Dynamic recrystallization multi-scale simulation method and system coupled with crystal plasticity

Abstract

The invention provides a dynamic recrystallization deformation structure and performance multi-scale simulation method and system coupled with crystal plasticity, and the method comprises the steps: simulating a metal plastic processing process through macroscopic finite element calculation, updating the state through a macroscopic material constitutive model in the calculation process, recording the historical information related to deformation of each unit, and calculating the deformation of each unit; a microstructure plastic recrystallization model is adopted, microstructure calculation is carried out in combination with deformation historical information, tissues, textures and stress at specified intervals are output, geometric information of a macroscopic finite element is extracted, geometry is reconstructed according to finite element deformation coordinate information, and according to the corresponding tissue, texture and stress information of unit and strain state indexes, the microstructure, texture and stress information of the unit and strain state indexes is calculated. And realizing prediction display of tissue and texture distribution in an overall corresponding deformation state. According to the method, under the metal non-uniform hot working plastic deformation state, the multi-scale simulation method for the structures, textures and mechanical properties of different areas is predicted, and the method has great significance in guiding metal plastic working process design and structure property regulation and control.

Description

Technical Field

[0001] The present invention relates to the technical field of metal plastic processing and the prediction of its non-uniform microstructure and mechanical characteristics. Specifically, it relates to a multi-scale simulation method and system for dynamic recrystallization deformation microstructure and properties coupling crystal plasticity. Background Art

[0002] In modern manufacturing, metal plastic processing has become one of the core methods of metal processing due to its significant advantages such as high efficiency and near-net shaping. The mechanical properties of metals after plastic processing are closely related to the microscopic tissue characteristics formed during the processing. Given the complexity of the shapes of metal parts, different regions will experience different deformation conditions during processing. Especially when deformed under heating conditions, the phenomenon of dynamic recrystallization is very likely to occur, which will not only promote tissue refinement but also cause stress softening, ultimately resulting in non-uniform microscopic tissue and mechanical property distributions in different regions of metal parts.

[0003] At present, it is extremely difficult to accurately predict the tissue and mechanical property distributions of metal parts after hot deformation. This problem has severely restricted the precise design of the hot processing technology of metal parts and the effective control of their properties.

[0004] Based on the mesoscopic calculation of crystal plasticity, the characteristics of metal microscopic tissue and texture can be accurately calculated, and the grain refinement and stress softening phenomena caused by dynamic recrystallization can also be considered. Therefore, the multi-scale calculation combining mesoscopic crystal plasticity with macroscopic simulation has become the key to realizing the non-uniform deformation simulation and shape-property control during the plastic processing of metals under heating conditions.

[0005] Through the retrieval of patent documents, it is found that the invention patent with the publication number CN110210103B discloses a multi-scale simulation method for the mechanical behavior of multiphase composites. It obtains various physical property parameters of the material through calculations at different scales, calculates the parameters required for macroscopic simulation through microscopic and mesoscopic scales, and predicts the stress-strain relationship, stress distribution, plastic deformation and other behaviors of multiphase composites. The multi-scale implementation method and prediction target of this invention are different from those of this method. The invention patent with the publication number CN116978496A discloses a visualization prediction method for the evolution of the microstructure of continuous dynamic recrystallization of aluminum alloys. This method realizes the prediction and visualization of the mesoscopic-scale microstructure during the ring rolling deformation process of aluminum alloys through physical evolution mechanisms, only focuses on the mesoscopic scale, and does not involve the non-uniform multi-scale simulation in the overall deformation of metals. The invention patent with the publication number CN111079309A discloses a method for establishing a multi-pass compression flow stress model coupled with recrystallization kinetics. By combining a phenomenological recrystallization model, it realizes the prediction of flow stress and microstructure during multi-pass deformation of high-strength steel. The phenomenological recrystallization model adopted by this method is different from the crystal plasticity recrystallization mesoscopic simulation method in this method. At the same time, the above method still belongs to macroscopic simulation, only updates the recrystallized volume fraction and so on by using the phenomenological recrystallization model, and the implementation method is different from that of this invention. The invention patent with the publication number CN114169189A discloses a texture prediction method during hot plastic large deformation of near-α titanium alloy. This method analyzes the plastic deformation mechanism, macroscopic mechanical behavior and texture evolution law during the deformation process by establishing an ABAQUS-VPSC-MTS multi-scale model. This multi-scale model belongs to an online calculation method, and the stress-strain data is transferred and converted between the finite element software ABAQUS and the viscoplastic self-consistent model VPSC, which has the problem of low calculation efficiency, is different from the offline calculation strategy in this method, and the above method cannot consider the stress softening and tissue texture evolution caused by dynamic recrystallization.

[0006] In summary, in the process of hot deformation of metals, there is still a lack of an effective integrated calculation method for predicting the mechanical properties and non-uniform evolution of tissue texture considering dynamic recrystallization. Therefore, it has become a key task to be solved urgently to study a multi-scale simulation method and system for the deformation tissue and properties of dynamic recrystallization coupled with crystal plasticity. Summary of the Invention

[0007] Aiming at the defects in the prior art, the purpose of the present invention is to provide a multi-scale simulation method and system for the deformation tissue and properties of dynamic recrystallization coupled with crystal plasticity.

[0008] According to a multi-scale simulation method for the deformation tissue and properties of dynamic recrystallization coupled with crystal plasticity provided by the present invention, it includes the following steps:

[0009] Step S1, calculate and simulate the metal plastic processing process through a macroscopic finite element model;

[0010] Step S2, export the position information and deformation gradient history information of each element integration point in the macroscopic finite element model, and output them to a file with the deformation simulation time and element number as the index;

[0011] Step S3, obtain the initial microstructure and initial mechanical properties of the metal material through experimental tests;

[0012] Step S4, based on the initial microstructure and initial mechanical properties, use a mesoscopic crystal plasticity dynamic recrystallization model to calibrate the material parameters and obtain the calibrated model parameters;

[0013] Step S5, after preprocessing the deformation gradient history information exported in Step S2, input it into the mesoscopic crystal plasticity dynamic recrystallization model with calibrated parameters, and based on the initial microstructure, carry out the prediction of the evolution of microstructure, texture and mechanical properties, and output the stress value, microstructure and texture at the specified time;

[0014] Step S6, according to the position information exported in Step S2, map the stress value, microstructure and texture to the deformed reconstructed geometry, and visualize the microstructure and mechanical property distribution according to the index of the deformation simulation time and element number.

[0015] Preferably, in Step S1, a temperature-dependent macroscopic material constitutive model is used to establish a thermo-mechanical coupled macroscopic finite element model, and the deformation loading conditions and loading speed of the macroscopic finite element model are consistent with the actual hot deformation process.

[0016] Preferably, Step S1 is implemented through commercial finite element simulation software, including the following sub-steps:

[0017] Step S1.1, construct a three-dimensional physical model of the hot compression part;

[0018] Step S1.2, input the temperature-dependent macroscopic constitutive model;

[0019] Step S1.3, set the deformation loading conditions and loading speed consistent with the actual hot compression process;

[0020] Step S1.4, carry out mesh division and determine the boundary conditions;

[0021] Step S1.5, carry out simulation calculations to obtain the strain rate, strain and temperature range during the metal plastic hot compression process.

[0022] Preferably, in step S2, in the form of batch post - processing or writing a user sub - program, the position information of the element integration points and the deformation gradient history information in the macroscopic finite - element model are derived to a file according to the set time requirements, and comprehensively using the deformation simulation time and the element number as indexes.

[0023] Preferably, in step S3, the initial microstructure includes the microscopic grain orientations, sizes, and morphologies of no less than 100 grains obtained by EBSD; the initial mechanical properties include the experimental data of unidirectional tension and unidirectional compression in a specific direction, and the deformation amount, deformation rate, and deformation temperature tested in the experiment cover the strain, strain rate, and temperature ranges output in step S1.

[0024] Preferably, step S4 includes the following sub - steps:

[0025] Step S4.1, based on the deformation mechanism of metal grain slip and dynamic recrystallization, construct a crystal plasticity model, with the input being the initial microstructure of the grains measured in step S3, and the number of grains used ≥ 100;

[0026] Step S4.2, adjust the parameters of the crystal plasticity model so that the deviation between the predicted stress - strain curve and the experimental data is ≤ 10%, and the fitting deviation of the evolution of grain size and recrystallized volume fraction is ≤ 15%;

[0027] Step S4.3, determine the hardening parameters and recrystallization parameters.

[0028] Preferably, step S4.2 includes: by adjusting methods such as manual or automatic optimization, make the overall shape and numerical matching degree between the stress - strain curve predicted by the crystal plasticity model for the corresponding deformation mode and the experimentally measured stress - strain curve, where the numerical deviation is ≤ 10%, and at the same time fit the evolution of grain size and recrystallized volume fraction, where the numerical deviation is ≤ 15%.

[0029] Preferably, step S5 includes the following sub - steps:

[0030] Step S5.1, convert the deformation gradient history file extracted in step S2 into the input format of the mesoscopic crystal plasticity dynamic recrystallization model, and input the initial microstructure;

[0031] Step S5.2, conduct mesoscopic crystal plasticity dynamic recrystallization calculations for the integration points or characteristic cross - sectional area integration points in the macroscopic finite - element model;

[0032] Step S5.3, output the stress value, grain size, and dynamic recrystallized volume fraction at a specific moment.

[0033] Preferably, step S6 includes the following sub - steps:

[0034] Step S6.1: Reconstruct the deformed geometry based on the spatial positions of all integration points or characteristic cross-sectional integration points in the macroscopic finite element model, and obtain the results of mesoscopic crystal plasticity recrystallization calculation by using the integration point numbers and deformation times as indexes.

[0035] Step S6.2: Display the stress values, grain sizes, and dynamic recrystallization volume fractions on the deformed and reconstructed geometry in the form of contour maps, and export the numerical information.

[0036] The present invention also provides a multi-scale simulation system for the deformed microstructure and properties coupling crystal plasticity dynamic recrystallization, including:

[0037] Module M1: Calculate and simulate the metal plastic processing process through the macroscopic finite element model.

[0038] Module M2: Export the position information and deformation gradient history information of each element integration point in the macroscopic finite element model, and output them to a file with the deformation simulation time and element number as indexes.

[0039] Module M3: Obtain the initial microstructure and initial mechanical properties of the metal material through experimental tests.

[0040] Module M4: Based on the initial microstructure and initial mechanical properties, use the mesoscopic crystal plasticity dynamic recrystallization model to carry out the calibration of material parameters and obtain the calibrated model parameters.

[0041] Module M5: After preprocessing the deformation gradient history information exported in Step S2, input it into the mesoscopic crystal plasticity dynamic recrystallization model with calibrated parameters, and based on the initial microstructure, carry out the prediction of the evolution of microstructure, texture, and mechanical properties, and output the stress values, microstructure, and texture at the specified time.

[0042] Module M6: Map the stress values, microstructure, and texture to the deformed and reconstructed geometry according to the position information exported in Step S2, and visualize the distribution of the microstructure and mechanical properties according to the indexes of the deformation simulation time and element number.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention establishes a multi-scale simulation method for the deformed microstructure and properties coupling crystal plasticity dynamic recrystallization. This method conducts macroscopic finite element forming calculations, extracts and preprocesses the deformation information of element integration points, calibrates the mesoscopic crystal plasticity dynamic recrystallization model, conducts offline crystal plasticity calculations and predictions, and finally realizes the visual display of microstructure, texture, and stress in non-uniform deformation. This multi-scale simulation method can provide an effective prediction method for accurately designing hot processing processes and realizing microstructure and property control.

[0045] 2. The multi-scale simulation method for the deformed microstructure and properties of coupled crystal plasticity and dynamic recrystallization of the present invention is based on the mesoscopic crystal plasticity recrystallization model in the material deformation physical model, and can accurately predict mechanical properties, texture and microstructure evolution.

[0046] 3. The multi-scale simulation method for the deformed microstructure and properties of coupled crystal plasticity and dynamic recrystallization of the present invention adopts the method of combining macroscopic thermo-mechanical coupling finite element calculation with off-line mesoscopic crystal plasticity recrystallization simulation, realizing the combination of macroscopic deformation and mesoscopic calculation. This method can consider the influence of different deformation histories, reduce the difficulty of multi-scale coupling, and improve the calculation efficiency.

[0047] 4. The multi-scale simulation method for the deformed microstructure and properties of coupled crystal plasticity and dynamic recrystallization of the present invention can realize the visualization of stress, microstructure and texture under non-uniform conditions of the entire part or characteristic section based on integral point off-line calculation, deformation geometry reconstruction and result index mapping. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Other features, objects and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0049] Figure 1 is a flowchart of a multi-scale simulation method for the deformed microstructure and properties of coupled crystal plasticity and dynamic recrystallization in an embodiment of the present invention;

[0050] Figure 2 is a schematic diagram of the geometric structure of a hot compression part in an embodiment of the present invention;

[0051] Figure 3 is the distribution of equivalent stress within the cross-section in an embodiment of the present invention;

[0052] Figure 4 is the distribution of grain size within the cross-section in an embodiment of the present invention;

[0053] Figure 5 is the distribution of dynamic recrystallization volume fraction within the cross-section in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0055] The present invention provides a multi-scale simulation method and system for the dynamic recrystallization deformation structure and properties coupling crystal plasticity. The method includes simulating the metal plastic processing process through macroscopic finite element calculation, updating the state using a macroscopic material constitutive model during the calculation, and recording the historical information related to deformation for each element simultaneously. A mesoscopic crystal plasticity recrystallization model is used to carry out mesoscopic calculations in combination with the deformation historical information, outputting the structure, texture, and stress at specified intervals, extracting the geometric information of the macroscopic finite element, reconstructing the geometry according to the finite element deformation coordinate information, and indexing the corresponding structure, texture, and stress information according to the element and strain state, so as to realize the prediction and display of the structure and texture distribution under the overall corresponding deformation state. The method of the present invention can predict the multi-scale simulation methods of the structure, texture, and mechanical properties of different regions under the non-uniform hot working plastic deformation state of metals, which has important significance for guiding the design of metal plastic processing technology and the regulation of structure and properties.

[0056] Example 1:

[0057] In this example, taking the hot compression of face-centered cubic metal as an example, the prediction of the structure and properties under non-uniform deformation conditions of the multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupling crystal plasticity is carried out.

[0058] Figure 1 It is a flowchart of a multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupling crystal plasticity in an embodiment of the present invention.

[0059] As Figure 1 shown, a multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupling crystal plasticity provided in this embodiment includes the following steps:

[0060] Step S1, simulating the metal plastic processing process through a macroscopic finite element model.

[0061] Specifically, a temperature-related macroscopic material constitutive model is used to establish a thermo-mechanical coupled macroscopic finite element model, and the deformation loading conditions and loading speed of the macroscopic finite element model are consistent with the actual hot deformation process.

[0062] In this embodiment, step S1 is implemented through commercial finite element simulation software and includes the following sub-steps:

[0063] Step S1.1, constructing a three-dimensional physical model of the hot compression part, Figure 2 It is a schematic diagram of the geometric structure of the hot compression part in this embodiment.

[0064] Step S1.2, inputting the temperature-related macroscopic constitutive model;

[0065] Step S1.3, setting the deformation loading conditions and loading speed consistent with the actual hot compression process;

[0066] Step S1.4: Conduct mesh generation and determine boundary conditions;

[0067] Step S1.5: Conduct simulation calculations to obtain the strain rate, strain, and temperature range during the metal plastic hot compression process.

[0068] Step S2: Export the position information and deformation gradient history information of each element integration point in the macroscopic finite element model, and output them to a file using the deformation simulation time and element number as the index.

[0069] Specifically, in a batch post-processing manner or by writing a user subroutine, export the position information and deformation gradient history information of the element integration points in the macroscopic finite element model to a file according to the set time requirements and using the deformation simulation time and element number as the index.

[0070] In this embodiment, a point tracking method is used to automatically batch post-process the element integration points in the macroscopic finite element calculation, export the position information and deformation-related velocity gradient history information of the uniformly distributed points on the characteristic cross-section of the hot-compressed part, and write them to a file;

[0071] Step S3: Through experimental tests, obtain the initial microstructure of the metal material and the initial mechanical properties under simple loading conditions.

[0072] Specifically, in Step S3, for the metal material before initial deformation, the initial microstructure includes the microscopic grain orientation, size, and morphology of no less than 100 grains obtained by EBSD (Electron Backscatter Diffraction); the initial mechanical properties include the experimental data of unidirectional tension and unidirectional compression in a specific direction, and the deformation amount, deformation speed, and deformation temperature of the experimental tests cover the strain, strain rate, and temperature range output in Step S1.

[0073] In this embodiment, measure the microstructure of the initial state of the hot-compressed part, conduct hot-compression experiments at reasonable intervals according to the strain rate, strain, and temperature range during the hot-compression process determined in Step S1, and obtain the microscopic grain orientation, size, and morphology of the grains on the characteristic cross-section of the hot-compressed part through methods such as EBSD, and select 100 of them as the input texture conditions for Step S4.

[0074] Step S4: Based on the initial microstructure and initial mechanical properties, use the mesoscopic crystal plasticity dynamic recrystallization model to conduct calibration of material parameters to obtain the calibrated model parameters.

[0075] Specifically, Step S4 includes the following sub-steps:

[0076] Step S4.1, calibration of the crystal plasticity model and related material model parameters: Based on the deformation mechanisms of metal grain slip and dynamic recrystallization, a crystal plasticity model is constructed. The input is the initial microstructure of the grains measured in Step S3, and the number of grains used is ≥ 100.

[0077] Step S4.2, adjust the parameters of the crystal plasticity model so that the deviation between the predicted stress-strain curve and the experimental data is ≤ 10%, and the fitting deviation of the evolution of grain size and recrystallized volume fraction is ≤ 15%.

[0078] In this embodiment: By means of manual adjustment or automatic optimization, etc., the stress-strain curve predicted by the crystal plasticity model under the corresponding deformation mode is matched with the experimentally measured stress-strain curve in terms of overall shape and numerical value, where the numerical deviation is ≤ 10%. At the same time, the evolution of grain size and recrystallized volume fraction is fitted, where the numerical deviation is ≤ 15%.

[0079] Step S4.3, determine the hardening parameters and recrystallization parameters.

[0080] In this embodiment, based on the initial microscopic grain orientation distribution, grain size characteristics, stress-strain data of the hot compression experiment, microscopic grain orientation, and grain size obtained in Step S3, the initial microscopic grain orientation and grain size are used as the input parameters of the mesoscopic-scale crystal plasticity recrystallization model to carry out multi-scale numerical simulation of hot compression deformation; Subsequently, by means of manual calibration, the stress-strain curve predicted by the crystal plasticity model under the corresponding deformation mode is double-matched with the experimental test results in terms of overall morphology and numerical accuracy, where the numerical deviation is ≤ 10%. At the same time, the evolution of grain size and recrystallized volume fraction is fitted, where the numerical deviation is ≤ 15%, to obtain the hardening parameters and recrystallization parameters of the mesoscopic crystal plasticity recrystallization model.

[0081] Step S5, after preprocessing the deformation gradient history information exported in Step S2, input it into the calibrated mesoscopic crystal plasticity dynamic recrystallization model, and based on the initial microstructure, carry out the prediction of the evolution of microstructure, texture, and mechanical properties, and output the stress value, microstructure, and texture at the specified moment.

[0082] Specifically, Step S5 includes the following sub-steps:

[0083] Step S5.1, convert the deformation gradient history file extracted in Step S2 into the input format of the mesoscopic crystal plasticity dynamic recrystallization model, and input the initial microstructure.

[0084] Step S5.2, for the integration points or characteristic cross-sectional area integration points in the macroscopic finite element model, carry out the mesoscopic crystal plasticity dynamic recrystallization calculation under all corresponding deformation conditions.

[0085] Step S5.3: Output the stress value, grain size, and dynamic recrystallization volume fraction at a specific moment according to requirements.

[0086] In this embodiment, the velocity gradient history condition file extracted in step S2 is pre - processed for velocity gradient history file conversion according to the input requirements of the mesoscopic crystal plasticity dynamic recrystallization model. The input microstructure of the mesoscopic crystal plasticity dynamic recrystallization model is the initial microscopic grain orientation and size obtained in step S3, and the deformation mode, hardening parameters, recrystallization parameters in the model are the same as those in step S4. For the points on the characteristic cross - section in the macroscopic finite - element simulation, carry out the mesoscopic crystal plasticity dynamic recrystallization calculation under all corresponding deformation conditions, and output the information of the equivalent stress value, grain size, and dynamic recrystallization volume fraction when the true strain at the final moment of hot compression is 0.6.

[0087] Step S6: According to the position information exported in step S2, map the stress value, microstructure, and texture to the deformed reconstructed geometry, and index the mesoscopic crystal plasticity predicted microstructure, texture, and mechanical properties according to the deformation simulation moment and element number, and visualize the distribution of the microstructure and mechanical properties.

[0088] Specifically, step S6 shows the deformed reconstructed geometry based on different times in spatial distribution, and indexes the microscopic features and stress results output in step S5 according to the deformation moment and integration point number. It specifically includes the following sub - steps:

[0089] Step S6.1: Reconstruct the deformed geometry according to the spatial positions of all integration points or characteristic cross - section integration points in the macroscopic finite - element model, and obtain the results of the mesoscopic crystal plasticity recrystallization calculation by indexing according to the integration point number and deformation moment.

[0090] Step S6.2: Display the stress value, grain size, and dynamic recrystallization volume fraction on the deformed reconstructed geometry in the form of a contour map, and export the numerical information.

[0091] In this embodiment, the deformed geometry is reconstructed according to the spatial positions of the points on the characteristic cross - section in the macroscopic finite - element model, and the results of the mesoscopic crystal plasticity recrystallization calculation are obtained by indexing according to the numbers of the traced selected points and the deformation moment. The calculation results are visualized in the form of a contour map according to the geometric coordinates of the nodes. The stress value, microstructure, and texture information are displayed on the deformed reconstructed geometry, and the corresponding numerical information can be exported. The distribution contour maps of the equivalent stress, grain size, and dynamic recrystallization volume fraction in the cross - section are drawn, and interpolation smoothing is carried out according to the color and geometric coordinates of each node. The attached figure shows the simulation results under the conditions of a hot - compression strain rate of 0.05 / s, a strain of 0.6, and a temperature of 450°C. Figure 3 This is the distribution of the equivalent stress in the cross - section in this embodiment; Figure 4 This is the distribution of the grain size in the cross - section in this embodiment;Figure 5 The distribution of the volume fraction of dynamic recrystallization in the cross-section in this embodiment.

[0092] Example 2:

[0093] The present invention also provides a multi-scale simulation system for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity. The multi-scale simulation system for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity can be realized by executing the process steps of the multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity. That is, those skilled in the art can understand the multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity as the preferred embodiment of the multi-scale simulation system for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity.

[0094] Specifically, the multi-scale simulation system for the dynamic recrystallization deformation structure and properties coupled with crystal plasticity includes:

[0095] Module M1, calculating and simulating the metal plastic processing process through a macroscopic finite element model;

[0096] Module M2, exporting the position information and deformation gradient history information of each unit integration point in the macroscopic finite element model, and outputting them to a file with the deformation simulation time and unit number as the index;

[0097] Module M3, obtaining the initial microstructure and initial mechanical properties of the metal material through experimental tests;

[0098] Module M4, calibrating the material parameters based on the initial microstructure and initial mechanical properties by using a mesoscopic crystal plasticity dynamic recrystallization model to obtain the calibrated model parameters;

[0099] Module M5, after preprocessing the deformation gradient history information exported in step S2, inputting it into the mesoscopic crystal plasticity dynamic recrystallization model with calibrated parameters, and predicting the evolution of the microstructure, texture and mechanical properties based on the initial microstructure, and outputting the stress value, microstructure and texture at a specified time;

[0100] Module M6, mapping the stress value, microstructure and texture to the deformed reconstructed geometry according to the position information exported in step S2, and visualizing the distribution of the microstructure and mechanical properties according to the index of the deformation simulation time and unit number.

[0101] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc., to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a kind of hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or structures within the hardware component.

[0102] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A multi-scale simulation method for the dynamic recrystallization deformation microstructure and properties coupling crystal plasticity, characterized in that It includes the following steps: Step S1, calculating and simulating the metal plastic processing process through a macroscopic finite element model; Step S2, deriving the position information and deformation gradient history information of each element integration point in the macroscopic finite element model, and outputting them to a file with the deformation simulation time and element number as the index; Step S3, obtaining the initial microstructure and initial mechanical properties of the metal material through experimental tests; Step S4, based on the initial microstructure and the initial mechanical properties, using a mesoscopic crystal plasticity dynamic recrystallization model to carry out the calibration of material parameters and obtain the calibrated model parameters; Step S5, after preprocessing the deformation gradient history information derived in Step S2, inputting it into the mesoscopic crystal plasticity dynamic recrystallization model after calibrating the parameters, and based on the initial microstructure, carrying out the prediction of the evolution of microstructure, texture and mechanical properties, and outputting the stress value, microstructure and texture at a specified time; Step S6, according to the position information derived in Step S2, mapping the stress value, microstructure and texture to the deformed reconstructed geometry, and visualizing the distribution of the microstructure and mechanical properties according to the index of the deformation simulation time and element number.

2. The multi-scale simulation method of the dynamic recrystallization deformation structure and properties coupling crystal plasticity according to claim 1, characterized in that In Step S1, a temperature-related macroscopic material constitutive model is adopted to establish a thermo-mechanical coupled macroscopic finite element model, and the deformation loading conditions and loading speed of the macroscopic finite element model are consistent with the actual hot deformation process.

3. A multi-scale simulation method for dynamic recrystallization deformation microstructure and properties coupling crystal plasticity according to claim 2, characterized in that, Step S1 is implemented through commercial finite element simulation software and includes the following sub-steps: Step S1.1, constructing a three-dimensional physical model of the hot compression part; Step S1.2, inputting the temperature-related macroscopic constitutive model; Step S1.3, setting the deformation loading conditions and loading speed consistent with the actual hot compression process; Step S1.4, carrying out mesh division and determining the boundary conditions; Step S1.5, carrying out simulation calculations to obtain the strain rate, strain amount and temperature range during the metal plastic hot compression process.

4. A multi-scale simulation method for dynamic recrystallization deformation microstructure and properties coupling crystal plasticity according to claim 1, characterized in that, In Step S2, in the form of batch post-processing or by writing a user subroutine, the position information and deformation gradient history information of the element integration points in the macroscopic finite element model are derived into a file according to the set time requirements and with the deformation simulation time and element number as the index.

5. A multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupling crystal plasticity according to claim 1, characterized in that In Step S3, the initial microstructure includes the microscopic grain orientation, size and morphology of no less than 100 grains obtained by EBSD; the initial mechanical properties include the experimental data of unidirectional tension and unidirectional compression in a specific direction, and the deformation amount, deformation speed and deformation temperature of the experimental tests cover the strain amount, strain rate and temperature range output in Step S1.

6. The multi-scale simulation method for the dynamic recrystallization deformation structure and properties coupling crystal plasticity according to claim 1, characterized in that, Step S4 includes the following sub-steps: Step S4.1, based on the deformation mechanisms of metal grain slip and dynamic recrystallization, constructing a crystal plasticity model, with the input being the initial microstructure of the grains measured in Step S3, and the number of grains used ≥ 100; Step S4.2, adjusting the parameters of the crystal plasticity model to make the deviation between the predicted stress-strain curve and the experimental data ≤ 10%, and the fitting deviation of the evolution of grain size and recrystallized volume fraction ≤ 15%; Step S4.3, determining the hardening parameters and recrystallization parameters.

7. A multi-scale simulation method for the dynamic recrystallization deformation microstructure and properties coupling crystal plasticity according to claim 6, characterized in that The step S4.2 includes: adjusting manually or automatically to optimize the matching degree in terms of shape and value between the stress-strain curve predicted by the crystal plasticity model under the corresponding deformation mode and the stress-strain curve measured experimentally, where the deviation in value is ≤10%, and simultaneously fitting the evolution of the grain size and the recrystallized volume fraction, where the deviation in value is ≤15%.

8. A multi-scale simulation method for the dynamic recrystallization deformation microstructure and properties coupling crystal plasticity according to claim 1, characterized in that The step S5 includes the following sub-steps: Step S5.1: Convert the deformation gradient history file extracted in the step S2 into the input format of the mesoscopic crystal plasticity dynamic recrystallization model and input the initial microstructure; Step S5.2: Conduct mesoscopic crystal plasticity dynamic recrystallization calculations for the integration points or characteristic cross-sectional area integration points in the macroscopic finite element model; Step S5.3: Output the stress values, grain sizes, and dynamic recrystallized volume fractions at specific moments.

9. A multi-scale simulation method for dynamic recrystallization deformation microstructure and properties coupling crystal plasticity according to claim 1, characterized in that, The step S6 includes the following sub-steps: Step S6.1: Reconstruct the deformation geometry based on the spatial positions of all integration points or characteristic cross-sectional area integration points in the macroscopic finite element model, and obtain the results of mesoscopic crystal plasticity recrystallization calculations by using the integration point numbers and deformation moments as indexes; Step S6.2: Display the stress values, grain sizes, and dynamic recrystallized volume fractions on the deformed and reconstructed geometry in the form of a contour map and export the numerical information.

10. A multi-scale simulation system for dynamic recrystallization deformation microstructure and properties coupling crystal plasticity, characterized in that It includes: Module M1: Calculate and simulate the metal plastic processing process through the macroscopic finite element model; Module M2: Export the position information and deformation gradient history information of each unit integration point in the macroscopic finite element model and output them to a file with the deformation simulation moment and unit number as indexes; Module M3: Obtain the initial microstructure and initial mechanical properties of the metal material through experimental tests; Module M4: Based on the initial microstructure and the initial mechanical properties, adopt the mesoscopic crystal plasticity dynamic recrystallization model to conduct calibration of material parameters and obtain the calibrated model parameters; Module M5: After preprocessing the deformation gradient history information exported in the step S2, input it into the mesoscopic crystal plasticity dynamic recrystallization model with calibrated parameters, and based on the initial microstructure, conduct predictions on the evolution of microstructure, texture, and mechanical properties, and output the stress values, microstructure, and texture at the specified moment; Module M6: Map the stress values, microstructure, and texture to the deformed and reconstructed geometry according to the position information exported in the step S2, and visualize the distribution of the microstructure and mechanical properties according to the indexes of the deformation simulation moment and unit number.

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