Microstructure simulation method and apparatus, electronic device, and storage medium

Abstract

Embodiments of the present application disclose a microstructure simulation method and device, electronic equipment and storage medium. The method comprises the following steps: step 1, generating an initial microstructure; step 2, reading a loading condition from a finite element simulation result of a cutting process; step 3, non-continuous dynamic recrystallization nucleation simulation; step 4, continuous dynamic recrystallization simulation; step 5, updating dislocation density; step 6, dynamic recrystallization grain growth simulation; step 7, judging whether a simulation actual time consumption reaches a simulation total time, if the simulation actual time consumption does not reach the simulation total time, repeating steps 3 to 6; if the simulation actual time consumption reaches the simulation total time, stopping the simulation. Through the present application, the technical problem that a microstructure simulation method of a cutting process in the related art ignores a continuous dynamic recrystallization mechanism is solved, and the technical effect that the microstructure evolution behavior of the cutting process can be more accurately simulated is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of numerical simulation of cutting process, and in particular, to a microstructure simulation method and device, an electronic device, and a storage medium. BACKGROUND

[0002] Cutting is one of the most important methods for product forming. Due to the mechanical contact between the tool and the workpiece material, it usually causes severe plastic deformation of the workpiece surface, resulting in complex changes in the microstructure of the workpiece surface, which has an important influence on the service performance of the product. Therefore, in order to obtain high-performance products, it is of great significance to study the evolution of microstructure in the cutting process. Since the deformation time in the cutting process is extremely short, it is difficult to observe the entire process of microstructure evolution through experimental methods. With the rapid development of computer technology and the continuous improvement of related material processing theory, numerical simulation calculation gradually shows the advantages of real-time, dynamic visualization, etc. that experimental methods cannot match.

[0003] Cellular automata is a method that uses a series of regular or irregular discrete points to represent real continuous space, and describes the evolution law of the state of a complex system in discrete space through deterministic or probabilistic transformation rules on these discrete points. In recent years, the cellular automata method has shown its unique advantages in the simulation of microstructure evolution such as recrystallization, grain growth and phase change phenomena, and has developed into an important method for simulating the evolution of material microstructure.

[0004] In the prior art, the temperature field, strain rate field and strain field of the titanium alloy cutting process are obtained by finite element simulation, the shear zone is simplified as a constant loading deformation process, and the temperature, strain rate and strain of the shear zone are obtained from the finite element simulation results as input conditions for the cellular automata simulation. A theoretical model of non-continuous dynamic recrystallization is established as the transformation rule for the cellular automata simulation, so as to realize the simulation of microstructure evolution in the shear zone. However, this method only considers one dynamic recrystallization mechanism of non-continuous dynamic recrystallization, but ignores the influence of continuous dynamic recrystallization.

[0005] In view of the problem in the related art that the microstructure simulation method in the cutting process ignores the continuous dynamic recrystallization mechanism, no effective solution has been proposed. SUMMARY

[0006] Embodiments of the present application provide a microstructure simulation method, device, electronic device and storage medium to at least solve the technical problem that the microstructure simulation method in the cutting process in the related art ignores the continuous dynamic recrystallization mechanism.

[0007] According to an aspect of the embodiments of the present application, a microstructure simulation method is provided, comprising: step 1, generating an initial microstructure; step 2, reading loading conditions from a finite element simulation result of a cutting process; step 3, non-continuous dynamic recrystallization nucleation simulation; step 4, continuous dynamic recrystallization simulation; step 5, updating dislocation density; step 6, dynamic recrystallization grain growth simulation; step 7, judging whether a simulation actual time consumption reaches a simulation total time, if the simulation actual time consumption does not reach the simulation total time, repeating the steps 3 to 6, and if the simulation actual time consumption reaches the simulation total time, stopping the simulation.

[0008] Optionally, the step 1 comprises the following specific implementation steps: step 1.1, determining a simulation region, discretizing the simulation region into a grid composed of cells, and calculating a grain number N of the simulation region according to an average grain size of a target base material n ; step 1.2, randomly selecting N n cells in the simulation region as initial nuclei, and assigning different grain number variables and grain orientation variables to the selected N n cells, and setting a grain boundary migration distance variable of a current cell to be one cell length; step 1.3, performing the following calculation on all cells one by one: if the current cell has not been assigned a grain number and the grain boundary migration distance is greater than or equal to a distance between two adjacent cells, the state of the current cell is changed to a neighbor cell state; step 1.4, repeating the step 1.3 until all cells in the simulation region are assigned the grain number and a cell state variable is assigned an initial value, wherein the initial value of the cell state variable at least includes an initial value of a dislocation density variable, an initial value of a recrystallization number variable, and an initial value of a subgrain number variable.

[0009] Optionally, the step 2 comprises the following specific implementation steps: extracting a strain, a maximum temperature, and a maximum strain rate of a center position of a simulation region from a finite element simulation result of a cutting process, and determining a time step and a total simulation time.

[0010] Optionally, the step 3 comprises the following specific implementation steps: scanning the entire cell space, if a dislocation density of a cell exceeds a non-continuous dynamic recrystallization critical dislocation density and the cell is at a grain boundary position, a current cell has a first predetermined probability to be converted into a non-continuous dynamic recrystallization nucleus; if the current nucleus is converted into the non-continuous dynamic recrystallization nucleus, updating a state variable thereof, setting a dislocation density variable, setting a grain orientation variable to a random value, setting a recrystallization number variable to a current recrystallization number + 1, obtaining a maximum grain number N g of the current cell, and setting a grain number variable to N g + 1.

[0011] Optionally, the step 4 comprises the following specific implementation steps: step 4.1, scanning the whole cell space, if the average dislocation density of the grain / sub-grain exceeds the critical dislocation density of sub-grain formation, the current grain / sub-grain has a second predetermined probability to split to generate a new sub-grain; step 4.2, if the current grain / sub-grain splits to generate a new sub-grain, the state variable is updated, and the current cell maximum grain number is obtained as N s , the sub-grain numbers of the cells in the newly generated sub-grain are set as N s +1, N s +2, N s +3, and the first dislocation density increment due to the generation of sub-grain is calculated; step 4.3, scanning the whole cell space, the rotation angle of all sub-grains is calculated, the sub-grain orientation angle is updated, if the sub-grain orientation angle exceeds the critical grain boundary angle, the cell state is updated, the grain orientation variable is set as a random value, the recrystallization frequency variable is set as the current recrystallization frequency + 1, and the current cell maximum grain number is obtained as N g , the grain number variable is set as N g +1, and the second dislocation density increment due to the rotation of sub-grain is calculated.

[0012] Optionally, the step 5 comprises the following specific implementation steps: the dislocation density increment of each cell in the current increment step is calculated, and the dislocation density is updated.

[0013] Optionally, the step 6 comprises the following specific implementation steps: scanning the whole cell space, the grain boundary migration driving force and migration distance of the recrystallized grain are calculated; if the migration distance is greater than the distance between adjacent two cells, the current cell state is changed to the neighbor cell state with the recrystallization frequency greater than or equal to 1.

[0014] According to another aspect of the embodiment of the present application, a microstructure simulation device is also provided, comprising: a generating module for generating an initial microstructure; a reading module for reading loading conditions from a finite element simulation result of a cutting process; a first simulation module for a non-continuous dynamic recrystallization nucleation simulation; a second simulation module for a continuous dynamic recrystallization simulation; an updating module for updating dislocation density; a third simulation module for a dynamic recrystallization grain growth simulation; a judging module for judging whether a simulation actual time consumption reaches a simulation total time, if the simulation actual time consumption does not reach the simulation total time, the implementation step contents corresponding to the first simulation module to the third simulation module are repeatedly executed; if the simulation actual time consumption reaches the simulation total time, the simulation is stopped.

[0015] According to another aspect of the embodiments of the present application, an electronic device is also provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the microstructure simulation method according to any one of the preceding embodiments.

[0016] According to another aspect of the embodiments of the present application, a storage medium is also provided, comprising a stored program, wherein the program, when executed, controls a device in which the storage medium is located to perform the microstructure simulation method according to any one of the preceding embodiments.

[0017] In the embodiments of the present application, step 1 is adopted to generate an initial microstructure; step 2 is adopted to read loading conditions from finite element simulation results of a cutting process; step 3 is adopted to simulate non-continuous dynamic recrystallization nucleation; step 4 is adopted to simulate continuous dynamic recrystallization; step 5 is adopted to update dislocation density; step 6 is adopted to simulate dynamic recrystallization grain growth; and step 7 is adopted to judge whether a simulation actual time consumption has reached a simulation total time, if the simulation actual time consumption has not reached the simulation total time, steps 3 to 6 are repeatedly executed; and if the simulation actual time consumption has reached the simulation total time, the simulation is stopped. That is to say, the embodiments of the present application comprehensively consider non-continuous dynamic recrystallization and continuous dynamic recrystallization, establish a cellular automaton model considering the two dynamic recrystallization mechanisms, and realize microstructure simulation oriented to a cutting process in combination with finite element simulation, thereby solving the technical problem that a microstructure simulation method of a cutting process in the related art ignores a continuous dynamic recrystallization mechanism, and achieving the technical effect that the microstructure evolution behavior of the cutting process can be more accurately simulated. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0019] Figure 1 A flow chart of a microstructure simulation method provided by the embodiments of the present application;

[0020] Figure 2 A flow chart of a microstructure simulation method oriented to a cutting process provided by the embodiments of the present application;

[0021] Figure 3 A schematic diagram of a Von Neumann type neighbor relationship of a microstructure simulation method oriented to a cutting process provided by the embodiments of the present application;

[0022] FIG. 4(a) is a schematic diagram of finite element simulation results of a titanium alloy cutting process about strain of a microstructure simulation method oriented to a cutting process provided by the embodiments of the present application;

[0023] Fig. 4(b) is a diagram of strain rate of an example result of finite element simulation of a titanium alloy cutting process according to the microstructure simulation method for a cutting process provided by the embodiment of the present application;

[0024] Fig. 4(c) is a diagram of temperature of an example result of finite element simulation of a titanium alloy cutting process according to the microstructure simulation method for a cutting process provided by the embodiment of the present application;

[0025] Figure 5 Fig. 5 is a diagram of microstructure evolution simulation result of the microstructure simulation method for a cutting process provided by the embodiment of the present application;

[0026] Figure 6 Fig. 6 is a diagram of comparison between the predicted value and the measured value of average grain size of the microstructure simulation method for a cutting process provided by the embodiment of the present application;

[0027] Figure 7 Fig. 7 is a diagram of the microstructure simulation device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0029] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the drawings are used to distinguish different objects, but not to limit a specific sequence. The steps shown in the flowchart of the drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical sequence is shown in the flowchart, in some cases, the steps shown or described can be executed in a sequence different from that here.

[0030] Figure 1 Fig. 8 is a flowchart of the microstructure simulation method provided by the embodiment of the present application, as shown in the figure, the method comprises the following steps: Figure 1

[0031] Step 1, generating an initial microstructure;

[0032] Step 2, reading loading conditions from the finite element simulation result of the cutting process;

[0033] Step 3, non-continuous dynamic recrystallization nucleation simulation;

[0034] ​Step 4, continuous dynamic recrystallization simulation;

[0035] Step 5, updating dislocation density;

[0036] Step 6, dynamic recrystallization grain growth simulation;

[0037] Step 7, judging whether the simulation actual time consumption reaches the simulation total time, if the simulation actual time consumption does not reach the simulation total time, repeating steps 3 to 6; if the simulation actual time consumption reaches the simulation total time, stopping the simulation.

[0038] In the embodiment of the present application, step 1 is adopted to generate an initial microstructure; step 2 is adopted to read loading conditions from cutting process finite element simulation results; step 3 is adopted to perform non-continuous dynamic recrystallization nucleation simulation; step 4 is adopted to perform continuous dynamic recrystallization simulation; step 5 is adopted to update dislocation density; step 6 is adopted to perform dynamic recrystallization grain growth simulation; and step 7 is adopted to judge whether the simulation actual time consumption reaches the simulation total time, if the simulation actual time consumption does not reach the simulation total time, repeating steps 3 to 6; if the simulation actual time consumption reaches the simulation total time, stopping the simulation. That is to say, the embodiment of the present application comprehensively considers non-continuous dynamic recrystallization and continuous dynamic recrystallization, establishes a cellular automaton model considering the two dynamic recrystallization mechanisms, and realizes microstructure simulation for a cutting process in combination with finite element simulation, thereby solving the technical problem in the prior art that a cutting process microstructure simulation method ignores the continuous dynamic recrystallization mechanism, and achieving the technical effect that the microstructure evolution behavior of the cutting process can be more accurately simulated.

[0039] It should be noted that the application scenarios of the above microstructure simulation method include but are not limited to metal cutting process microstructure evolution numerical simulation.

[0040] In an optional embodiment, step 1 includes the following specific implementation steps:

[0041] Step 1.1, determining a simulation region, discretizing the simulation region into a grid composed of cells, and calculating the number N of grains of the simulation region according to the average grain size of the target base material n ;

[0042] Step 1.2, randomly selecting N n cells in the simulation region as initial nuclei, and assigning different grain number variables and grain orientation variables to the selected N n cells, and setting the grain boundary migration distance variable of the current cell to 1 cell length;

[0043] Step 1.3, perform the following calculations for each cell: If the current cell has not yet been assigned a grain number and the grain boundary migration distance is greater than or equal to the distance between two adjacent cells, then change the state of the current cell to the state of the neighboring cell.

[0044] Step 1.4: Repeat step 1.3 until all cells in the simulation region are assigned grain numbers and initial values ​​are assigned to the cell state variables. The initial values ​​assigned to the cell state variables include at least the initial values ​​of the dislocation density variable, the initial values ​​of the recrystallization number variable, and the initial values ​​of the subgrain number variable.

[0045] In one optional implementation, step 2 above includes the following specific implementation steps: extracting the strain, maximum temperature and maximum strain rate at the center of the simulation region from the finite element simulation results of the cutting process, and determining the time step and total simulation time.

[0046] In an optional implementation, step 3 above includes the following specific implementation steps: scanning the entire cell space; if the dislocation density of the cell exceeds the critical dislocation density for discontinuous dynamic recrystallization and the cell is located at a grain boundary, then the current cell has a first predetermined probability of transforming into a discontinuous dynamic recrystallization nucleus; if the current nucleus transforms into a discontinuous dynamic recrystallization nucleus, its state variables are updated, the dislocation density variable is set, the grain orientation variable is set to a random value, and the recrystallization number variable is set to the current recrystallization number + 1, thus obtaining the maximum grain number of the current cell as N. g The grain number variable is set to N. g +1.

[0047] It should be noted that the above-mentioned first predetermined probability uses P. d express.

[0048] In one optional implementation, step 4 above includes the following specific implementation steps:

[0049] Step 4.1: Scan the entire cell space. If the average dislocation density of the grain / subgrain exceeds the critical dislocation density for subgrain formation, the current grain / subgrain has a second predetermined probability of splitting to generate a new subgrain.

[0050] Step 4.2: If the current grain / subgrain splits to generate a new subgrain, update its state variables to obtain the maximum grain number of the current cell as N. s The subgrain numbers of the newly generated subgrain cells are respectively set as N. s +1、N s +2、N s +3, and calculate the first fault density increment due to the formation of subgrains;

[0051] It should be noted that the above-mentioned second predetermined probability uses P. cwherein the first dislocation density increment is represented by Δρ 1- wherein the first dislocation density increment is represented by Δρ

[0052] Step 4.3, scanning the whole cell space, calculating the rotation angle of all subgrains, updating the subgrain orientation angle, if the subgrain orientation angle exceeds the critical grain boundary angle, updating the cell state, setting the grain orientation variable to a random value, setting the recrystallization times variable to the current recrystallization times + 1, and obtaining the current cell maximum grain number N g , setting the grain number variable to N g + 1, and calculating the second dislocation density increment caused by the subgrain rotation.

[0053] It should be noted that the second dislocation density increment is represented by Δρ 2- .

[0054] In an optional embodiment, the step 5 includes the following specific implementation steps: calculating the dislocation density increment of each cell in the current increment step, and updating the dislocation density.

[0055] In an optional embodiment, the step 6 includes the following specific implementation steps: scanning the whole cell space, calculating the grain boundary migration driving force and migration distance of the recrystallized grain; if the migration distance is greater than the distance between the adjacent two cells, the current cell state is converted to the neighbor cell state with the recrystallization times greater than or equal to 1.

[0056] The specific implementation of the present application will be described below with titanium alloy TC4 as the research object.

[0057] In view of the deficiency of the existing microstructure simulation method for the cutting process that ignores the continuous dynamic recrystallization mechanism, the optional embodiment of the present application proposes a microstructure simulation method for the cutting process. The method comprehensively considers the discontinuous dynamic recrystallization and the continuous dynamic recrystallization, establishes a cellular automaton model considering the two dynamic recrystallization mechanisms, and realizes the microstructure simulation for the cutting process in combination with the finite element simulation, thereby providing theoretical support for in-depth research on the dynamic recrystallization mechanism of the cutting process.

[0058] Figure 2 The flowchart of the microstructure simulation method for the cutting process provided by the embodiment of the present application is shown in FIG. Figure 2 , and is implemented according to the following steps.

[0059] Step 1, generating an initial microstructure, including the following sub-steps:

[0060] Selecting a simulation area of 200×200um 2 , discretizing the simulation area into 1000×1000 grids, and setting the side length of each square cell to L c0.2 um, the grain number N of the simulation area is calculated according to the average grain size d0=20 um of the actually measured TC4 base material n =10000 / (πd0 2 / 4);

[0061] N n initial crystal nuclei are randomly selected in the selected simulation area, and the selected N n initial crystal nuclei are assigned different grain number variables and grain orientation variables, and the grain boundary migration distance variable of the current cell is set to 0.2 um; Figure 3 A schematic diagram of the Von Neumann type neighbor relationship of a microstructure simulation method for a cutting process provided by the embodiment of the application is shown in Figure 3 The Von Neumann type neighbor is used to calculate the state of the cell, and the state of the cell is determined by the nearest four cells around it;

[0062] The following calculation is performed on all cells one by one: if the current cell has not been assigned a grain number and the neighbor cell grain boundary migration distance is greater than or equal to 0.2 um, the state of the current cell is changed to that of the neighbor cell;

[0063] Step (3) is repeated until all cells in the selected area are assigned a grain number; the cell state variable is assigned an initial value; the dislocation density variable initial value is p0=10 12 / m 2 , the recrystallization number variable initial value is 0, and the subgrain number variable initial value is 0.

[0064] Step two, read the loading conditions from the finite element simulation results of the cutting process; Fig. 4(a) is a schematic diagram of the strain of a titanium alloy cutting process finite element simulation example result of a microstructure simulation method for a cutting process provided by the embodiment of the application, Fig. 4(b) is a schematic diagram of the strain rate of a titanium alloy cutting process finite element simulation example result of a microstructure simulation method for a cutting process provided by the embodiment of the application, and Fig. 4(c) is a schematic diagram of the temperature of a titanium alloy cutting process finite element simulation example result of a microstructure simulation method for a cutting process provided by the embodiment of the application, as shown in Figure 4(a) , 4(b) and 4(c), the advantage software is used for titanium alloy cutting finite element simulation, and the strain e=2.2, the maximum temperature T=853 K and the maximum strain rate of the center position of the simulation area are determined from the simulation results, the time step At=4.115x10 -8 s, and the total simulation time t total =4.527x10 -5 s;

[0065] Step three, non-continuous dynamic recrystallization nucleation simulation; calculate the non-continuous dynamic recrystallization critical dislocation density p dc ; can be obtained by solving the following formula:

[0066]

[0067] Wherein, g m = 0.75 J / m 2 Is the energy of high angle grain boundary, t = 8.38 x 10 -10 J / m is the linear dislocation energy, k1, k2 is the dislocation density evolution coefficient, the calculation formula is:

[0068]

[0069]

[0070] Wherein, c1 = 8.28 x 10 8 , c2 = 15.64, m1 = 0.0122, m2 = -0.0071 are material constants, R = 8.314 J / K / mol is the gas constant, Q act = 153 kJ / mol is the activation energy. M is the grain boundary mobility, the calculation formula is:

[0071]

[0072] Wherein, d is the grain boundary thickness, D ob Is the grain boundary self-diffusion coefficient, and dD ob = 5 x 10 -15 , b = 2.86 x 10 -10 M is the Burgers vector size, Q b = 108 kJ / mol is the self-diffusion activation energy, K = 13.8 x 10 -23 J / K is the Boltzmann constant.

[0073] Scan the whole cell space, if the dislocation density p of the cell exceeds the non-continuous dynamic recrystallization critical dislocation density p dc And the cell is at the grain boundary position, then the current cell has P d The probability of transforming into non-continuous dynamic recrystallization nucleus; the calculation formula is as follows:

[0074]

[0075] Wherein, C d = 4 x 10 13 Is a material constant, S CA = 0.04 m 2 Is the cell area.

[0076] If the current nucleus is transformed into a non-continuous dynamic recrystallization nucleus, update its state variables, set the dislocation density variable to p0, set the grain orientation variable to a random value, set the recrystallization number variable to the current recrystallization number + 1, and obtain the current cell maximum grain number N g ; otherwise, the cell state variable remains unchanged. g ; otherwise, the cell state variable remains unchanged.

[0077] Step four, continuous dynamic recrystallization simulation; including the following sub-steps:

[0078] Scan the entire cell space, if the average dislocation density of the grain / sub-grain exceeds the sub-grain formation critical dislocation density p cc , then the current grain / sub-grain has a P c probability of splitting to generate new sub-grains; the calculation formula is as follows:

[0079]

[0080] Wherein, a1=8.46x10 -3 , b1=-0.04, g1=-0.0077 are material constants; theta0=1° is the critical angle of sub-grain, r=(NS CA / π) 0.5 is the current grain / sub-grain radius, N is the number of cells constituting the current grain / sub-grain.

[0081] Since the stable grain boundary angle of two-dimensional grain is 120°, therefore in this simulation, the grain / sub-grain will split into three to form three smaller sub-grains, if the current grain / sub-grain splits to generate new sub-grains, update its state variables, obtain the current cell maximum sub-grain number N s , the sub-grain numbers of the newly generated sub-grains in the cells are set to N s +1, N s +2, N s +3, calculate the dislocation density increment Delta p 1- due to the generation of sub-grains, the calculation formula is as follows:

[0082]

[0083] Wherein, omega1=1.38x10 3 is a material constant.

[0084] Scan the entire cell space, calculate the rotation angle Delta theta of all sub-grains, update its orientation angle theta, the calculation formula is as follows:

[0085]

[0086] Where α² = 9.368, β² = -0.0194, and γ² = 5.38 × 10⁻⁶. -4 ξ1 = 1.437 and ξ2 = 1.1031 are material constants; r0 = 20 μm is the reference radius, E θ The grain boundary energy with orientation angle θ is calculated using the following formula:

[0087]

[0088] Where, θ c =15° is the critical grain boundary angle. Calculate the dislocation density increment Δρ due to subgrain rotation. 2- The calculation formula is as follows:

[0089]

[0090] If the subgrain orientation angle exceeds the critical grain boundary angle θ c Then update its cell state, set the grain orientation variable to a random value, and set the recrystallization count variable to the current recrystallization count + 1, thus obtaining the maximum grain number of the current cell as N. g The grain number variable is set to N. g +1;

[0091] Step 5: Update dislocation density; Calculate the dislocation density increment Δρ for each cell in the current increment step, and update its dislocation density ρ. The calculation formula is as follows:

[0092]

[0093] Step Six: Simulation of Dynamic Recrystallization Grain Growth; Scan the entire cell space and calculate the grain boundary migration driving force F and migration distance L of the recrystallized grains. The calculation formulas are as follows:

[0094] F = 4πr 2 τ(ρ m -ρ d )-8πrγ m

[0095]

[0096] Where, ρ d ρ is the dislocation density of the recrystallized grain. m The dislocation density is the matrix. If the migration distance is greater than the distance between two adjacent cells, the current cell state is transformed into the neighboring cell state with a recrystallization count greater than or equal to 1. Determine if the total simulation time has been reached. If not, repeat steps three through six; otherwise, stop the simulation.

[0097] Figure 5A schematic diagram of microstructure evolution simulation result of a microstructure simulation method for cutting process provided by the embodiment of the present application is shown in Figure 5 As shown, the visualization of microstructure evolution process of the specified region of the cutting process is realized; by using the above method, the surface region of the titanium alloy cutting process under different cutting speeds is simulated, Figure 6 A comparison diagram between the average grain size prediction value and the measured value of a microstructure simulation method for cutting process provided by the embodiment of the present application is shown in Figure 6 As shown, the comparison of the microstructure prediction result and the experimental result shows that the microstructure evolution behavior of the titanium alloy cutting process can be simulated more accurately by the present application.

[0098] It is further known that the above-mentioned embodiments of the present application can achieve the following beneficial effects:

[0099] (1) The two mechanisms of discontinuous dynamic recrystallization and continuous dynamic recrystallization are considered, and the microstructure evolution mechanism of the cutting process can be understood more deeply by visualizing the microstructure evolution of the cutting process;

[0100] (2) A dynamic recrystallization simulation method based on physical mechanism is adopted, and the microstructure evolution behavior of the cutting process can be simulated more accurately.

[0101] According to another aspect of the embodiment of the present application, a microstructure simulation device is further provided, Figure 7 A schematic diagram of a microstructure simulation device provided by the embodiment of the present application is shown in Figure 7 As shown, the microstructure simulation device comprises a generation module 71, a reading module 72, a first simulation module 73, a second simulation module 74, an update module 75, a third simulation module 76 and a judgment module 77. The microstructure simulation device will be described in detail below.

[0102] The generation module 71 is used for generating an initial microstructure; the reading module 72 is connected to the generation module 71 and is used for reading loading conditions from the finite element simulation result of the cutting process; the first simulation module 73 is connected to the reading module 72 and is used for discontinuous dynamic recrystallization nucleation simulation; the second simulation module 74 is connected to the first simulation module 73 and is used for continuous dynamic recrystallization simulation; the update module 75 is connected to the second simulation module 74 and is used for updating dislocation density; the third simulation module 76 is connected to the update module 75 and is used for dynamic recrystallization grain growth simulation; the judgment module 77 is connected to the third simulation module 76 and is used for judging whether the simulation actual time consumption reaches the simulation total time; if the simulation actual time consumption does not reach the simulation total time, the implementation step contents corresponding to the first simulation module 73 to the third simulation module 76 are repeatedly executed; if the simulation actual time consumption reaches the simulation total time, the simulation is stopped.

[0103] It should be noted that the above modules can be implemented by software or hardware, for example, for the latter, the above modules can be located in the same processor, and / or the above modules are located in different processors in any combination.

[0104] In the embodiment of the present application, the generating module in the microstructure simulation device is configured to generate an initial microstructure; the reading module is configured to read loading conditions from finite element simulation results of a cutting process; the first simulation module is configured to simulate non-continuous dynamic recrystallization nucleation; the second simulation module is configured to simulate continuous dynamic recrystallization; the updating module is configured to update dislocation density; the third simulation module is configured to simulate dynamic recrystallization grain growth; and the judging module is configured to judge whether a simulation actual time consumption reaches a simulation total time, if the simulation actual time consumption does not reach the simulation total time, the implementation steps corresponding to the first simulation module to the third simulation module are repeatedly executed; and if the simulation actual time consumption reaches the simulation total time, the simulation is stopped. That is, the embodiment of the present application comprehensively considers non-continuous dynamic recrystallization and continuous dynamic recrystallization, establishes a cellular automaton model considering the two dynamic recrystallization mechanisms, and realizes microstructure simulation for a cutting process in combination with finite element simulation, thereby solving the technical problem that a microstructure simulation method for a cutting process in the related art ignores the continuous dynamic recrystallization mechanism, and achieving the technical effect that the microstructure evolution behavior of the cutting process can be more accurately simulated.

[0105] It should be noted that the generating module 71, the reading module 72, the first simulation module 73, the second simulation module 74, the updating module 75, the third simulation module 76 and the judging module 77 correspond to steps 1 to 7 in the method embodiment, and the above modules have the same examples and application scenarios as the corresponding steps, but are not limited to the disclosure of the above method embodiment.

[0106] According to another aspect of the embodiment of the present application, an electronic device is also provided, which includes a processor, and a memory for storing processor-executable instructions, wherein the processor is configured to execute the microstructure simulation method in any one of the above.

[0107] According to another aspect of the embodiment of the present application, a storage medium is also provided, which includes a stored program, wherein the program controls a device where the storage medium is located to execute the microstructure simulation method in any one of the above when the program is running.

[0108] It should be noted that the storage medium described above includes, but is not limited to, a computer readable storage medium. In the embodiments of the present application, the computer readable storage medium described above can be located in any one of the computer terminals in the computer terminal group in the computer network, and / or in any one of the mobile terminals in the mobile terminal group, and the computer readable storage medium includes a stored program.

[0109] The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0110] In the above-mentioned embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0111] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0112] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed to multiple units. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment scheme.

[0113] In addition, each functional unit in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The above integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0114] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0115] The above is only the preferred embodiment of the present application, it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A microstructure simulation method characterized by, The method comprises the following steps: Step 1, generating an initial microstructure; The method comprises the following specific implementation steps: Step 1.1, determining a simulation region, discretizing the simulation region into a grid consisting of cells, and calculating a number of grains of the simulation region from an average grain size of the target base material ; Step 1.2, randomly selecting a cell as an initial crystal nucleus in the simulation region, and assigning different grain number variables and grain orientation variables to the selected cell, setting the grain boundary migration distance variable of the current cell as one cell length Step 1.2, randomly selecting a cell as an initial crystal nucleus in the simulation region, and assigning different grain number variables and grain orientation variables to the selected cell, setting the grain boundary migration distance variable of the current cell as one cell length​ Step 1.3, for each cell, if the current cell has not been assigned a grain number and the grain boundary migration distance is greater than or equal to the distance between adjacent two cells, the state of the current cell is changed to the neighbor cell state; Step 1.4, repeating the step 1.3 until all cells in the simulation region are assigned the grain number and the cell state variable is assigned an initial value, wherein the initial value of the cell state variable at least includes an initial value of a dislocation density variable, an initial value of a recrystallization frequency variable and an initial value of a subgrain number variable; Step 2, reading loading conditions from a finite element simulation result of a cutting process; Step 3, non-continuous dynamic recrystallization nucleation simulation; Step 4, continuous dynamic recrystallization simulation; The method comprises the following specific implementation steps: Step 4.1, scanning the entire cell space, if the average dislocation density of a grain / subgrain exceeds a subgrain formation critical dislocation density, the current grain / subgrain has a second predetermined probability to split to generate a new subgrain; Step 4.2, if the current grain / sub-grain is split to generate a new sub-grain, update its state variables, get the current cell maximum grain number as , the sub-grain number of the cell in the newly generated sub-grain is set as , , , and calculate the first dislocation density increment due to the generation of the sub-grain; Step 4.3, scan the whole cell space, calculate the rotation angle of all subgrains, update the subgrain orientation angle, if the subgrain orientation angle exceeds the critical grain boundary angle, update the cell state, set the grain orientation variable to a random value, set the recrystallization number variable to the current recrystallization number + 1, and obtain the current cell maximum grain number as , the grain number variable is set to , and the second dislocation density increment caused by the rotation of the subgrain is calculated; Step 5, updating the dislocation density; Step 6, dynamic recrystallization grain growth simulation; Step 7, judging whether the simulation actual time consumption reaches the total simulation time, if the simulation actual time consumption does not reach the total simulation time, repeating the steps 3 to 6; if the simulation actual time consumption reaches the total simulation time, stopping the simulation.

2. The method of claim 1, wherein, The step 2 comprises the following specific implementation steps: Extracting strain, maximum temperature and maximum strain rate of a simulation region center position from the finite element simulation result of the cutting process, and determining a time step and a total simulation time.

3. The method of claim 1, wherein, The step 3 comprises the following specific implementation steps: Scanning the entire cell space, if the dislocation density of a cell exceeds a non-continuous dynamic recrystallization critical dislocation density and the cell is at a grain boundary position, the current cell has a first predetermined probability to be converted into a non-continuous dynamic recrystallization nucleus; If the current nucleus is transformed into a non-continuous dynamic recrystallization nucleus, update its state variables, set the dislocation density variable, set the grain orientation variable to a random value, set the recrystallization number variable to the current recrystallization number + 1, and obtain the current cell maximum grain number as , and set the grain number variable to .

4. The method of claim 1, wherein, The step 5 comprises the following specific implementation steps: Calculating a dislocation density increment of each cell in a current increment step, and updating the dislocation density.

5. The method of claim 1, wherein, The step 6 comprises the following specific implementation steps: Scanning the entire cell space, calculating a grain boundary migration driving force and a migration distance of a recrystallization grain; If the migration distance is greater than the distance between adjacent two cells, the state of the current cell is changed to the neighbor cell state with a recrystallization frequency greater than or equal to 1.

6. A microstructure simulation device characterized by comprising: The method comprises the following steps: A generating module is configured to generate an initial microstructure; the method comprises the following steps: determining a simulation region, discretizing the simulation region into a grid of cells, and calculating a number of grains for the simulation region based on an average grain size of a target base material ; Randomly selected within the simulation area Each cell is used as the initial nucleus, and the selected... Each cell is assigned a different grain number variable and grain orientation variable, and the grain boundary migration distance variable of the current cell is set to the side length of 1 cell. For each cell, if the current cell has not been assigned a grain number and the grain boundary migration distance is greater than or equal to the distance between adjacent two cells, the state of the current cell is changed to the neighbor cell state; until all cells in the simulation region are assigned the grain number and the cell state variable is assigned an initial value, wherein the initial value of the cell state variable at least includes an initial value of a dislocation density variable, an initial value of a recrystallization frequency variable and an initial value of a subgrain number variable; A reading module is configured to read loading conditions from a finite element simulation result of a cutting process; A first simulation module is configured to perform non-continuous dynamic recrystallization nucleation simulation. A second simulation module for continuous dynamic recrystallization simulation; comprising: Scanning the whole cell space, if the average dislocation density of the grain / sub-grain exceeds the critical dislocation density for sub-grain formation, the current grain / sub-grain has a second predetermined probability to split to generate a new sub-grain; If the current grain / sub-grain is split to generate a new sub-grain, update the state variables of the current grain / sub-grain to obtain the maximum grain number of the current cell as , the sub-grain numbers of the cells in the newly generated sub-grain are respectively set as , , , and the first dislocation density increment caused by the generation of the sub-grain is calculated; Scanning the entire cell space, the rotation angle of all subgrains is calculated, the subgrain orientation angle is updated, if the subgrain orientation angle exceeds the critical grain boundary angle, the cell state is updated, the grain orientation variable is set to a random value, the recrystallization frequency variable is set to the current recrystallization frequency + 1, and the current cell maximum grain number is obtained , the grain number variable is set to , and the second dislocation density increment caused by the rotation of the subgrain is calculated; An updating module for updating the dislocation density; A third simulation module for dynamic recrystallization grain growth simulation; A judging module for judging whether the simulation actual time consumption reaches the simulation total time, if the simulation actual time consumption does not reach the simulation total time, the corresponding implementation steps of the first simulation module to the third simulation module are repeatedly executed; if the simulation actual time consumption reaches the simulation total time, the simulation is stopped.

7. An electronic device, comprising: Comprise: A processor; A memory for storing processor-executable instructions; Wherein, the processor is configured to execute the microstructure simulation method in any one of claims 1 to 5.

8. A storage medium, characterized by The storage medium comprises a stored program, wherein the device where the storage medium is located executes the microstructure simulation method in any one of claims 1 to 5 when the program runs.

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