Metal structure material design method based on thermal-dynamic constraint

Abstract

The invention discloses a metal structure material design method based on thermal-dynamic constraint, and relates to the technical field of metal and alloy preparation. The method comprises the following steps: establishing a thermal-dynamic model of inverse austenite phase transformation, martensite phase transformation, carbon partition process and secondary martensite phase transformation included in a low-alloy high-strength steel'structure formation 'stage, and calculating thermal-dynamic constraints of the thermal-dynamic model of the inverse austenite phase transformation, the martensite phase transformation, the carbon partition process and the secondary martensite phase transformation; and performing weighted summation on the thermodynamics of each sub-process according to the thermodynamic contribution, calculating to obtain an overall effective thermodynamic parameter, and designing a material processing process parameter based on a large driving force-large generalized stability criterion to realize the high-strength and high-plasticity design of the material. According to the method, the machining process parameters of the metal structure material are designed based on the thermal-dynamic constraint, compared with a trial and error method of traditional material design, the strength and plasticity of the material can be predicted through the calculation result, then the optimal process parameters are obtained, the development cost is reduced, and the actual production efficiency is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of metal and alloy preparation, and particularly relates to a design method of metal structural materials based on thermal-kinetic constraints. Background Art

[0002] The third-generation high-strength steel plays an important role in fields such as aviation and automobiles due to its excellent tensile strength and tensile properties. However, it is still an urgent problem to realize the prediction of the microstructure based on the processing process and the determination of the process for target properties. At present, most design methods of metal structural materials still use the "trial and error method" to obtain high-performance materials, which greatly reduces the production efficiency and increases the production cost.

[0003] Generally, the mechanical properties are reflected in the specific service process or test process of materials with different microstructures, such as tensile property or fracture toughness test. However, it is impossible to test the performance of each material product to determine its optimal composition and process; and it is generally recognized in the industry that the large driving force - large general stability of the phase transformation process corresponds to the high-strength and high-ductility properties of the material (Acta Materialia. 201(2020)167–181). The physical action on the occurrence and development of phase transformation / deformation generated from thermodynamic or thermal-kinetic changes is defined as a constraint. The thermodynamic constraint represents the difficulty of initiating phase transformation / deformation, and the thermal-kinetic constraint, in terms of energy change, is reflected in the nucleation constraint growth and growth constraint nucleation. In terms of the process speed, it is reflected in the thermodynamic constraint dynamics and the kinetic constraint thermodynamics. For example, the martensitic transformation process is a thermodynamic constraint dynamics process. At the same time, the closed loop of composition / process - microstructure - property can be divided into two stages: "microstructure formation" and "property manifestation". Generally, the "microstructure formation" stage includes multiple sub-processes (nucleation-growth processes) that occur simultaneously or continuously, corresponding to different thermodynamic constraints and thermal-kinetic constraints. The thermal-kinetic constraints of each sub-process can be weighted according to the chemical driving force / mechanical driving force corresponding to the thermodynamic contribution, and then the evolution of the overall thermal-kinetic constraint accompanying the formation of the microstructure can be obtained. Summary of the Invention

[0004] Aiming at the deficiencies in the above-mentioned background technology, the present invention mainly solves the current situation that the design of traditional metal structural materials can only improve relevant process parameters through continuous experiments and "trial and error". Although materials with excellent performance can be obtained through the "trial and error method", the trial and error cost is high, the cycle is long and the efficiency is low. The present invention provides a design method for metal structural materials based on thermo-kinetic constraints. By designing the thermodynamic constraints and thermo-kinetic constraints in the "microstructure formation" stage of metal structural materials, and based on the judgment criterion of large driving force - large generalized stability, the process design of Fe-C-Mn-Si series low-alloy high-strength steel is carried out, and excellent properties of high strength and high plasticity are obtained, providing a method for improving the strength and plasticity of metal materials with improved production efficiency and reduced cost.

[0005] The first object of the present invention is to provide a design method for metal structural materials based on thermo-kinetic constraints, including the following steps:

[0006] Establish a thermo-kinetic model for inverse austenite transformation;

[0007] Establish a thermo-kinetic model for primary martensite transformation;

[0008] Establish a thermo-kinetic model for carbon partitioning process;

[0009] Establish a thermo-kinetic model for secondary martensite transformation according to the thermo-kinetic model of primary martensite transformation;

[0010] According to the thermo-kinetic model of inverse austenite transformation, the thermo-kinetic model of primary martensite transformation, the thermo-kinetic model of carbon partitioning process, and the thermo-kinetic model of secondary martensite transformation, fit the thermodynamic driving force and generalized stability of each phase transformation into a function of the quenching temperature of primary martensite transformation and the carbon partitioning time, and then perform weighted calculation on this function to obtain a function of equivalent driving force and overall effective generalized stability;

[0011] Combine the penalty function method with the quasi-Newton method to calculate the extreme value of the function of equivalent driving force and overall effective generalized stability, and predict the material properties and design the process parameter combination according to the large driving force - large generalized stability criterion.

[0012] Preferably, establishing a thermo-kinetic model for inverse austenite transformation includes:

[0013] Based on Thermo-calc software, simulate the inverse austenite transformation process to obtain the thermodynamic driving force of inverse austenite transformation;

[0014] Based on DICTRA software, simulate the inverse austenite transformation process to obtain the migration rate of the ferrite-austenite phase interface and its composition change with time. Combine the thermodynamic driving force of inverse austenite transformation to establish a kinetic energy barrier equation for inverse austenite transformation, and obtain the kinetic energy barrier of inverse austenite transformation;

[0015] Combining the thermodynamic driving force and the kinetic energy barrier of the inverse austenite transformation, a generalized stability expression for the phase transformation process is established to obtain the generalized stability of the inverse austenite transformation, and a thermo-kinetic model for the inverse austenite transformation process is established.

[0016] Preferably, a thermo-kinetic model for the primary martensite transformation is established, including:

[0017] Calculating the thermodynamic driving force of the martensite transformation process based on the sublattice model;

[0018] Based on the nucleation activation energy at the Ms point of the martensite transformation, a kinetic energy barrier equation for the martensite transformation is established to obtain the kinetic energy barrier of the martensite transformation;

[0019] Combining the thermodynamic driving force and the kinetic energy barrier of the martensite transformation process, a generalized stability expression for the martensite transformation is established to obtain the generalized stability of the martensite transformation, and a thermo-kinetic model for the martensite transformation process is established.

[0020] Preferably, a thermo-kinetic model for the carbon partitioning process is established, including:

[0021] Combining Fick's second law and the classical CCE model, using the Murray-Landis finite difference method, a group of diffusion models of carbon atoms in martensite and austenite is established, and the average carbon concentration and diffusion fraction of carbon atoms at the two-phase interface and in the crystal are solved to establish a carbon atom diffusion equation;

[0022] Substituting the carbon atom concentrations in the two phases into the chemical potential equations of carbon atoms in martensite and austenite, and solving to obtain the chemical potential values of carbon elements in martensite and austenite;

[0023] According to the carbon atom concentrations, transformation fraction and chemical potential values in the two phases, a weighted equation for the diffusion driving force of carbon atoms in martensite and the diffusion driving force in austenite is established to obtain the thermodynamic driving force of the carbon partitioning process;

[0024] Substituting the carbon atom concentrations in the two phases into the diffusion energy barrier equations of carbon atoms in the two phases, and combining with the weighted equation, a weighted equation for the diffusion energy barrier of carbon atoms in martensite and the diffusion energy barrier in austenite is established to obtain the kinetic energy barrier of the carbon atom partitioning process;

[0025] According to the effective thermodynamic driving force and the effective kinetic energy barrier of carbon partitioning, a generalized stability expression for the carbon partitioning process is established to obtain the generalized stability of the carbon partitioning process, and a thermo-kinetic model for the carbon partitioning process is established.

[0026] Preferably, the expression for the generalized stability of the carbon partitioning process is:

[0027]

[0028] Among them, Q* and ΔG* are the kinetic energy barrier and thermodynamic driving force at the beginning of the transformation.

[0029] Preferably, a thermal-kinetic model for secondary martensitic transformation is established, including:

[0030] According to the empirical equation, the initial point of martensitic transformation is calculated to determine whether secondary martensitic transformation occurs. If it occurs, a thermal-kinetic model for secondary martensitic transformation is established based on the thermal-kinetic model of primary martensitic transformation.

[0031] Preferably, the empirical equation for calculating the initial point of martensitic transformation to determine whether secondary martensite occurs is:

[0032] M s = 541 - 401 * C (wt%) - 36 * Mn (wt%) - 10.5 * Si (wt%).

[0033] Preferably, the functions of the equivalent driving force and the overall effective generalized stability are:

[0034] ΔG eff = φ RT * ΔG RT + φ MT1 * ΔG MT1 + φ PT * ΔG PT + φ MT2 * ΔG MT2

[0035]

[0036] In the formula, RT represents reverse austenite transformation; MT1 represents martensitic transformation; PT represents carbon partitioning; MT2 represents secondary martensitic transformation; eff represents overall effective;

[0037]

[0038] In the formula, ΔG all is the difference between the maximum and minimum values of the phase transformation driving force.

[0039] Preferably, relying on the large driving force - large generalized stability criterion, the optimal combination of process parameters is designed as quenching at 190 °C and carbon partitioning for 200 s.

[0040] The second object of the present invention is to provide an application of a method for designing metal structural materials based on thermal-kinetic constraints in improving the strength and plasticity of low-alloy steel.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] The present invention provides a method for designing metal structural materials based on thermal-kinetic constraints. This method establishes a thermal-kinetic model for the main phase transformation processes during the formation of quenching partitioning steel (Fe-C-Mn-Si steel system), and then summarizes the comprehensive thermal-kinetic model in the "microstructure formation" stage, that is, the overall thermal-kinetic constraints accompany the evolution of microstructure formation. According to the criterion of large driving force - large general stability, the optimal process parameters of the material are obtained, and then the optimal strength-plasticity of the material is obtained.

[0043] By designing the thermodynamic constraints and thermal-kinetic constraints in the "microstructure formation" stage of metal structural materials, based on the judgment criterion of large driving force - large general stability, the process design of low-alloy high-strength steel (Fe-C-Mn-Si steel system) is carried out, and excellent properties of high strength and high plasticity are obtained, providing a method for improving the strength and plasticity of metal materials with improved production efficiency and reduced cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a process flow chart of the method for designing materials based on thermal-kinetics proposed by the present invention and the main phase transformation processes involved in the example material QP steel.

[0045] Figure 2 It is the thermodynamic driving force, kinetic energy barrier and general stability of the models in each stage in the embodiment of the present invention.

[0046] Figure 3 It is the overall equivalent driving force, general stability in the "microstructure formation" stage obtained in the example of the present invention, and the corresponding process parameters (taking partitioning for 200 s after quenching at different temperatures and partitioning at different times after quenching as examples).

[0047] Figure 4 It is the yield strength and uniform elongation of the sheet prepared with the optimal process parameters in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] In order to enable those skilled in the art to better understand and implement the technical solution of the present invention, the present invention will be further described below in conjunction with specific embodiments and drawings, but the specific embodiments cited do not limit the present invention.

[0049] The method for designing metal structural materials based on thermal-kinetic constraints provided by the present invention aims to establish a thermal-kinetic model for the main phase transformation processes during the formation of low-alloy high-strength steel (Fe-C-Mn-Si steel system), and then summarize the comprehensive thermal-kinetic model in the "microstructure formation" stage. According to the criterion of large driving force - large general stability, the optimal process parameters of the material are obtained, and then the optimal strength-plasticity of the material is obtained.

[0050] To achieve the above object, the present invention provides a method for designing a metal structural material based on thermal-kinetic constraints, comprising the following steps:

[0051] Establish a thermal-kinetic model for reverse austenite transformation;

[0052] Establish a thermal-kinetic model for primary martensite transformation;

[0053] Establish a thermal-kinetic model for carbon partitioning process;

[0054] Establish a thermal-kinetic model for secondary martensite transformation based on the thermal-kinetic model of primary martensite transformation;

[0055] According to the thermal-kinetic models of reverse austenite transformation, primary martensite transformation, carbon partitioning process, and secondary martensite transformation, fit the thermodynamic driving force and generalized stability of each transformation into a function of the quenching temperature of primary martensite transformation and carbon partitioning time, and then perform weighted calculation on this function to obtain a function of equivalent driving force and overall effective generalized stability;

[0056] Combine the penalty function method with the quasi-Newton method to calculate the extreme value of the function of equivalent driving force and overall effective generalized stability, and predict the material properties and design the process parameter combination according to the large driving force - large generalized stability criterion.

[0057] Among them, establishing the thermal-kinetic model for reverse austenite transformation includes:

[0058] Simulate the reverse austenite transformation process based on Thermo-calc software to obtain the thermodynamic driving force for reverse austenite transformation;

[0059] Simulate the reverse austenite transformation process based on DICTRA software to obtain the migration rate of the ferrite-austenite phase interface and its composition change over time, and combine with the thermodynamic driving force for reverse austenite transformation to establish a kinetic energy barrier equation for reverse austenite transformation, and obtain the kinetic energy barrier for reverse austenite transformation;

[0060] Combine the thermodynamic driving force for reverse austenite transformation and the kinetic energy barrier for reverse austenite transformation to establish a generalized stability expression for the phase transformation process, obtain the generalized stability for reverse austenite transformation, and establish a thermal-kinetic model for the reverse austenite transformation process.

[0061] Establishing the thermal-kinetic model for primary martensite transformation includes:

[0062] Calculate the thermodynamic driving force for martensite transformation process based on the sublattice model;

[0063] Based on the nucleation activation energy at the Ms point of martensite transformation, establish a kinetic energy barrier equation for martensite transformation to obtain the kinetic energy barrier for martensite transformation;

[0064] Combining the thermodynamic driving force and the kinetic energy barrier of the martensitic transformation process, a generalized stability expression for the martensitic transformation is established, the generalized stability of the martensitic transformation is obtained, and a thermal-kinetic model of the martensitic transformation process is established.

[0065] Establish a thermal-kinetic model for the carbon partitioning process, including:

[0066] Combining Fick's second law and the classical CCE model, using the Murray-Landis finite difference method, a diffusion model group of carbon atoms in martensite and austenite is established. By solving, the average carbon concentration and diffusion fraction of carbon atoms at the two-phase interface and in the crystal are obtained, and a carbon atom diffusion equation is established;

[0067] Substitute the carbon concentrations in the two phases into the chemical potential equations of carbon atoms in martensite and austenite, and solve to obtain the chemical potential values of carbon elements in martensite and austenite;

[0068] According to the carbon concentrations, transformation fractions, and chemical potential values in the two phases, establish a weighted equation for the diffusion driving force of carbon atoms in martensite and the diffusion driving force in austenite, and obtain the thermodynamic driving force of the carbon partitioning process;

[0069] Substitute the carbon concentrations in the two phases into the diffusion energy barrier equations of carbon atoms in the two phases, and combine with the weighted equation to establish a weighted equation for the diffusion energy barrier of carbon atoms in martensite and the diffusion energy barrier in austenite, and obtain the kinetic energy barrier of the carbon atom partitioning process;

[0070] According to the effective thermodynamic driving force and the effective kinetic energy barrier of carbon partitioning, establish a generalized stability expression for the carbon partitioning process, obtain the generalized stability of the carbon partitioning process, and establish a thermal-kinetic model of the carbon partitioning process.

[0071] The expression for the generalized stability of the carbon partitioning process is:

[0072]

[0073] where Q* and △G* are the kinetic energy barrier and the thermodynamic driving force at the beginning of the transformation.

[0074] Establish a thermal-kinetic model for the secondary martensitic transformation, including:

[0075] According to the empirical equation, calculate the initial point of the martensitic transformation, judge whether the secondary martensitic transformation occurs. If it occurs, establish a thermal-kinetic model for the secondary martensitic transformation based on the thermal-kinetic model of the primary martensitic transformation.

[0076] The empirical equation for calculating the initial point of the martensitic transformation to judge whether the secondary martensitic transformation occurs is:

[0077] M s = 541 - 401 * C (wt%) - 36 * Mn (wt%) - 10.5 * Si (wt%).

[0078] The functions of the equivalent driving force and the overall effective generalized stability are as follows:

[0079] ΔG eff = φ RT * ΔG RT + φ MT1 * ΔG MT1 + φ PT * ΔG PT + φ MT2 * ΔG MT2

[0080]

[0081] In the formula, RT represents reverse austenite transformation; MT1 represents martensite transformation; PT represents carbon partitioning; MT2 represents secondary martensite transformation; eff represents overall effectiveness;

[0082]

[0083] In the formula, △G all is the difference between the maximum and minimum values of the phase transformation driving force.

[0084] Relying on the large driving force - large generalized stability criterion, the optimal combination of process parameters is designed as quenching at 190 °C and carbon partitioning for 200 s.

[0085] The present invention provides an application of a design method for metal structural materials based on thermo - kinetic constraints in enhancing the strength and plasticity of low - alloy steel.

[0086] Exemplarily, a design method for metal structural materials based on thermo - kinetic constraints includes the following steps:

[0087] 1) Establish a thermo - kinetic model of reverse austenite transformation

[0088] 1.1) Simulate the reverse austenite transformation process based on Thermo - calc software to obtain the thermodynamic driving force of reverse austenite transformation;

[0089] 1.2) Simulate the reverse austenite transformation process based on DICTRA software to obtain the migration rate of the ferrite (bcc phase) - austenite (fcc phase) phase interface and the change of its composition with time. Combining with the thermodynamic driving force of reverse austenite transformation obtained in step 1.1), establish a kinetic energy barrier equation for reverse austenite transformation to obtain the kinetic energy barrier of reverse austenite transformation;

[0090] The kinetic energy barrier equation for the reverse austenite phase transformation described in step 1.2) is as follows:

[0091]

[0092] v = MΔG

[0093] Wherein, R represents the gas constant, 8.314 J / mol / K; T represents the phase transformation temperature; v is the interface migration rate; M0 is the pre-exponential factor of the grain boundary mobility; ΔG is the thermodynamic driving force for the reverse austenite phase transformation; M is the interface mobility.

[0094] 1.3) Combining the driving force and energy barrier obtained in steps 1.1) and 1.2), establish a general stability expression for the phase transformation process, obtain the general stability of the reverse austenite phase transformation, and establish a thermo-kinetic model for the reverse austenite phase transformation process;

[0095] The general stability of the reverse austenite phase transformation described in step 1.3) is:

[0096]

[0097] Where Q * , △G * are the kinetic energy barrier and thermodynamic driving force at the beginning of the transformation (transformation fraction is 0).

[0098] 2) Establish a thermo-kinetic model for the primary martensite phase transformation

[0099] 2.1) Calculate the thermodynamic driving force for the martensite phase transformation based on the sublattice model;

[0100] In step 2.1), the thermodynamic driving force for the martensite phase transformation is:

[0101]

[0102] Where ΔG chem is the chemical driving force; ΔG s is the strain energy, taking 41.9 J / mol; T mt is the starting temperature of the martensite phase transformation; T mf is the ending temperature of the martensite phase transformation.

[0103] 2.2) Based on the nucleation activation energy at the Ms point of the martensite phase transformation, establish a kinetic energy barrier equation for the martensite phase transformation to obtain the kinetic energy barrier of the martensite phase transformation;

[0104] In step 2.2), the kinetic energy barrier of the martensite phase transformation is:

[0105]

[0106] Where Q mtis the nucleation activation energy at the start of martensitic transformation, i.e., the nucleation activation energy at the M s point.

[0107] 2.3) Combine the driving force and energy barrier obtained in steps 2.1) and 2.2) to establish a general stability expression for martensitic transformation, obtain the general stability of martensitic transformation, and establish a thermo-kinetic model for the martensitic transformation process;

[0108] In step 2.3), the general stability expression for martensitic transformation is:

[0109]

[0110] where Q * , △G * are the kinetic energy barrier and thermodynamic driving force at the beginning of the transformation (transformation fraction is 0).

[0111] 3) Establish a thermo-kinetic model for the carbon partitioning process

[0112] 3.1) Combine Fick's second law and the classical CCE model, and use the Murray-Landis finite difference method to establish a set of diffusion models for carbon atoms in martensite and austenite. Solve to obtain the average carbon concentration and diffusion fraction of carbon atoms at the two-phase interface and in the crystal interior, and establish a carbon atom diffusion equation;

[0113] The carbon atom diffusion equation described in step 3.1) is:

[0114]

[0115] Combined with the Murray-Landis finite difference method:

[0116]

[0117] where the classical CCE model uses the model described in "Acta Materialia, 2003, 51: 2611-2622". The thermodynamic driving force equation for carbon partitioning is:

[0118]

[0119] where

[0120]

[0121] In the formula, f α , f γ are the diffusion fractions of carbon atoms in the α and γ phases, respectively; are the mole fractions of carbon atoms in the α and γ phases, respectively; is the chemical potential of carbon at the center of the α and γ phases; is the chemical potential of carbon at the α / γ phase interface.

[0122] 3.2) Substitute the concentrations of carbon atoms in the two phases obtained in step 3.1) into the chemical potential equations of carbon atoms in martensite and austenite, and solve to obtain the chemical potential values of carbon in martensite and austenite;

[0123] 3.3) Combine the concentrations of carbon atoms in the two phases obtained in step 3.1), the transformation fraction, and the chemical potential values obtained in step 3.2) to establish a weighted equation for the diffusion driving force of carbon atoms in martensite and its diffusion driving force in austenite, and obtain the thermodynamic driving force for the carbon partitioning process;

[0124] 3.4) Substitute the concentrations of carbon atoms in the two phases obtained in step 3.1) into the diffusion energy barrier equations of carbon atoms in the two phases, and combine with the weighting method in step 3.3) to establish a weighted equation for the diffusion energy barrier of carbon atoms in martensite and the diffusion energy barrier in austenite, and obtain the kinetic energy barrier for the carbon partitioning process;

[0125] The carbon partitioning kinetic energy barrier described in step 3.4) is:

[0126]

[0127] where

[0128]

[0129] In the formula, are the kinetic energy barriers of carbon in the α and γ phases, respectively.

[0130] 3.5) Combine the effective thermodynamic driving force for carbon partitioning obtained in step 3.3) and the effective kinetic energy barrier for carbon partitioning obtained in step 3.4) to establish a general stability expression for the carbon partitioning process, obtain the general stability of the carbon partitioning process, and establish a thermo-kinetic model for the carbon partitioning process;

[0131] As described in step 3.5), the expression for the general stability of the carbon partitioning process is:

[0132]

[0133] where Q * , △G * are the kinetic energy barrier and thermodynamic driving force at the beginning of the transformation (transformation fraction is 0).

[0134] 4) Establish a thermo-kinetic model for the secondary martensitic transformation

[0135] 4.1) According to the empirical equation, calculate the initial point of the martensitic transformation (M sAt point), determine whether secondary martensitic transformation occurs. If it does, establish a heat-kinetic model for secondary martensitic transformation according to step 2).

[0136] The empirical formula for calculating M s point in step 4) to determine whether secondary martensite occurs is as follows:

[0137] M s = 541 - 401*C (wt%) - 36*Mn (wt%) - 10.5*Si (wt%).

[0138] 5) Combine the heat-kinetic models obtained in steps 1), 2), 3), and 4), and use a large amount of calculation data to fit the thermodynamic driving force and generalized stability (ΔG, GS) of each phase transformation into functions of QT (austenite transformation quenching temperature) and Pt (carbon partitioning time). Subsequently, perform weighted calculations on these functions to obtain functions of the equivalent driving force and overall effective generalized stability [ΔG eff (QT, Pt), GS eff (QT, Pt)];

[0139] The expressions for the equivalent driving force and generalized stability in step 5) are as follows:

[0140] ΔG eff = φ RT *ΔG RT + φ MT1 *ΔG MT1 + φ PT *ΔG PT + φ MT2 *ΔG MT2

[0141]

[0142] where RT represents reverse austenite transformation; MT1 represents martensite transformation; PT represents carbon partitioning; MT2 represents secondary martensite transformation; eff represents overall effective.

[0143]

[0144] where ΔG all is the difference between the maximum and minimum values of the phase transformation driving force.

[0145] 6) Apply the functions of the equivalent driving force and overall effective generalized stability obtained in step 5), and use the penalty function method (interior point method) combined with the quasi-Newton method (BFGS method) to find ΔG eff (QT , Pt), GS eff (QT ,(Pt) Extreme values. According to the large driving force - large generalized stability criterion, predict the material properties and design the combination of process parameters.

[0146] Apply the equivalent driving force and generalized stability obtained in step 6), and rely on the large driving force - large generalized stability criterion to design the optimal combination of process parameters as quenching at 190 °C and carbon partitioning for 200 s.

[0147] In order to illustrate a method for designing metal structural materials based on thermo - kinetic constraints provided by the present invention, it is described in conjunction with the accompanying drawings.

[0148] First, according to the thermo - kinetic model of the main phase transformation processes involved in the "structure formation" stage of quenching and partitioning steel (Fe - C - Mn - Si steel), calculate the thermodynamic driving force and generalized stability of each process. The process is as Figure 1 shown in a. See Figure 1 shown in b. The phase transformation process includes: reverse austenite transformation - primary martensite transformation - carbon partitioning - secondary martensite transformation. The calculation results include:

[0149] (1) Reverse austenite transformation at 850 °C, as Figure 2 shown in a;

[0150] (2) Primary martensite transformation between Ms - Mf points (170 - 250 °C), as Figure 2 shown in b;

[0151] (3) Heat up to 400 °C and carry out carbon partitioning for different times (20 s, 50 s, 200 s) respectively, as Figure 2 shown in d;

[0152] Carbon partitioning with the same partitioning time (200 s) at different quenching temperatures (170 - 250 °C), as Figure 2 shown in c;

[0153] (4) Finally, quench and judge whether secondary martensite transformation occurs, as Figure 2 shown in e;

[0154] According to the thermodynamic constraints and thermo - kinetic constraints corresponding to the continuous sub - processes included in the "structure formation" stage, weight the thermo - kinetic constraints of each sub - process by the chemical driving force corresponding to the thermodynamic constraints, and then obtain the evolution of the overall thermo - kinetic constraints accompanying the formation of the microstructure, that is, the comprehensive thermo - kinetic model and its corresponding driving force and generalized stability.

[0155] Compare the driving force and generalized stability results obtained from carbon partitioning for 200 s at quenching temperatures of 170 - 250 °C, as Figure 3As shown in Fig. a, with the continuous increase of the quenching temperature, its thermodynamic driving force continuously decreases, and an inflection point appears at 210 °C and then starts to increase. The generalized stability increases with the continuous increase of the quenching temperature, and an inflection point appears at 210 °C and then starts to decrease. According to the large driving force - large generalized stability criterion, when the material is subjected to carbon partitioning for 200 s after quenching at 210 °C, it should exhibit the best plasticity but relatively low strength. Comparing the driving force and generalized stability results obtained at different carbon partitioning times under the quenching temperature of 190 °C, as Figure 3 shown in Fig. b, with the continuous extension of the partitioning time, its thermodynamic driving force continuously decreases, and the generalized stability continuously increases. According to the large driving force - large generalized stability criterion, when the material is quenched at 190 °C and then subjected to carbon partitioning for about 200 s, it should exhibit the best strength and plasticity.

[0156] According to a method for designing a metal structural material based on thermo - kinetic constraints provided by the present invention, specific examples are also operated in this embodiment. The process parameters are selected as: QT = 170 °C / 190 °C / 210 °C / 250 °C, Pt = 200 s and QT = 190 °C, Pt = 20 s / 50 s / 200 s for quenching and partitioning experiments, which are respectively denoted as QT170(or 190 or 210 or 250)-200(or 20 or 50) to verify the effectiveness of the method of the present invention, specifically as follows:

[0157] First, a dilatometer (DIL) is used to perform quenching and partitioning treatment on a standard tensile specimen (5 mm in length, 2 mm in width). The sample is heated to 850 °C at a rate of 5 K / s and held for 300 s to complete the reverse austenite phase transformation stage. Then, it is cooled to 250 °C at a rate of 10 K / s and held for 5 s to complete the martensite phase transformation stage. Next, the sample is heated to 400 °C at a heating rate of 5 K / s and held for 200 s to complete the carbon partitioning stage. Finally, it is directly cooled to room temperature at a cooling rate of 10 K / s to complete the secondary martensite phase transformation stage.

[0158] Samples with the selected different process parameters are prepared in sequence according to the above steps.

[0159] A universal testing machine is used to conduct room - temperature uniaxial tensile tests on the QP steel. Figure 4 Fig. c shows the tensile engineering stress - strain curves of the specimens after quenching at 170, 190, 210, and 250 °C and then subjected to 200 s of carbon partitioning, all showing continuous yield behavior. Correspondingly, the values of the 0.2% offset yield strength and uniform elongation obtained under all conditions are as Figure 4As shown in Fig. a, the yield strength and uniform elongation of the QT190-200 specimen are 1018.04 MPa and 12.58% respectively. Compared with the properties of 1239.6 MPa and 11.23%, 860.48 MPa and 13.45%, 881.76 MPa and 7.61% of the QT170-200, QT230-200, and QT250-200 samples, the product of strength and plasticity of QT190-200 is the highest, and its performance is better. And as Figure 3 shown in Fig. a, its generalized stability and driving force are both large; Figure 4 Fig. d shows the tensile engineering stress-strain curves of the specimens after quenching at a temperature of 190 °C and then undergoing carbon partitioning for 20 s, 50 s, and 200 s, all of which exhibit continuous yielding behavior. The values of the 0.2% offset yield strength and uniform elongation obtained under all corresponding conditions are as Figure 4 shown in Fig. b. Among them, the yield strength and uniform elongation of QT190-200 are 1018.04 MPa and 12.58% respectively. Compared with the properties of 1066.13 MPa and 8.21%, 1035.8 MPa and 10.87% of the QT190-20s and QT190-50s samples, its yield strength is the lowest, and the corresponding Figure 3 thermodynamic driving force in Fig. b is the smallest, and the uniform elongation is the highest, and the corresponding Figure 3 generalized stability in Fig. b is the largest. However, the difference in its yield strength is not significant, and its uniform elongation is higher. Therefore, the performance of the sample with 200 s carbon partitioning after quenching at 190 °C is the best. On the other hand, with the change of heat treatment parameters, the change of the tensile results of the samples is basically consistent with the change of the calculated and predicted thermodynamics results.

[0160] Therefore, for the current sample situation, it can be concluded that there is a correlation between the phase transformation thermodynamics and mechanical properties. That is: the greater the driving force, the higher the yield strength, the greater the generalized stability, and the better the uniform elongation. The conditions for obtaining a higher yield strength and good plasticity are indeed the same as the above predictions. By exploring the influence of different composition contents and process parameters on the thermodynamic driving force and generalized stability of the material, and conducting mechanical property prediction, through the method of the present invention, it can provide an important reference basis for experimental work, avoid a large number of repeated experimental work, greatly reduce the R & D cost, improve the production efficiency, and has high practical value.

[0161] In summary, the present invention provides a method for designing metal structural materials based on thermo-kinetic constraints. The method includes establishing thermo-kinetic models for reverse austenite transformation, martensite transformation, carbon partitioning process, and secondary martensite transformation included in the "microstructure formation" stage of low-alloy high-strength steel, and calculating its thermo-kinetic constraints (such as thermodynamic driving force, kinetic energy barrier, and generalized stability, etc.); performing weighted summation of the thermo-kinetics of each sub-process according to the thermodynamic contribution, calculating the overall effective thermo-kinetic parameters, and designing the material processing process parameters based on the large driving force - large generalized stability criterion to achieve the design of high strength and high plasticity of the material. The present invention designs the processing process parameters of metal structural materials based on thermo-kinetic constraints. Compared with the "trial and error method" of traditional material design, it can predict the strength and plasticity of materials through calculation results, thereby obtaining the optimal process parameters, reducing development costs, and optimizing the actual production efficiency.

[0162] The present invention describes the preferred embodiments and their effects. However, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0163] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A design method for metal structural materials based on thermo-kinetic constraints, characterized in that Including the following steps: Establish a thermal-kinetic model for inverse austenite transformation; Establish a thermal-kinetic model for primary martensite transformation; Establish a thermal-kinetic model for carbon partitioning process; Establish a thermal-kinetic model for secondary martensite transformation based on the thermal-kinetic model of primary martensite transformation; According to the thermal-kinetic models of inverse austenite transformation, primary martensite transformation, carbon partitioning process, and secondary martensite transformation, fit the thermodynamic driving force and generalized stability of each phase transformation into a function of the quenching temperature of primary martensite transformation and carbon partitioning time. Subsequently, perform a weighted calculation on this function to obtain a function of equivalent driving force and overall effective generalized stability; Combine the penalty function method with the quasi-Newton method to calculate the extreme value of the function of equivalent driving force and overall effective generalized stability, and predict the material properties and design the process parameter combination based on the large driving force - large generalized stability criterion.

2. The method for designing a metal structure material based on thermo-kinetic constraints according to claim 1, wherein Establish a thermal-kinetic model for inverse austenite transformation, including: Simulate the inverse austenite transformation process based on Thermo-calc software to obtain the thermodynamic driving force of inverse austenite transformation; Simulate the inverse austenite transformation process based on DICTRA software to obtain the migration rate of the ferrite-austenite phase interface and its composition change over time. Combine the thermodynamic driving force of inverse austenite transformation to establish a kinetic energy barrier equation for inverse austenite transformation, and obtain the kinetic energy barrier of inverse austenite transformation; Combine the thermodynamic driving force of inverse austenite transformation and the kinetic energy barrier of inverse austenite transformation to establish a generalized stability expression for the phase transformation process, obtain the generalized stability of inverse austenite transformation, and establish a thermal-kinetic model for the inverse austenite transformation process.

3. The method for designing a metallic structural material based on thermo-kinetic constraints according to claim 1, wherein Establish a thermal-kinetic model for primary martensite transformation, including: Calculate the thermodynamic driving force of martensite transformation based on the sublattice model; Based on the nucleation activation energy at the Ms point of martensite transformation, establish a kinetic energy barrier equation for martensite transformation to obtain the kinetic energy barrier of martensite transformation; Combine the thermodynamic driving force of martensite transformation process and the kinetic energy barrier of martensite transformation to establish a generalized stability expression for martensite transformation, obtain the generalized stability of martensite transformation, and establish a thermal-kinetic model for the martensite transformation process.

4. The method for designing a metal structure material based on thermo-kinetic constraints according to claim 1, wherein Establish a thermal-kinetic model for carbon partitioning process, including: Combine Fick's second law and the classical CCE model, and use the Murray-Landis finite difference method to establish a set of diffusion models for carbon atoms in martensite and austenite. Solve to obtain the average carbon concentration and diffusion fraction at the phase interface and in the crystal interior of carbon atoms, and establish a carbon atom diffusion equation; Substitute the carbon concentrations in the two phases into the chemical potential equations of carbon atoms in martensite and austenite, and solve to obtain the chemical potential values of carbon elements in martensite and austenite; According to the carbon concentrations, transformation fractions, and chemical potential values in the two phases, establish a weighted equation for the diffusion driving force of carbon atoms in martensite and its diffusion driving force in austenite to obtain the thermodynamic driving force of the carbon partitioning process. Substitute the carbon atom concentrations in the two phases into the diffusion energy barrier equation of carbon atoms in the two phases, combine it with the weighting equation, establish the weighting equation of the diffusion energy barrier of carbon atoms in martensite and in austenite, and obtain the kinetic energy barrier of the carbon atom partitioning process; Based on the effective thermodynamic driving force of carbon partitioning and the effective kinetic energy barrier of carbon partitioning, establish the general stability expression of the carbon partitioning process, obtain the general stability of the carbon partitioning process, and establish the thermo-kinetic model of the carbon partitioning process.

5. The design method of the metal structural material based on thermo-kinetic constraints according to claim 4, characterized in that The expression of the general stability of the carbon partitioning process is: Among them, Q* and △G* are the kinetic energy barrier and the thermodynamic driving force at the beginning of the transformation.

6. The method for designing a metallic structural material based on thermo-kinetic constraints according to claim 1, wherein Establish the thermo-kinetic model of secondary martensitic transformation, including: According to the empirical equation, calculate the initial point of martensitic transformation, judge whether secondary martensitic transformation occurs. If it occurs, establish the thermo-kinetic model of secondary martensitic transformation according to the thermo-kinetic model of primary martensitic transformation.

7. The method for designing a metallic structural material based on thermo-kinetic constraints according to claim 6, wherein The empirical equation for calculating the initial point of martensitic transformation to judge whether secondary martensite occurs is: M s = 541 - 401 * C (wt%) - 36 * Mn (wt%) - 10.5 * Si (wt%).

8. The method for designing a metal structural material based on thermo-kinetic constraints according to claim 1, wherein The function of the equivalent driving force and the overall effective general stability is: ΔG eff = φ RT *ΔG RT + φ MT1 *ΔG MT1 + φ PT *ΔG PT + φ MT2 *ΔG MT2 In the formula, RT represents reverse austenite transformation; MT1 represents martensitic transformation; PT represents carbon partitioning; MT2 represents secondary martensitic transformation; eff represents overall effective; where, △G all is the difference between the maximum and minimum values of the phase transformation driving force.

9. The design method of a metal structure material based on thermo-kinetic constraints according to claim 1, characterized in that, Relying on the large driving force - large general stability criterion, design the optimal process parameter combination as quenching at 190°C and carbon partitioning for 200 s.

10. Application of the method according to any one of claims 1 to 9 in improving the strength and plasticity of low alloy steel.

Images