Information processing method, program, and information processing device

Abstract

To provide an information processing method, etc., that can perform simulations that reflect variations in the martensitic transformation initiation temperature. [Solution] The information processing method involves a computer that repeatedly performs the following steps to calculate the state of the object at the end of cooling: acquiring information about the shape of the object to be analyzed, acquiring physical properties of each phase and temperature of the steel constituting the object to be analyzed, acquiring information about the initial state of the object to be analyzed after heating, acquiring the results of a coupled analysis of the thermal conductivity analysis and elastoplastic analysis of the object to be analyzed after a time width Δt has elapsed, calculating the bainite fraction of the object to be analyzed based on the coupled analysis results, calculating the austenite fraction of the object to be analyzed based on the bainite fraction, calculating the martensitic transformation start temperature of the object to be analyzed based on the austenite fraction, and calculating the martensite fraction of the object to be analyzed based on the martensitic transformation start temperature.

Description

Technical Field

[0001] The present invention relates to an information processing method, a program, and an information processing apparatus.

Background Art

[0002] In order to predict the state after quenching steel, simulations using a computer are used (Patent Document 1, Non-Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Non-Patent Documents

[0004]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In the steel quenching operation, steel with desired properties is obtained by cooling the steel material heated to the austenite state. Austenitic steel mainly transforms into martensite by rapid cooling. The transformation start temperature from austenite to martensite varies depending on the amount of carbon contained in the steel, the amount of trace elements such as manganese, and the austenite fraction immediately before the start of transformation.

[0006] However, in the simulations disclosed in Patent Document 1 and Non-Patent Document 1, a simulation reflecting the variation in the martensite transformation start temperature cannot be performed.

[0007] One aspect of this is the aim to provide information processing methods that can perform simulations that reflect variations in the martensitic transformation onset temperature. [Means for solving the problem]

[0008] The information processing method involves a computer repeatedly performing the following steps to calculate the state of the object at the end of its cooling: acquiring information about the shape of the object to be analyzed; acquiring physical properties of each phase and temperature of the steel constituting the object; acquiring information about the initial state of the object after it has been heated; acquiring the results of a coupled analysis of the thermal conduction analysis and elastoplastic analysis of the object after a time width Δt has elapsed; calculating the bainite fraction of the object based on the coupled analysis results; calculating the austenite fraction of the object based on the bainite fraction; calculating the martensitic transformation onset temperature of the object based on the austenite fraction; and calculating the martensite fraction of the object based on the martensitic transformation onset temperature. [Effects of the Invention]

[0009] In one respect, this provides information processing methods that can perform simulations that reflect variations in the transformation initiation temperature from austenite to martensite. [Brief explanation of the drawing]

[0010] [Figure 1] This is an explanatory diagram illustrating the overview of the heat treatment simulation. [Figure 2] This is an explanatory diagram illustrating the continuous cooling transformation of steel. [Figure 3] This is an enlarged view of part III in Figure 2. [Figure 4] This graph shows the relationship between the austenite fraction and the martensitic transformation initiation temperature. [Figure 5] This is an explanatory diagram illustrating the configuration of an information processing device. [Figure 6] This is a flowchart that explains the processing flow of a program. [Figure 7] This is a flowchart for explaining the process flow of the subroutine for calculating the phase fraction. [Figure 8] This is an explanatory diagram for explaining the analysis target model. [Figure 9] This is a graph for explaining the simulation result regarding the temperature change. [Figure 10] This is a graph showing the simulation result regarding the change in the phase fraction in the core part. [Figure 11] This is a graph showing the simulation result regarding the change in the phase fraction in the corner part. [Figure 12] This is a graph showing the simulation result regarding the change in the martensite phase fraction in the core part and the corner part.

Embodiments for Carrying Out the Invention

[0011] [Embodiment 1] When manufacturing a steel product, heat treatment such as quenching and tempering is performed on a base material that has been formed into a desired shape by machining such as casting, forging, and cutting. It is known that in quenching, the structure and properties of the steel after cooling are greatly changed depending on the cooling rate.

[0012] For example, in a large steel product such as a die-cast mold, the cooling rate inside the product is slower than that on the surface of the product. Numerical calculation methods such as the finite element method are suitable for simulating phenomena where the situation changes depending on the location.

[0013] FIG. 1 is an explanatory diagram for explaining the outline of the quenching simulation. Using FIG. 1, the outline of the process executed by the control unit 11 (see FIG. 5) will be explained. The control unit 11 acquires the calculation conditions specified by the user. The calculation conditions include information regarding the shape of the analysis target object 44 (see FIG. 8), information regarding the physical property values of the material constituting the analysis target object 44, information regarding the initial state of the analysis target object 44, and information regarding the boundary conditions of the analysis target object 44.

[0014] Information regarding the shape of the object to be analyzed 44 is represented, for example, by a 3D-CAD (3 Dimensional Computer Aided Design) model. When the object to be analyzed 44 has a simple shape such as a square plate, for example, information regarding the shape of the object to be analyzed 44 may be represented by several parameters such as a symbol indicating the shape, the length of one side, and the thickness.

[0015] Information regarding the physical property values of the object to be analyzed 44 is the physical property values and mechanical properties at each phase and each temperature of the steel constituting the object to be analyzed 44. The physical property values are, for example, density, thermal conductivity, specific heat, linear expansion coefficient, and phase transformation parameters. The mechanical properties are, for example, Young's modulus, Poisson's ratio, and deformation resistance during plastic deformation.

[0016] Note that all of the physical property values and mechanical properties listed here are merely examples. Only some of the listed physical property values and mechanical properties may be used in the simulation described later. Data other than the listed physical property values and mechanical properties may also be used in the simulation described later.

[0017] Information regarding the initial state is, for example, the initial temperature and boundary conditions of the object to be analyzed 44. The initial temperature is, for example, the quenching temperature, that is, the temperature immediately before heating ends and cooling starts. When calculating the state after the quenching process, the initial state of the object to be analyzed 44 is the temperature at which the quenching target portion becomes austenite state. Initial conditions such that the temperature of the object to be analyzed 44 varies for each part may also be specified.

[0018] Information regarding the boundary conditions is, for example, the ambient temperature of the object to be analyzed 44 and the heat transfer coefficient between the object to be analyzed 44 and the surrounding substances. The ambient temperature is, for example, room temperature, water temperature, or oil temperature. When analyzing the situation where the object to be analyzed 44 is held by a jig or a table, etc., the temperature of the contact portion between the object to be analyzed 44 and the jig or the table, etc. is also the ambient temperature of the object to be analyzed 44. For example, when performing a simulation such as continuously carrying out quenching and tempering, a time-varying ambient temperature may be set for the boundary conditions.

[0019] The control unit 11 generates an analysis target model 45 by dividing the object to be analyzed 44 into multiple finite elements 451. Since the generation of the analysis target model 45 is commonly performed in simulations using the finite element method, a detailed explanation will be omitted.

[0020] The control unit 11 starts the heat conduction analysis simulation software 31 (see Figure 5) and the elastoplastic analysis simulation software 32 (see Figure 5) to perform a coupled analysis of the heat conduction analysis and elastoplastic analysis of the model 45 to be analyzed. The coupled analysis performed here is a strongly coupled analysis in which the two analyses are performed simultaneously. Note that the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 are not separate simulation software programs, but may be a single coupled analysis software that integrates the functions of both.

[0021] The control unit 11 calculates the temperature and deformation state for each finite element 451 that constitutes the model 45 under analysis by coupled analysis. The control unit 11 calculates the distribution of phase fractions by calculating the phase fraction of each finite element 451.

[0022] Phase fractions include, for example, austenite fraction, martensite fraction, and bainite fraction. Martensite and bainite are phases that are formed by cooling austenite. The method for calculating phase fractions will be described later.

[0023] The martensitic fraction of finite element 451 begins to increase when the temperature of finite element 451 falls below the martensitic transformation initiation temperature. The martensitic transformation initiation temperature varies depending on the cooling rate of finite element 451 and the phase fraction of finite element 451.

[0024] The bainite fraction of finite element 451 begins to increase when the temperature of finite element 451 falls below the bainite transformation initiation temperature. The bainite transformation initiation temperature varies depending on the cooling rate of finite element 451.

[0025] As the material cools, austenite is converted to martensite and bainite, so the austenite fraction of finite element 451 is calculated by equation (1). fγ = fγ0 - fM - fB ... (1) fγ is the austenite fraction. fγ0 is the austenite fraction at the start of cooling. fM is the martensite fraction. fB is the bainite fraction.

[0026] In general quenching simulations, fγ0 ≈ 1, so equation (1) can be approximated by equation (2). fγ = 1 - fM - fB ... (2)

[0027] Furthermore, in the stage before the start of martensitic transformation, fM in equations (1) and (2) can also be approximated as 0. In simulations under conditions where a non-austenite phase, such as martensite, ferrite, or pearlite, is present at a non-negligible level at the start of cooling, the aforementioned information on the initial state includes the distribution of phase fractions of the material being analyzed 44.

[0028] The state of the model 45 under analysis after a time interval Δt is calculated through a series of processes including coupled analysis of heat conduction and elastoplasticity, and calculation of the phase fraction. The control unit 11 repeatedly performs calculations at each time interval Δt to calculate the time-series change in the state of the model 45 under analysis. The time interval Δt is automatically determined by the software each time a calculation is performed.

[0029] The control unit 11 repeatedly performs calculations until, for example, the temperature of all finite elements 451 constituting the model 45 under analysis reaches room temperature. In this way, the control unit 11 can calculate the state of the object 44 after quenching is complete. The control unit 11 may also repeatedly perform calculations until some of the finite elements 451 constituting the model 45 under analysis reach room temperature.

[0030] Figure 2 is an explanatory diagram illustrating the continuous cooling transformation (CCT) of steel. Figure 3 is an enlarged view of part III in Figure 2. The horizontal axis represents the elapsed time after the start of cooling, and the vertical axis represents the temperature. In Figure 3, the magnification of the vertical axis is greater than that of the horizontal axis.

[0031] The four curves extending downwards from the point of high temperature (time 0) are cooling curves that represent the relationship between time and temperature when the cooling rate is constant. The further to the right the cooling curve is, the slower the cooling rate. Note that the cooling rate refers to the temperature increase per unit time.

[0032] In Figures 2 and 3, the line denoted by Ms is the transformation curve indicating the martensitic transformation initiation temperature at which the transformation begins when the temperature of the steel decreases. In the following explanation, the transformation initiation temperature from austenite to martensite will be referred to as the MS point, and the transformation curve denoted by Ms will be referred to as the transformation curve at the MS point.

[0033] Similarly, the line denoted by the sign Bs is a transformation curve that shows the bainite transformation onset temperature at which the bainite transformation begins when the temperature of the steel decreases. In the following explanation, the transformation onset temperature from austenite to bainite will be referred to as the BS point, and the transformation curve denoted by the sign Bs will be referred to as the transformation curve at the BS point.

[0034] As shown in Figures 2 and 3, the transformation curve at point BS branches off from the transformation curve at point MS. In the following explanation, the region below the transformation curve at point MS will be referred to as the martensitic transformation region, and the region between the transformation curves at point BS and point MS will be referred to as the bainite transformation region.

[0035] Figure 3 illustrates the behavior of steel when cooled. The leftmost cooling curve shows the fastest cooling rate among the four cooling curves. Austenitic steel begins its martensitic transformation at a temperature of just under 300°C.

[0036] The cooling curve on the far right represents the slowest cooling rate among the four cooling curves. Austenitic steel begins bainite transformation at a temperature of approximately 350°C. As cooling progresses, the bainite fraction increases and the austenite fraction decreases. Steel containing both austenite and bainite begins martensitic transformation at a temperature of approximately 220°C.

[0037] The second and third cooling curves from the right show the case where the cooling rate is intermediate between the rightmost and leftmost cooling curves. The slower the cooling rate, the higher the temperature at which the bainite transformation begins. Therefore, for example, when the temperature reaches just under 300°C, as shown by the dashed line, the bainite fraction is higher and the austenite fraction is lower compared to the leftmost cooling curve. In steels with a low austenite fraction, the martensitic transformation temperature decreases. Thus, the slower the cooling rate, the lower the martensitic transformation onset temperature.

[0038] Therefore, the martensitic transformation initiation temperature can be expressed as a function of the austenite fraction shown in equation (3). TM = f(fγ) ... (3) TM is the martensitic transformation onset temperature (°C). fγ is the austenite fraction. f() is a function.

[0039] Figure 4 is a graph showing the relationship between the austenite fraction and the martensitic transformation onset temperature. The horizontal axis shows the austenite fraction on a logarithmic scale. The rightmost point on the horizontal axis, "1," means that the austenite fraction is 100%. The leftmost point on the horizontal axis, "0.1," means that the austenite fraction is 10%. The vertical axis shows the martensitic transformation onset temperature, in degrees Celsius.

[0040] In the example shown in Figure 4, when the austenite fraction is expressed on a logarithmic scale, the relationship between the martensitic transformation onset temperature and the austenite fraction can be approximated by a straight line. This approximate straight line is shown in equation (4). TM = p × ln(fγ) + q ... (4) ln(fγ) is the natural logarithm of the austenite fraction. p is a constant that indicates the slope of the approximating line. q is a constant that represents the y-intercept of the approximation line.

[0041] Figure 4 and equation (4) show an example where the martensitic transformation initiation temperature TM can be calculated using a linear function with the natural logarithm of the austenite fraction fγ as the variable.

[0042] The graph illustrated in Figure 4 can be created by determining the relationship between the austenite fraction and the martensitic transformation onset temperature at various cooling rates through measurement or simulation. Note that the relationship between the austenite fraction and the martensitic transformation onset temperature differs depending on the steel composition. Therefore, the values ​​of p and q in equation (4) will differ depending on the steel composition. In the following explanation, we will use p = 45.45 and q = 298.69.

[0043] Furthermore, depending on the composition of the steel, the relationship between the martensitic transformation onset temperature and the austenite fraction may not be approximated by equation (4). In other words, the function f() shown in equation (3) is not limited to equation (4).

[0044] Figure 5 is an explanatory diagram illustrating the configuration of the information processing device 10. The information processing device 10 is used in the simulation of this embodiment. The information processing device 10 comprises a control unit 11, a main memory 12, an auxiliary memory 13, a communication unit 14, a display unit 15, an input unit 16, a reading unit 19, and a bus.

[0045] The control unit 11 is an arithmetic control device that executes the program of this embodiment. The control unit 11 uses one or more CPUs (Central Processing Units), GPUs (Graphics Processing Units), or multi-core CPUs, etc. The control unit 11 is connected to each hardware component of the information processing device 10 via a bus.

[0046] The main memory 12 is a storage device such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), or flash memory. The main memory 12 temporarily stores information necessary during processing performed by the control unit 11 and the program currently being executed by the control unit 11.

[0047] The auxiliary storage device 13 is a storage device such as SRAM, flash memory, hard disk, or magnetic tape. The auxiliary storage device 13 stores the program to be executed by the control unit 11, the heat conduction analysis simulation software 31, the elastoplastic analysis simulation software 32, and various data necessary for the execution of each software. The heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 may also be stored in an external mass storage device connected to the information processing device 10.

[0048] The communication unit 14 is an interface for communication between the information processing device 10 and the network. The display unit 15 is, for example, a liquid crystal display panel or an organic EL (Electro-Luminescence) panel. The input unit 16 is, for example, an input device such as a keyboard, mouse, or microphone. The display unit 15 and the input unit 16 may be stacked to form a touch panel.

[0049] The portable recording medium 96 is, for example, a USB (Universal Serial Bus) memory, a CD-ROM (Compact Disc Read-only memory), a magneto-optical disk medium, another optical disk medium, or an SD memory card. The program 97, which will be described later, is stored on the portable recording medium 96.

[0050] The reading unit 19 is an interface to which a portable recording medium 96, such as a USB connector, CD-ROM drive, or SD memory reader, can be connected. The semiconductor memory 98 stores the program 97 and is a memory that can be installed inside the information processing device 10.

[0051] The information processing device 10 is a general-purpose personal computer, tablet, mainframe computer, virtual machine running on a mainframe computer, or quantum computer. The information processing device 10 may also be composed of multiple personal computers or mainframe computers that perform distributed processing. The information processing device 10 may also be composed of a cloud computing system. The information processing device 10 may also be composed of multiple personal computers or mainframe computers that operate in cooperation with each other.

[0052] Program 97 is recorded on a portable recording medium 96. The control unit 11 reads Program 97 via the reading unit 19 and saves it to the auxiliary storage device 13. The control unit 11 may also read Program 97 stored in the semiconductor memory 98. Furthermore, the control unit 11 may download Program 97 from another server computer (not shown) connected via the communication unit 14 and a network (not shown) and save it to the auxiliary storage device 13.

[0053] Program 97 is installed as a control program for the information processing device 10, loaded into the main memory 12, and executed. Program 97 in this embodiment is an example of a program product.

[0054] The heat conduction analysis simulation software 31 is software that simulates the heat conduction behavior when the temperature of the object being analyzed 44 differs from the ambient temperature, using numerical analysis methods such as the finite element method. The elastoplastic analysis simulation software 32 is software that simulates the elastic deformation behavior and plastic deformation behavior when the temperature of the object being analyzed 44 is not uniform, using numerical analysis methods such as the finite element method. The heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 operate simultaneously to perform coupled analysis.

[0055] As mentioned above, the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 are not separate simulation software programs, but rather a single coupled analysis software that integrates the functions of both. However, for the sake of explanation, the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 will be described separately below.

[0056] The heat conduction analysis simulation software 31 of this embodiment includes a so-called mesh generation function that generates an analysis target model 45 by dividing the object to be analyzed 44 into a plurality of finite elements 451. The mesh generation function may be implemented by a separate program that operates in conjunction with the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32.

[0057] The heat conduction analysis simulation software 31 accepts input parameters and outputs output parameters that show the heat conduction analysis results after a time width Δt has elapsed. Table 1 shows examples of input and output parameters for the heat conduction analysis simulation software 31. The output parameters of the heat conduction analysis simulation software 31 are examples of heat conduction analysis results.

[0058] [Table 1]

[0059] In the following explanation, we will use as an example the case where the element division of the object to be analyzed 44 when the heat conduction analysis simulation software 31 is run for the first time is used consistently in subsequent processing.

[0060] Table 2 shows examples of input and output parameters for the elastoplastic analysis simulation software 32. The output parameters of the elastoplastic analysis simulation software 32 are examples of elastoplastic analysis results. The elastoplastic analysis simulation software 32 accepts input parameters and outputs output parameters at the same time point.

[0061] Table 2 shows examples of input and output parameters for the elastoplastic analysis simulation software 32. The output parameters of the elastoplastic analysis simulation software 32 are examples of elastoplastic analysis results.

[0062] [Table 2]

[0063] Since the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 are both publicly known, a detailed explanation of their processing is omitted. Since the coupling of these two simulation software programs is also publicly known, a detailed explanation of their processing is omitted.

[0064] The heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 may be provided in the form of SaaS (Software as a Service) via a large computer or cloud service connected to the information processing device 10 via a network.

[0065] Returning to Figure 1, let's continue the explanation. The martensite fraction is calculated using the Koistinen-Marburger equation (5). fM=1-exp(a×(T-TM)) ‥‥‥(5) fM is the martensite fraction. T is the temperature. a and TM are phase transformation parameters related to martensitic transformation. In the following explanation, 'a' will be set to 0.025.

[0066] TM, one of the phase transformation parameters, is the martensitic transformation initiation temperature and is calculated using equation (4) above. The temperature T is calculated using the heat conduction analysis simulation software 31.

[0067] The bainite fraction is calculated using equation (6), which is the Johnson-Mehl-Avrami-Kolmogorov formula. fB = 1 - exp(-b*t^n) ... (6) fB is the bainite fraction. t is time. b and n are phase transformation parameters related to the bainite transformation.

[0068] The phase transformation parameters for bainite transformation can be calculated, for example, using a dilatometry curve created by measuring the relationship between the temperature and deformation of the steel. Since the method for creating the dilatometry curve and the method for calculating the phase transformation parameters for bainite transformation are well known, a detailed explanation is omitted. The phase transformation parameters calculated for various conditions such as the temperature and composition of the steel may be recorded in the auxiliary storage device 13.

[0069] Constants may be used as phase transformation parameters for the bainite transformation, such as b=0.24E-5 and n=2.

[0070] Figure 6 is a flowchart illustrating the program's processing flow. The program in Figure 6 simulates the state of a steel object 44, which has been heated to its quenching temperature, when it cools to room temperature.

[0071] The control unit 11 acquires the calculation conditions (step S501). The calculation conditions include information about the shape of the object to be analyzed 44, information about the physical properties of the materials constituting the object to be analyzed 44, information about the initial state of the object to be analyzed 44, and information about the boundary conditions of the object to be analyzed 44. The calculation conditions are supplied, for example, by a text file in which data is recorded according to a predetermined format. The calculation conditions may also be entered by the user via the input unit 16 each time the program is executed.

[0072] The control unit 11 performs a coupled analysis using the heat conduction analysis simulation software 31 and the elastoplastic analysis simulation software 32 (step S502). During this coupled analysis, the control unit 11 automatically determines the time width Δt. The input and output parameters for step S502 are as described using Tables 1 and 2.

[0073] The control unit 11 starts a phase fraction calculation subroutine (step S503). The phase fraction calculation subroutine calculates the phase fraction in each finite element 451 that constitutes the model 45 under analysis, that is, the phase fraction distribution in the model 45 under analysis. The processing flow of the phase fraction calculation subroutine will be described later.

[0074] The control unit 11 temporarily stores the data calculated in steps S502 and S503 in the auxiliary storage device 13 or the main storage device 12 (step S504).

[0075] The control unit 11 determines whether or not to terminate the iterative calculation process (step S505). The control unit 11 determines to terminate the iterative calculation process when the cooling of the object to be analyzed 44 is complete. Specifically, the control unit 11 determines to terminate the process, for example, when the temperature of the object to be analyzed 44 obtained in step S502 falls below room temperature.

[0076] In either case, the temperature used for the determination is the temperature of all or some of the finite elements 451 that constitute the model 45 under analysis. Specific examples of conditions for terminating the process include "the temperature of all finite elements 451 constituting the object 44 under analysis is 50°C or lower," or "the temperature of some of the finite elements 451 constituting the object 44 under analysis is 30°C or lower." Here, "some of the finite elements 451" may be defined by a ratio or number, such as "10 percent of the finite elements 451" or "50 finite elements 451."

[0077] The control unit 11 may determine to terminate the process if the calculation time obtained by accumulating the time width Δt in each repeating loop exceeds a predetermined value. The control unit 11 may also determine to terminate the process if the number of executions of step S505 exceeds a predetermined value.

[0078] If it is determined that the process will not terminate (NO in step S505), the control unit 11 returns to step S502 and obtains output parameters indicating the coupled analysis results after a time width Δt has elapsed since the previous step S502. As described above, for each loop from step S502 to step S505, the state change of the object being analyzed 44 over time with a time width Δt is calculated and recorded.

[0079] If it is determined that the process is finished (YES in step S505), the control unit 11 outputs the calculated data (step S506). For example, the control unit 11 accepts the user's specification of the output destination and output format, and outputs the data in the specified format. Specific examples of the output data will be described later. Alternatively, instead of executing step S506, the control unit 11 may output the data to the user-specified output destination and in the user-specified output format each time step S504 is executed. After that, the control unit 11 terminates the process.

[0080] The control unit 11 does not need to reuse the element division performed in the initial step S502 in subsequent processing. For example, the control unit 11 may perform a new element division each time the process is repeated. For instance, if the object 44 underwent significant plastic deformation, a new element division can be performed to enable a highly accurate simulation.

[0081] Figure 7 is a flowchart illustrating the processing flow of the phase fraction calculation subroutine. The phase fraction calculation subroutine calculates the phase fraction in each finite element 451 that constitutes the model 45 under analysis, i.e., the phase fraction distribution in the model 45 under analysis.

[0082] The control unit 11 extracts information about one finite element 451 (step S521). The information to be extracted is, for example, the temperature calculated in the previous step S502.

[0083] The control unit 11 obtains the phase transformation parameters b and n related to the bainite transformation (step S522). The control unit 11 calculates the bainite fraction fB based on equation (6) (step S523). If the bainite transformation has not yet started, the bainite fraction fB calculated in step S523 will be the same as the value in the previous loop.

[0084] The control unit 11 substitutes the bainite fraction fB calculated in step S523 into equation (2) to calculate the austenite fraction fγ. As mentioned above, for finite elements 451 before the start of martensitic transformation, the martensitic fraction fM can be approximated as 0. For finite elements 451 after the start of martensitic transformation, the control unit 11 uses the martensitic fraction fM calculated in the previous loop.

[0085] The control unit 11 calculates the martensitic transformation start temperature TM, which is a phase transformation parameter related to martensitic transformation, based on equation (4) (step S524). The control unit 11 calculates the martensitic fraction fM based on equation (5) (step S525). If martensitic transformation has not yet started, the martensitic fraction fM calculated in step S524 will be the same value as the value in the previous loop.

[0086] The control unit 11 determines whether or not it has finished processing all finite elements 451 that constitute the model 45 under analysis (step S526). If it determines that it has not finished (NO in step S526), ​​the control unit 11 returns to step S521. If it determines that it has finished (YES in step S526), ​​the control unit 11 terminates the processing.

[0087] According to this embodiment, a program for performing the coupled analysis described using Figure 1 can be provided. [Examples]

[0088] The following describes a calculation example using the program explained with reference to Figures 6 and 7. The object of analysis 44 is a cubic steel ingot with sides of 500 mm. The simulation was performed for the case where the entire steel ingot is heated to 1030°C and then air-cooled in an atmosphere of 20°C. In the following description, the simulation results using the program of this embodiment will be referred to as the example.

[0089] In the following explanation, the comparative example shows the simulation results when the martensitic transformation initiation temperature is constant and independent of the austenite phase fraction. Specifically, in step S524 of the phase fraction calculation subroutine explained using Figure 7, the comparative example used a constant value of 296.00 for the martensitic transformation initiation temperature TM, which is a phase transformation parameter.

[0090] Figure 8 is an explanatory diagram illustrating the analysis model 45. To reduce computational complexity, the analysis model 45 is used, which models the parts obtained by cutting the object 44 into halves in each direction (length, width, and height). As mentioned above, the analysis model 45 is composed of multiple finite elements 451. The analysis model 45 includes corners 41 corresponding to the corners of the object 44 and a core 42 corresponding to the center of the object 44.

[0091] Figure 9 is a graph illustrating the simulation results regarding temperature change. The horizontal axis in Figure 9 represents the elapsed time since the start of cooling, and the unit of the horizontal axis is minutes. The vertical axis in Figure 9 represents temperature, and the unit of the vertical axis is °C. The solid line shows the temperature of the finite element 451 including the core 42. The dashed line shows the temperature of the finite element 451 including the corner 41.

[0092] As expected, the temperature of the corner portion 41 decreases rapidly after cooling begins, while the temperature of the core portion 42 decreases slowly. After 280 minutes from the start of cooling, the temperature of the core portion 42 is approximately 40°C, and the temperature of the corner portion 41 is approximately 25°C.

[0093] Figure 10 is a graph showing the simulation results regarding the phase fraction change in the core 42. The horizontal axis of Figure 10 represents temperature, and the unit of the horizontal axis is °C. The vertical axis of Figure 10 represents the phase fraction, and the unit is dimensionless.

[0094] The thick solid line shows the martensite fraction of the finite element 451 including the core 42. The thick dashed line shows the bainite fraction of the finite element 451 including the core 42. The thin solid line shows a comparative example of the martensite fraction of the finite element 451 including the core 42. The thin dashed line shows a comparative example of the bainite fraction of the finite element 451 including the core 42.

[0095] As mentioned above, the initial temperature of the finite element 451, including the core 42, was 1030°C, and simulations were performed until the temperature dropped to approximately 40°C. Figure 10 shows the range from 300°C to 200°C.

[0096] According to Figure 10, the bainite fraction at the point when the temperature drops to 300°C is approximately 0.5 for both the example and the comparative example. Therefore, as explained in equation (2), the austenite fraction is also approximately 0.5.

[0097] In the comparative example, the phenomenon described using Figure 3, where the decrease in austenite fraction leads to a decrease in the martensitic transformation initiation temperature, is not simulated. Therefore, when the temperature falls below 296°C, the martensitic fraction increases. While the martensitic fraction is increasing, the bainite fraction remains constant.

[0098] In the examples, the phenomenon of a decrease in the austenite fraction leading to a decrease in the martensitic transformation initiation temperature is simulated, with the martensitic fraction increasing after the temperature falls below 250°C. While the martensitic fraction is increasing, the bainite fraction remains constant.

[0099] Figure 11 is a graph showing the simulation results regarding the change in phase fraction at corner 41. The vertical and horizontal axes are the same as in Figure 10, so their explanation is omitted.

[0100] The thick solid line shows the martensite fraction of finite element 451 including corner 41. The thick dashed line shows the bainite fraction of finite element 451 including corner 41. The thin solid line shows a comparative example of the martensite fraction of finite element 451 including corner 41. The thin dashed line shows a comparative example of the bainite fraction of finite element 451 including corner 41.

[0101] According to Figure 11, the bainite fraction at 300°C is approximately 0.1 for both the example and the comparative example. Therefore, as explained in equation (2), the austenite fraction is approximately 0.9. The phenomenon of a lower bainite fraction at 300°C compared to Figure 10 reflects the phenomenon explained using Figure 3, where a faster cooling rate results in a lower bainite transformation onset temperature.

[0102] In the comparative example, the martensite fraction increases when the temperature falls below 296°C. While the martensite fraction increases, the bainite fraction remains constant. In the example, the martensite fraction increases after the temperature reaches approximately 290°C. While the martensite fraction increases, the bainite fraction remains constant.

[0103] Figure 12 is a graph showing the simulation results regarding the change in the martensite phase fraction in the core 42 and corner 41. The vertical and horizontal axes are the same as in Figure 10, so their explanation is omitted.

[0104] The thick solid line shows the martensite fraction of the finite element 451 including the core 42. The thick dashed line shows the martensite fraction of the finite element 451 including the corner 41. The thin solid line shows a comparative example of the martensite fraction of the finite element 451 including the core 42. The thin dashed line shows a comparative example of the martensite fraction of the finite element 451 including the corner 41.

[0105] In the comparative example, the martensitic transformation initiation temperature is fixed at 296°C. Therefore, the martensite fraction increases from 296°C in both the core portion 42 and the corner portion 41. In the example, the phenomenon in which the martensite fraction in the core portion 42 is lower than that in the corner portion 41 is simulated because the martensite transformation initiation temperature decreases due to the increase in the austenite fraction.

[0106] According to this embodiment, it is possible to perform simulations that reflect fluctuations in the martensitic transformation onset temperature. Therefore, even for an object 44 that is analyzed, such as a die-casting mold, where the cooling temperature differs from part to part, accurate simulations can be performed, contributing to the improvement of the quality of the quenching process.

[0107] The program is an example of a program product. The program may be provided on a recording medium or distributed from an external computer. Computer programs can be deployed to run on a single computer, at a single site, or distributed across multiple sites and interconnected by a communication network.

[0108] The technical features (constituent elements) described in each embodiment are combinable with each other, and by combining them, new technical features can be formed. The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims, not in the sense described above, and all modifications within the sense and scope equivalent to the claims are intended to be included.

[0109] The independent and dependent claims described in the claims can be combined with each other in any combination, regardless of the form of reference. Furthermore, while the claims use a multi-claim format in which claims refer to two or more other claims (multi-claim format), this is not the only option. Claims may also be described using a multi-claim format in which at least one multi-claim is referenced (multi-multi-claim format). [Explanation of Symbols]

[0110] 10 Information Processing Devices 11 Control Unit 12 Main storage 13 Auxiliary storage device 14 Communications Department 15 Display section 16 Input section 19 Reading section 31. Thermal Conduction Analysis Simulation Software 32. Elastoplastic Analysis Simulation Software 41 Corner 42 Core 44. Objects to be analyzed 45 Models to be analyzed 451 Finite Element 96 Portable recording media 97 Programs 98 Semiconductor memory

Claims

1. Obtain information regarding the shape of the object to be analyzed, The physical properties of the steel constituting the object to be analyzed are obtained at each phase and temperature. Information is obtained regarding the initial state of the object to be analyzed after heating. After a time interval of Δt has elapsed The results of the coupled analysis of the thermal conduction analysis and elastoplastic analysis of the object to be analyzed are obtained. Based on the results of the coupled analysis, the bainite fraction of the object being analyzed is calculated. Based on the bainite fraction, the austenite fraction of the object to be analyzed is calculated. Based on the austenite fraction, the martensitic transformation initiation temperature of the material to be analyzed is calculated. Based on the martensite transformation onset temperature, the martensite fraction of the material to be analyzed is calculated. The process is repeated to calculate the state of the object being analyzed at the end of its cooling. An information processing method in which a computer performs the processing.

2. The martensitic transformation initiation temperature is calculated using a function with respect to the austenite fraction. The information processing method according to claim 1.

3. The aforementioned physical properties include density, thermal conductivity, specific heat, Young's modulus, Poisson's ratio, deformation resistance, coefficient of linear expansion, and phase transformation parameters. The information regarding the initial state includes the temperature of the object being analyzed and the ambient temperature. The information processing method according to claim 1.

4. For each of the multiple finite elements obtained by dividing the object to be analyzed, the martensitic transformation onset temperature is determined. The information processing method according to any one of claims 1 to 3.

5. Obtain information regarding the shape of the object to be analyzed, The physical properties of the steel constituting the object to be analyzed are obtained at each phase and temperature. Information is obtained regarding the initial state of the object to be analyzed after heating. After a time interval of Δt has elapsed The results of the coupled analysis of the thermal conduction analysis and elastoplastic analysis of the object to be analyzed are obtained. Based on the results of the coupled analysis, the bainite fraction of the object being analyzed is calculated. Based on the bainite fraction, the austenite fraction of the object to be analyzed is calculated. Based on the austenite fraction mentioned above, the martensitic transformation initiation temperature of the material to be analyzed is calculated. Based on the martensite transformation onset temperature, the martensite fraction of the material to be analyzed is calculated. The process is repeated to calculate the state of the object being analyzed at the end of its cooling. A program that instructs a computer to perform a process.

6. An information processing device comprising a control unit, The control unit, Obtain information regarding the shape of the object to be analyzed, The physical properties of the steel constituting the object to be analyzed are obtained at each phase and temperature. Information is obtained regarding the initial state of the object to be analyzed after heating. After a time interval of Δt has elapsed The results of the coupled analysis of the thermal conduction analysis and elastoplastic analysis of the object to be analyzed are obtained. Based on the results of the coupled analysis, the bainite fraction of the object being analyzed is calculated. Based on the bainite fraction, the austenite fraction of the object to be analyzed is calculated. Based on the austenite fraction mentioned above, the martensitic transformation initiation temperature of the material to be analyzed is calculated. Based on the martensite transformation onset temperature, the martensite fraction of the material to be analyzed is calculated. The process is repeated to calculate the state of the object being analyzed at the end of its cooling. Information processing device.

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