model, the alloy density, and the alloy melt flow velocity, construct the momentum conservation equation for different phase components of the alloy.

[0110] Step 703: Based on the specific heat capacity, temperature, latent heat of solidification, liquid volume fraction, alloy density, and alloy melt flow rate of different phase components in the polycrystalline model, construct the energy conservation equation for different phase components of the alloy.

[0111] Step 704: Based on the mass conservation equation, momentum conservation equation, and energy conservation equation for different phase compositions of the alloy, construct the internal flow and heat transfer model of the alloy.

[0112] For example, the mass conservation equation for the internal flow and heat transfer model of the alloy is constructed as follows:

[0113] ;

[0114] The momentum conservation equation for constructing the internal flow and heat transfer model of the alloy is as follows:

[0115] ;

[0116] The energy conservation equation for constructing the internal flow and heat transfer model of the alloy is as follows:

[0117] ;

[0118] Where ρ' represents the alloy density, u represents the melt flow rate of the alloy, κ represents the thermal conductivity of the NdFeB alloy, and c p denoted by , p represents the specific heat capacity of the NdFeB alloy, g represents the molten NdFeB alloy pressure during the calculation, μ represents the kinetic viscosity of the NdFeB alloy, T' represents the temperature of the NdFeB alloy during the calculation, and t represents time. This represents the latent heat of solidification, where L represents the latent heat and f L This indicates the volume fraction of the liquid phase.

[0119] In this embodiment, a lattice Boltzmann mesoscale mathematical model is constructed by building an internal flow and heat transfer model of the alloy. The Boltzmann discretization process is then performed using this internal flow and heat transfer model of the alloy to simulate the sintering boundary diffusion process of NdFeB.

[0120] In one example embodiment, a method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion is provided. This example embodiment takes NdFeB grain boundary diffusion as an example, assuming that the microphase distribution within the NdFeB alloy is regular, and the simulated structural distribution can be seen in... Figure 8 In the graph, blue represents grain boundary phases, and red represents main phase grains. The horizontal axis represents the number of grids in the horizontal direction, and the vertical axis represents the number of grids in the vertical direction. The main phase grain composition of the NdFeB alloy is Nd2Fe. 14 B, where the grain boundary phase is pure Nd, containing no rare earth oxides, and the diffuser is pure Tb, its diffusion process is predicted. Specifically, the following steps are included:

[0121] Step 801: Based on the characteristics of the main phase grains and pure Nd phase elements, set the composition parameters of different calculation regions of the NdFeB polycrystalline model, and initialize the density, velocity, temperature and concentration of the overall calculation region of the NdFeB polycrystalline model.

[0122] Step 802: The compositional parameters of different computational regions of the NdFeB polycrystalline model are imported into the alloy's internal flow and heat transfer model, i.e., the three-dimensional D3Q19 lattice Boltzmann model, for Boltzmann discretization to simulate the sintering boundary diffusion process of NdFeB. Based on the temperature changes within the NdFeB alloy during the sintering boundary diffusion process, the evolution behavior of the solid and liquid phases within the NdFeB alloy at each moment is obtained. Simultaneously, based on the migration characteristics of pure Tb under different compositions, its distribution characteristics in the main phase grains and Nd-rich grain boundary phases are calculated. Figure 9 The graphs show the liquid phase ratio in the main phase and grain boundary phase regions during grain boundary diffusion. Four figures represent the liquid phase ratio in the main phase and grain boundary phase regions at times t=1, t=1000, t=2000, and t=3000. The horizontal axis represents the number of grid cells in the horizontal direction, the vertical axis represents the number of grid cells in the vertical direction, and liquid_volume represents the liquid phase volume fraction. Because the sintering temperature is above the melting point of the grain boundary phase but below the main phase grains, the grain boundary phase continuously melts, the liquid phase ratio continuously increases, and eventually the entire phase becomes molten.

[0123] Step 803 involves processing data on the evolution of the solid and liquid phases within the NdFeB alloy at each time step, and the distribution characteristics of the diffuser pure Tb in the main phase grains and Nd-rich grain boundary phases at each time step. This data is used to predict the segregation and migration characteristics of different phase elements within the NdFeB alloy during grain boundary diffusion, as well as the dynamic evolution of the microstructure of the main phase grains and grain boundary phases. The distribution of the diffuser pure Tb at different locations within the NdFeB alloy is tracked, diffusion characteristics are analyzed, and visualization of the solid-liquid phase and elemental distribution during grain boundary diffusion is achieved. Figure 10 This is a pure Tb elemental distribution diagram of the diffuser during grain boundary diffusion. The horizontal axis represents the number of grid cells in the horizontal direction, the vertical axis represents the number of grid cells in the vertical direction, and mass_fraction represents the mass fraction of the alloying element. Figure 10 It can be seen that during the grain boundary diffusion process, Tb element gradually diffuses from the surface into the NdFeB alloy. Due to the fluidity of the molten grain boundary phase, more Tb element diffuses into the grain boundary phase, resulting in a higher mass fraction in the grain boundary phase.

[0124] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially as indicated by 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. These steps or stages are not necessarily completed at the same time, but can be executed at different times, and 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 a portion of steps or stages in other steps.

[0125] Based on the same inventive concept, this application also provides a system for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, used to implement the aforementioned method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more NdFeB grain boundary diffusion dynamic behavior prediction visualization system embodiments provided below can be found in the limitations of the NdFeB grain boundary diffusion dynamic behavior prediction method described above, and will not be repeated here.

[0126] In one embodiment, such as Figure 11 As shown, a system for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion is provided, comprising: a parameter structure acquisition module 110, a structure lattice reconstruction module 111, a grain boundary diffusion simulation module 112, and a microstructure visualization module 113, wherein:

[0127] The parameter structure acquisition module 110 is used to acquire the different phase composition parameters and microstructure distribution characteristics of the NdFeB alloy.

[0128] The structure lattice reconstruction module 111 is used to perform lattice reconstruction based on the microstructure distribution characteristics to obtain the polycrystalline model of the neodymium iron boron.

[0129] The grain boundary diffusion simulation module 112 is used to construct an internal flow and heat transfer model of the alloy, and to perform Boltzmann discretization processing on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters, so as to simulate the sintering grain boundary diffusion process of the NdFeB.

[0130] The microstructure visualization module 113 is used to obtain the microstructure parameters at each moment of the sintering crystal boundary diffusion process, and to visualize the microstructure parameters at each moment to obtain the distribution characteristics of different phases and different components during the NdFeB sintering crystal boundary diffusion process.

[0131] In one embodiment, the grain boundary diffusion simulation module 112 is further configured to:

[0132] Based on the structural characteristics of the polycrystalline model, the computational domain of the internal flow and heat transfer model of the alloy and the mesh parameters of the polycrystalline model are initialized; the start and end times and boundary conditions of the NdFeB simulated sintering crystal boundary diffusion process are set; based on the different phase composition parameters of the alloy, the grain boundary phase flow characteristics of the mesh node particles at each moment during the simulated sintering process are obtained; the boundary conditions are executed, and the microstructure parameters of the mesh node particles are extracted based on the grain boundary phase flow characteristics at each moment, until the termination time of the NdFeB simulated sintering crystal boundary diffusion process is reached.

[0133] In one embodiment, the physical properties include the density distribution function, enthalpy distribution function, and mass fraction distribution function of each grid node. The grain boundary diffusion simulation module 112 is further used to: construct the collision step and migration step equations of the grid node particles; and obtain the density distribution function, enthalpy distribution function, and mass fraction distribution function of each grid node in different directions according to the collision step and migration step equations.

[0134] In one embodiment, the microstructure parameters include the densities of different phases in the NdFeB simulated sintering crystal boundary diffusion process, the boundary conditions include no-slip boundary conditions, and the grain boundary diffusion simulation module 112 is further configured to: execute the collision step and migration step equations of the particles at each time step based on the obtained density equilibrium distribution function on each grid node and the migration direction and migration velocity of the particles on the grid node, to obtain the density distribution function of the particles on each grid node in different directions; execute the no-slip boundary conditions, and sum the density distribution functions in different directions to obtain the macroscopic density of each grid node; the macroscopic density of each grid node is the density of different phases in the NdFeB simulated sintering crystal boundary diffusion process.

[0135] In one embodiment, the microstructure parameters include the temperature and liquid volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process. The boundary conditions also include isobaric boundary conditions. The crystal boundary diffusion simulation module 112 is further configured to: execute the collision step and migration step equations of the particles at each time step based on the obtained enthalpy equilibrium distribution function on each grid node and the migration direction and migration velocity of the particles at the grid nodes, to obtain enthalpy distribution functions in different directions; execute the isobaric boundary conditions to sum the enthalpy distribution functions in different directions to obtain the enthalpy of each grid node; and obtain the temperature and liquid volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process based on the enthalpy of each grid node.

[0136] In one embodiment, the microstructure parameters include the elemental concentrations of different phase components in the NdFeB sintering process, the boundary conditions include isoconcentration boundary conditions, and the grain boundary diffusion simulation module 112 is further configured to: execute the collision step and migration step equations of the NdFeB at each moment based on the obtained mass fraction equilibrium distribution function on each grid node and the migration direction and migration velocity of the particles at the grid nodes, to obtain the elemental mass fraction distribution functions in different directions; execute the isoconcentration boundary conditions to sum the elemental mass fraction distribution functions in different directions to obtain the mass fraction of each grid node; and obtain the elemental concentrations of different phase components in the NdFeB sintering process based on the mass fraction of each grid node.

[0137] In one embodiment, the grain boundary diffusion simulation module 112 is further configured to: construct a mass conservation equation for the interior of the alloy based on the alloy density and melt flow velocity of the polycrystalline model; construct a momentum conservation equation for different phase components of the alloy based on the kinetic viscosity of different phase components in the polycrystalline model, the alloy density, and the melt flow velocity of the alloy; construct an energy conservation equation for different phase components of the alloy based on the specific heat capacity, temperature, latent heat of solidification, liquid phase volume fraction of different phase components in the polycrystalline model, the alloy density, and the melt flow velocity of the alloy; and construct a flow and heat transfer model for the interior of the alloy based on the mass conservation equation, momentum conservation equation, and energy conservation equation for different phase components of the alloy.

[0138] The modules in the aforementioned prediction and visualization system for the dynamic behavior of NdFeB grain boundary diffusion 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 memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0139] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 12 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores NdFeB alloy data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a method for predicting and visualizing the dynamic behavior of NdFeB during grain boundary diffusion.

[0140] 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 steps corresponding to the methods described in the above embodiments.

[0141] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method for predicting and visualizing the dynamic behavior during NdFeB grain boundary diffusion as described in the above embodiments.

[0142] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the method for predicting and visualizing the dynamic behavior during NdFeB grain boundary diffusion as described in the above embodiments.

[0143] 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.

[0144] 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 predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, characterized in that, The method includes: To obtain the phase composition parameters and microstructure distribution characteristics of NdFeB alloys; Based on the aforementioned microstructure distribution characteristics, lattice reconstruction was performed to obtain the polycrystalline model of the neodymium iron boron. An internal flow and heat transfer model of the alloy is constructed, and the Boltzmann discretization process is performed on the internal flow and heat transfer model of the alloy based on the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of the NdFeB alloy. The microstructure parameters at each moment of the sintering crystal boundary diffusion process are obtained, and the microstructure parameters at each moment are visualized to obtain the distribution characteristics of different phases and components of NdFeB during the crystal boundary diffusion process.

2. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 1, characterized in that, The step of performing Boltzmann discretization on the internal flow and heat transfer model of the alloy based on the polycrystalline model and the different phase composition parameters to simulate the sintering boundary diffusion process of the NdFeB alloy includes: Based on the structural characteristics of the polycrystalline model, the computational domain of the internal flow and heat transfer model of the alloy and the mesh parameters of the polycrystalline model are initialized. Set the start and end times and boundary conditions for the NdFeB simulated sintering crystal boundary diffusion process; Based on the different phase composition parameters of the alloy, the physical properties of the computational domain grid node particles at each moment during the simulated sintering process are obtained; The boundary conditions are applied, and the microstructure parameters of the grid node particles are extracted based on the physical characteristics at each time point until the termination time of the NdFeB simulated sintering crystal boundary diffusion process is reached.

3. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 2, characterized in that, The physical properties at each moment include the density distribution function, enthalpy distribution function, and elemental mass fraction distribution function of each grid node. Obtaining the physical properties of the grid node particles at each moment during the simulated sintering process includes: Construct the equations for the collision step and migration step of particles in the mesh nodes; Based on the collision step and migration step equations, the density distribution function, enthalpy distribution function, and element mass fraction distribution function of each grid node in different directions are obtained.

4. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 3, characterized in that, The microstructure parameters include the densities of different phases in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions include no-slip boundary conditions; the execution of the boundary conditions, based on the physical characteristics at each time step, extracts the microstructure parameters of the grid node particles, including: Based on the density equilibrium distribution function of each grid node and the migration direction and migration speed of the particles at each grid node, the collision step and migration step equations of the particles at each time step are executed to obtain the density distribution function of the particles at each grid node in different directions. By applying the no-slip boundary condition, the density distribution functions in different directions are summed to obtain the macroscopic density of each grid node; the macroscopic density of each grid node is the density of different phases in the NdFeB simulated sintering crystal boundary diffusion process.

5. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 3, characterized in that, The microstructure parameters include the temperature and liquid phase volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process, and the boundary conditions also include iso-wall temperature boundary conditions; the step of executing the boundary conditions and extracting the microstructure parameters of the grid node particles based on the physical characteristics at each time step further includes: Based on the enthalpy equilibrium distribution function of each grid node and the migration direction and migration speed of the particles at the grid nodes, the collision step and migration step equations of the particles at each time step are executed to obtain the enthalpy distribution function in different directions. By applying the isobaric boundary condition, the enthalpy distribution functions in different directions are summed to obtain the enthalpy of each grid node; Based on the enthalpy of each grid node, the temperature and liquid volume fraction of different phases in the NdFeB simulated sintering crystal boundary diffusion process are obtained.

6. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 3, characterized in that, The microstructure parameters include the elemental concentrations within different phases during the NdFeB sintering process, and the boundary conditions include equal-concentration boundary conditions; the step of executing the boundary conditions and extracting the microstructure parameters of the grid node particles based on the physical characteristics at each moment further includes: Based on the obtained mass fraction equilibrium distribution function on each grid node and the migration direction and migration speed of the particles at the grid node, the collision step and migration step equations of the NdFeB at each time step are executed to obtain the element mass fraction distribution function in different directions. By applying the isoconcentration boundary conditions, the element mass fraction distribution functions in different directions are summed to obtain the mass fraction of each grid node; The element concentrations in different phases during the NdFeB sintering process are obtained based on the mass fraction of each grid node.

7. The method for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion according to claim 1, characterized in that, The constructed alloy internal flow and heat transfer model includes: Based on the alloy density and melt flow rate of the polycrystalline model, a mass conservation equation is constructed for the interior of the alloy. Based on the kinetic viscosity of different phase components in the polycrystalline model, as well as the alloy density and the melt flow velocity of the alloy, momentum conservation equations for different phase components of the alloy are constructed. Based on the specific heat capacity, temperature, latent heat of solidification, liquid volume fraction, alloy density, and alloy melt flow rate of different phase components in the polycrystalline model, an energy conservation equation for different phase components of the alloy is constructed. Based on the mass conservation equation, momentum conservation equation, and energy conservation equation for different phase compositions of the alloy, a flow and heat transfer model for the internal flow of the alloy is constructed.

8. A system for predicting the dynamic evolution of microstructures during NdFeB grain boundary diffusion, characterized in that, The system includes: The parameter structure acquisition module is used to acquire the different phase composition parameters and microstructure distribution characteristics of NdFeB alloys; The structure lattice reconstruction module is used to perform lattice reconstruction based on the microstructure distribution characteristics to obtain the polycrystalline model of the neodymium iron boron. The grain boundary diffusion simulation module is used to construct an internal flow and heat transfer model of the alloy, and to perform Boltzmann discretization processing on the internal flow and heat transfer model of the alloy according to the polycrystalline model and the different phase composition parameters, so as to simulate the sintering grain boundary diffusion process of the NdFeB. The microstructure visualization module is used to obtain the microstructure parameters at various moments during the sintering grain boundary diffusion process, and to visualize the microstructure parameters at each moment to obtain the distribution characteristics of different phases and components of NdFeB during the grain boundary diffusion process.

9. 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 steps of the method according to any one of claims 1 to 7.

10. 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 steps of the method according to any one of claims 1 to 7.

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