Analysis method of carbon concentration distribution

Abstract

To enhance analysis accuracy of a carbon concentration distribution.SOLUTION: A distribution of a carbon concentration is analyzed based on a diffusion equation with a driving force of a carbon concentration gradient in a steel material. A carbide is formed in the steel material by carburization treatment. The diffusion equation is represented by an equation (I) and an equation (II) described in Claim 1, where D in the equation (I) is calculated from an equation (III) described in Claim 1 or an equation (IV) below. Furthermore, a parameter (in other words, a diffusion flow rate, a diffusion coefficient, a mobility included in the diffusion equation) used in a calculation of a diffusion coefficient in the steel material and a diffusion simulation is corrected with a correction coefficient.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for analyzing the carbon concentration distribution in a carburized steel material. [Background technology]

[0002] In the case of steel products (for example, drive system products such as gears), carburizing is performed on the products processed into the desired shape in order to ensure the necessary properties such as wear resistance, fatigue strength, etc. of the product surface. In recent years, reduced pressure carburizing, typified by reduced pressure carburizing, has become widespread from the viewpoint of reducing the environmental load.

[0003] In reduced pressure carburizing, the workpiece is heated at a certain temperature for a certain time in an atmosphere in which carburizing gas containing carbon is injected under reduced pressure after the gas has been evacuated in a heating furnace, and then the workpiece is cooled by immersing it in a cooling medium such as oil. This reduced pressure carburizing process has a carburizing period during which the injection of carburizing gas continues, and a diffusion period during which the injection of carburizing gas is stopped.

[0004] In the reduced pressure carburization process, if too much carbon penetrates into the surface layer of the product and the carbon does not sufficiently diffuse further inside than the surface layer, coarse carbides are formed, which may reduce the fatigue strength and other properties of the product. In order to avoid such problems, the following techniques have been disclosed.

[0005] In Patent Document 1, a carburizing pattern is set, and the carbon concentration of any cell in the surface layer of the target part is calculated using a diffusion equation.Then, the set carburizing conditions are evaluated and pass / fail is determined by comparing the calculated carbon concentration with a desired carbon concentration.

[0006] Patent Document 2 describes a reduced pressure carburizing process method capable of suppressing the carburizing variation of carburized parts. The carburizing process has an early carburizing process from the start of the carburizing process to the crossover time te, and a later carburizing process from the crossover time te to the carburizing time ta. In the early carburizing process, the actual carburizing gas flow rate is set to be equal to or greater than the theoretical carburizing gas flow rate at the reference time ta / 5 from the start of the carburizing process, and equal to or less than the theoretical carburizing gas flow rate at the 20 second point from the start of the carburizing process. In the later carburizing process, the actual carburizing gas flow rate is set to be within the range of 1.00 to 1.20 times the theoretical carburizing gas flow rate. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2008-208403 A [Patent Document 2] Patent No. 6583600 [Non-patent literature]

[0008] [Non-Patent Document 1] Effect of excess carburization of edge on fatigue strength in vacuum carburizing, Iron and Steel, Iron and Steel Institute of Japan, 2010, Vol.96, No.6, pp.48-53 Summary of the Invention [Problem to be solved by the invention]

[0009] In Patent Document 1, the carbon concentration distribution is analyzed by using the diffusion coefficient included in the diffusion equation as a constant. However, strictly speaking, the diffusion coefficient is a value that changes depending on the carbon concentration in γ, so the analysis precision of the carbon concentration distribution is low. Patent Document 2 sets the conditions for reduced pressure carburization treatment in order to suppress the carburization variation of carburized parts, but does not analyze the distribution of carbon concentration in steel material that undergoes reduced pressure carburization treatment. An object of the present invention is to improve the accuracy of analysis of carbon concentration distribution. [Means for solving the problem]

[0010] In order to solve the above problems, the present invention provides a method for analyzing carbon concentration distribution, (1) a method for analyzing carbon concentration distribution in a carburized steel material by using a diffusion equation, wherein carbides are formed in the steel material by the carburization treatment, the diffusion equation is represented by the following formula (I) and formula (II), and D in the following formula (I) is calculated from the following formula (III) or the following formula (IV).

number

[0011] (2) In the above configuration (1), the following may be set: In the carbide precipitation region in the steel material formed by the carburizing treatment, the diffusion coefficient D of the formula (I), the diffusion flux J of the formula (II), the diffusion coefficient D of the formula (III) γ , the mobility m of formula (IV) γ at least one of the above may be multiplied by a correction coefficient, and the correction coefficient may be set so as to satisfy a condition that an error between the carbon concentration distribution analyzed from the diffusion equation and the carbon concentration distribution measured in advance is equal to or smaller than a threshold value.

[0012] (3) In the above configuration (1) or (2), when D in formula (I) is calculated from formula (III), the right-hand side of any of formulas (I), (II), and (III) may be multiplied by the labyrinth degree λ represented by the following formula (V), and when D in formula (I) is calculated from formula (IV), the right-hand side of any of formulas (I), (II), and (IV) may be multiplied by the labyrinth degree λ represented by the following formula (V). λ=V γ n (V) V γ is the volume fraction of austenite [-], and n is an integer. Effect of the Invention

[0013] According to the present invention, even in steel materials that contain a multi-phase region of austenite and carbide during carburization (e.g., reduced pressure carburization, high concentration carburization, etc.), the carbon concentration distribution can be analyzed with high accuracy based on a diffusion equation using the carbon concentration gradient in the steel material as a driving force. Furthermore, by correcting the parameters used in the calculation of the diffusion coefficient in steel and the diffusion simulation (in other words, the diffusion flow rate, diffusion coefficient, and mobility included in the diffusion equation) with a correction coefficient, it becomes easier to ensure accuracy when analyzing the carbon concentration in steel that has been carburized. [Brief description of the drawings]

[0014] [Figure 1] 10 is a flowchart illustrating a method for correcting a diffusion simulation that analyzes a carbon concentration in a steel material. [Diagram 2] FIG. 1 is a perspective view of a steel sample. [Diagram 3] FIG. 1 is a cross-sectional view of a steel sample. [Figure 4] FIG. 1 is a diagram showing the relationship between the analytical results and the actual measured values ​​in Examples 1 and 2 and Comparative Examples 1 and 2, regarding the carbon concentration as a function of the depth from the steel material surface. [Diagram 5] FIG. 1 is a diagram showing the relationship between the analytical results and the actual measured values ​​in Examples 3-4 and Comparative Examples 3-4, regarding the carbon concentration as a function of the depth from the steel material surface. [Figure 6] FIG. 11 is a diagram showing the relationship between the analysis results in Example 5 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel material surface. [Figure 7] FIG. 13 is a diagram showing the relationship between the analysis results in Example 6 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel material surface. [Figure 8] FIG. 13 is a diagram showing the relationship between the analysis results in Example 7 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel material surface. [Figure 9] FIG. 13 is a diagram showing the relationship between the analysis results in Example 8 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel material surface. [Figure 10] FIG. 13 is a diagram showing the relationship between the analysis results of Example 9 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 11] FIG. 13 is a diagram showing the relationship between the analysis results of Example 10 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel surface. [Figure 12] FIG. 11 is a diagram showing the relationship between the analysis results in Example 11 and the actual measured values ​​for the carbon concentration as a function of the depth from the steel material surface. [Figure 13] FIG. 13 is a diagram showing the relationship between the analysis results of Example 12 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 14] FIG. 13 is a diagram showing the relationship between the analysis results in Example 13 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 15] FIG. 13 is a diagram showing the relationship between the analysis results in Example 14 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 16] FIG. 13 is a diagram showing the relationship between the analysis results in Example 15 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 17] FIG. 13 is a diagram showing the relationship between the analysis results of Example 16 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 18] FIG. 13 is a diagram showing the relationship between the analysis results in Example 17 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 19]FIG. 13 is a diagram showing the relationship between the analysis results of Example 18 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 20] FIG. 13 is a diagram showing the relationship between the analysis results of Example 19 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 21] FIG. 23 is a graph showing the relationship between the analysis results of Example 20 and the actual measured values ​​for the carbon concentration depending on the depth from the steel surface. [Figure 22] FIG. 23 is a diagram showing the relationship between the analysis results of Example 21 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Diagram 23] FIG. 23 is a diagram showing the relationship between the analysis results of Example 22 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Figure 24] FIG. 23 is a graph showing the relationship between the analysis results of Example 23 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. [Diagram 25] FIG. 23 is a diagram showing the relationship between the analysis results of Example 24 and the actual measured values ​​for the carbon concentration depending on the depth from the steel material surface. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] (First embodiment) The distribution of carbon concentration inside the steel material when carburizing treatment is performed can be analyzed based on the diffusion simulation (diffusion equation based on the carbon concentration gradient in the steel material) and the calculation of the diffusion coefficient, which will be described later. (Diffusion simulation based on the diffusion equation) In carburizing, carbon diffuses through the steel material, and Fick's law holds true. In this case, the carbon diffusion flux J is expressed by the diffusion equation (1) below, and the change in carbon concentration over time (∂C / ∂t) is expressed by the diffusion equation (2) below.

number

[0016] (Diffusion simulation when carbide is formed) Carbide is formed during carburizing in high-concentration carburizing, where carbides are formed by controlling the carbon potential in the atmospheric gas high, and in the above-mentioned reduced-pressure carburizing. In this case, in order to calculate the carbon diffusion flux based on formula (1), the carbon diffusion coefficient corresponding to the multi-phase region of austenite and carbide is required, and this diffusion coefficient changes greatly depending on the carbon concentration, which changes depending on the carburizing state, and the concentration of solute C in austenite and the amount of carbide formed, which differ depending on the steel composition other than carbon. In this case, in order to improve the accuracy of the analysis, it is necessary to derive the diffusion coefficient at different carbon concentrations and temperatures for each steel type and set this in the simulation. For example, a method of deriving the diffusion coefficient only through experiments, such as the decarburization method, is not realistic because it requires an excessive number of experiments. Therefore, the present inventors discovered a method for calculating the diffusion coefficient in a steel material including a multi-phase region using the diffusion coefficient and mobility of carbon in austenite, as described below, and calculating the diffusion flux of carbon based on formula (1).

[0017] (Calculation of the diffusion coefficient in the multi-phase region using the diffusion coefficient in austenite) Even in the case of a steel material containing a multi-phase region including austenite and carbides, the carbon diffusion flux can be calculated based on equation (1) by calculating the diffusion coefficient D in the steel material using equation (3).

number

[0018] (Calculation of the diffusion coefficient in the multiphase region using the mobility in austenite) Even for a target that includes a multi-phase region containing austenite and carbides, the carbon diffusion flux can be calculated based on equation (1) by calculating the diffusion coefficient in the steel using equation (4).

number

[0019] (Diffusion simulation using thermodynamic calculations) The details will be described later, but the parameters included in formulas (3) and (4) can be obtained by the following method. The carbon concentration Cγ and the carbon activity coefficient γ in austenite included in formulas (3) and (4) γ may be obtained by thermodynamic calculation. The diffusion coefficient Dγ in formula (3) may be obtained from a numerical value obtained in advance by an experiment using the steel material to be carburized, or from data reported as experimental data. The mobility of carbon in austenite m γ may be obtained by thermodynamic calculation using a thermodynamic database and a diffusion database. The carbon concentration C included in the formulas (3) and (4) is a value obtained over time by a diffusion simulation.

[0020] (Labyrinth Level Setting) In the calculation of the diffusion coefficient in steel using the above formulas (3) and (4), it is assumed that the austenite single phase is continuous. Therefore, when the steel contains a multi-phase region containing austenite and carbide, in order to make the analysis more precise, the labyrinth factor λ (where λ ≠ 1) shown in the following formula (5) may be multiplied by the right-hand side of formulas (3) and (4) in the multi-phase region to calculate the diffusion coefficient D of carbon in the steel. Since "it may be calculated (omitted) in order to make the analysis more precise," it is not necessary to multiply by the labyrinth factor λ. In the single-phase region, λ = 1. It is mathematically self-evident that the right side of equation (1) may be multiplied by the labyrinth degree λ without multiplying the right side of equation (3) or equation (4) by the labyrinth degree λ. Moreover, instead of multiplying the right side of the formula (3) or (4) by the labyrinth degree λ, the right side of the formula (2) may be multiplied by the labyrinth degree λ.

number

[0021] (Calculation method for diffusion simulation) Mesh data is created in which the surface layer of the steel material to be carburized is divided into a number of cells. The size of each cell can be set appropriately, for example, to 1 to 500 μm. The size of the cells can be uniform, or can be gradually increased from the surface of the steel material toward the inside (in other words, gradually decreased from the inside of the steel material toward the surface). The type of mesh elements is not particularly limited, but can be appropriately selected from triangles and quadrangles in two dimensions, and tetrahedrons and hexahedrons in three dimensions. Either primary or secondary elements can be used.

[0022] When targeting a part or shape where carbon diffuses in one dimension during carburizing (e.g., a flat part), it may be modeled in one dimension. When the shape of the steel material is a round bar or a cylinder, it can be treated as one dimension by making the mesh data into a cylindrical coordinate system. When dealing with steel materials in which carbon diffuses in two or three dimensions during carburizing (e.g. steel materials with edge-shaped parts), two or three-dimensional modeling is required. When dealing with steel materials with axially symmetric shapes such as notched round bar test pieces, mesh data may be treated as two-dimensional by using a cylindrical coordinate system. The analysis time (step time) of the diffusion simulation is not particularly limited, but can be set to, for example, 0.001 to 1.0 seconds.

[0023] It is assumed that the steel surface is in equilibrium with graphite during the carburizing stage of reduced pressure carburizing. Therefore, based on the chemical composition excluding carbon of the steel to be carburized, the equilibrium phase and equilibrium composition in equilibrium with graphite at the carburizing temperature are determined by well-known thermodynamic calculations. The carbon concentration in the steel, the solute C concentration in austenite, the volume fraction of austenite, and the activity coefficient of carbon in austenite can be determined from the equilibrium phase and equilibrium composition determined by thermodynamic calculations.

[0024] On the other hand, periods when carbon does not penetrate from the steel surface, such as the diffusion period of reduced pressure carburizing, are considered to be closed systems. Cementite (θ) may precipitate on the surface or inside of steel material due to carburizing treatment. In this case, carbon in the steel material is distributed between cementite and austenite. Therefore, the equilibrium phase and equilibrium composition in the steel material at the temperature and chemical composition at that position can be obtained by the above-mentioned thermodynamic calculation, and the solute C concentration in austenite, the volume fraction of austenite, and the activity coefficient of carbon in austenite can be specified.

[0025] Diffusion coefficient D of carbon in austenite of steel γ The mobility of carbon in austenite in steel may be determined by a numerical value obtained in advance through an experiment using the steel to be carburized, or may be data reported as experimental data. γ can be obtained, for example, from a thermodynamic calculation using a thermodynamic database and a diffusion database. The diffusion coefficient in austenite, D γ is required to calculate the diffusion coefficient D in steel from equation (3). For example, the diffusion coefficient D of carbon in austenite γ As the above, the following formula (6) shown in Non-Patent Document 1 may be used.

number

[0026] Numerical analysis methods for carrying out a simulation based on a diffusion equation include, but are not limited to, a finite difference method, a finite element method, a finite volume method, and the like.

[0027] Second embodiment In this embodiment, the formulas (1) to (4) described in the first embodiment are corrected to perform a diffusion simulation, which makes it easier to ensure accuracy when analyzing the carbon concentration in a steel material that has been subjected to a carburizing treatment. Hereinafter, a method for correcting the diffusion simulation will be described with reference to the flowchart in FIG.

[0028] In step S101, the distribution of carbon concentration inside the steel material when carburizing treatment (e.g., reduced pressure carburizing treatment) is performed is analyzed based on the diffusion simulation. The distribution of carbon concentration can be analyzed by applying the carburizing treatment conditions (temperature and time) to the diffusion simulation.

[0029] In step S102, after the steel material is subjected to a carburizing treatment, the distribution of the carbon concentration inside the steel material is measured. The steel material used in the treatment in step S102 is the same as the steel material used in the treatment in step S101, and the carburizing treatment conditions used in the treatment in step S102 are the same as the carburizing treatment conditions used in the treatment in step S101. As the carburizing gas used in the carburizing treatment, for example, acetylene can be used. As a method for measuring the carbon concentration, a known measuring method can be appropriately adopted, and for example, the distribution of the carbon concentration in the steel material can be measured using an electron probe microanalyzer (EPMA).

[0030] The order in which the processes in steps S101 and S102 are performed is not particularly limited.

[0031] In step S103, a correction coefficient k[-] for correcting the diffusion simulation used in the processing of step S101 is determined so that the error Ec between the carbon concentration distribution analyzed in the processing of step S101 and the carbon concentration distribution measured in the processing of step S102 is equal to or smaller than a threshold value Eth.

[0032] As the error Ec, for example, the mean absolute error (MAE) or the mean square error (MSE) can be used. The threshold value Eth can be set appropriately taking into consideration the analytical accuracy of the carbon concentration when the correction coefficient k is not set. Here, the smaller the threshold value Eth, the more the analytical accuracy of the carbon concentration can be improved. For example, when an edge-shaped steel material is to be analyzed, the analytical accuracy can be improved by setting the threshold value Eth to 18% or less. Moreover, the threshold value Eth is preferably 15% or less, and more preferably 13% or less.

[0033] As described above, the diffusion equation (corresponding to equations (1) and (2)) used in the diffusion simulation and the calculation formula for the diffusion coefficient D in steel (corresponding to equations (3) and (4)) contain the diffusion flow rate J of carbon, the diffusion coefficient D, Dγ, and the mobility m γ The diffusion simulation can be corrected by multiplying at least one of these parameters by a correction coefficient k. The correction coefficient k is a value greater than 0 and less than 1. It goes without saying that the correction coefficient k is set in the carbide precipitation region in the steel material formed by the carburizing process.

[0034] After arbitrarily setting the correction coefficient k, the carbon concentration is analyzed based on the diffusion simulation to obtain the error Ec. If this error Ec is equal to or less than the threshold value Eth, the correction coefficient k at the time when this error Ec was obtained is determined as the correction coefficient k for correcting the diffusion simulation. On the other hand, if the error Ec is greater than the threshold value Eth, the correction coefficient k is reset, and the carbon concentration is analyzed based on the diffusion simulation to obtain the error Ec. Then, the correction coefficient k is continuously searched for until the error Ec becomes equal to or less than the threshold value Eth.

[0035] In step S104, the diffusion simulation is corrected using the correction coefficient k determined in the process of step S103. Specifically, the parameters (diffusion flux J, diffusion coefficient D, D γ , mobility m γ) is multiplied by the determined correction coefficient k to correct the diffusion simulation, and the carbon concentration in the carburized steel is analyzed using this corrected diffusion simulation. Here, even if the carburizing conditions, the shape (part) of the steel material, and the steel type change, the diffusion simulation can be corrected using the previously determined correction coefficient k. However, the analysis accuracy is improved by performing the processes of steps S101 to S103 for each carburizing condition, shape (part) of the steel material, and steel type, and determining the corresponding correction coefficient k for each.

[0036] According to this embodiment, by correcting the diffusion simulation, it becomes easier to ensure accuracy when analyzing the carbon concentration in a steel material after carburization. In particular, as can be understood from the examples described later, it is possible to accurately analyze the distribution of carbon concentration not only in a single-phase region where carbides do not precipitate, but also in a multi-phase region including austenite and carbides, for example.

[0037] (Diffusion simulation correction) As mentioned above, when correcting the diffusion simulation, the diffusion flux J, diffusion coefficients D and D contained in the diffusion equation and the calculation formula for the diffusion coefficient in the steel are γ and mobility m γ At least one of the above is multiplied by a correction coefficient k. The following equations (1a), (2a), (3a), and (4a) respectively represent the parameters (diffusion flux J, diffusion coefficient D, and D) of the above equations (1), (2), (3), and (4), respectively. γ , mobility m γ ) multiplied by the correction coefficient k.

number

[0038] When analyzing the distribution of carbon concentration using equations (1), (2), and (3), at least one of the diffusion coefficients D, Dγ, and diffusion flux J is multiplied by a correction coefficient k as shown in equations (1a), (2a), and (3a). Since it is "at least one," the carbon concentration distribution may be analyzed using formula (1a), formula (2), and formula (3), the carbon concentration distribution may be analyzed using formula (1), formula (2a), and formula (3), the carbon concentration distribution may be analyzed using formula (1), formula (2), and formula (3a), the carbon concentration distribution may be analyzed using formula (1a), formula (2a), and formula (3), the carbon concentration distribution may be analyzed using formula (1), formula (2a), and formula (3a), the carbon concentration distribution may be analyzed using formula (1), formula (2a), and formula (3a), the carbon concentration distribution may be analyzed using formula (1a), formula (2), and formula (3a), or the carbon concentration distribution may be analyzed using formula (1a), formula (2a), and formula (3a). The correction coefficient k included in each formula may have a different value.

[0039] When analyzing the distribution of carbon concentration using equations (1), (2), and (4), the diffusion coefficient D and mobility m γ and at least one of the diffusion fluxes J is multiplied by a correction coefficient k. Since it is "at least one," the carbon concentration distribution may be analyzed using formula (1a), formula (2), and formula (4), or the carbon concentration distribution may be analyzed using formula (1), formula (2a), and formula (4), or the carbon concentration distribution may be analyzed using formula (1), formula (2), and formula (4a), or the carbon concentration distribution may be analyzed using formula (1a), formula (2a), and formula (4), or the carbon concentration distribution may be analyzed using formula (1), formula (2a), and formula (4a), or the carbon concentration distribution may be analyzed using formula (1a), formula (2), and formula (4a), or the carbon concentration distribution may be analyzed using formula (1a), formula (2), and formula (4a). The correction coefficient k included in each formula may have a different value. Needless to say, the description regarding the "labyrinthiness" in the first embodiment can be applied to the second embodiment.

[0040] (First embodiment) The first example corresponds to the first embodiment. (Steel sample and carburizing conditions) As steel materials to be subjected to reduced pressure carburizing treatment, steel samples having the compositions shown in the table below were prepared. [Table 1]

[0041] Fig. 2 is a perspective view of a steel sample. Referring to the figure, the steel sample was a rectangular prism with a trapezoidal cross section (steel having an edge-shaped portion). The long side L, short side S, and height H of the trapezoidal cross section were 16 mm, 10 mm, and 10 mm, respectively. The rectangular prism length K was 50 mm. The trapezoidal cross section had two angles of 90° and one angle of α (60°).

[0042] The reduced pressure carburizing process included a heating process in which the steel sample was heated to the carburizing temperature in a reduced pressure heating furnace, a soaking process in which the steel sample was soaked at the carburizing temperature, a carburizing process in which carburizing gas (acetylene gas) was introduced into the furnace to carburize the steel sample at the carburizing temperature, a diffusion process in which the invaded carbon was diffused into the steel sample, a temperature reduction process in which the temperature of the steel sample was reduced to a holding temperature, and a holding process in which the temperature of the steel sample was held at the holding temperature, in this order. Note that no carburizing gas was introduced in any process other than the carburizing process. Reduced pressure carburizing condition A shown in the table below was set as the reduced pressure carburizing process condition. [Table 2]

[0043] (Measurement of carbon concentration) The steel samples were subjected to reduced pressure carburization treatment under the above-mentioned carburization conditions, and the carbon concentration (actual measured value) of each of the steel samples after the treatment was measured. Fig. 3 is a cross-sectional view of a steel sample. With reference to the figure, the cross-section at the center of the rectangular column length direction of the steel sample (i.e., the center of length K in Fig. 2) was set as the inspection position, and the carbon concentration was measured in the measurement direction MD indicated by the arrow. The measurement direction MD was in two directions. Specifically, the line that bisects the right angle part of the cross-section (hereinafter also referred to as "90° corner") was set as the measurement direction MD, and the line that bisects the corner part of the cross-section with angle α (hereinafter also referred to as "60° corner") was set as the measurement direction MD. Needless to say, all of the measurement directions MD pass through the edge vertices (vertices of the trapezoidal cross sections).

[0044] (Diffusion simulation) A modeling method in the diffusion simulation will be described below. In this embodiment, a known analytical software (commercial product) based on the finite element method was used, which incorporates a program for calculating the carbon diffusion flux J using the diffusion equation of the above-mentioned formula (1) (a diffusion equation in which the gradient of the carbon concentration in the steel material is used as a driving force). (I) Mesh data The two-dimensional cross section of the area including within a radius of 6 mm from the edge vertex of the 90° corner and 60° corner was modeled, and mesh data was created so that the mesh on the steel surface would be the finest. Specifically, the mesh size was set within the range of 1 to 500 μm. The mesh type was a quadrilateral mesh. (II) Boundary conditions In the carburizing period (carburizing process) of the reduced pressure carburizing treatment, the carbon concentration at equilibrium with graphite obtained by thermodynamic calculation was given at the position corresponding to the surface of the steel material.In addition, after the diffusion period (diffusion process), it was assumed that no carbon penetrated from the surface of the steel material, and it was considered a closed system. (III) Temperature setting The temperature conditions for the reduced pressure carburizing treatment were set in the calculation model as shown in the reduced pressure carburizing conditions above. However, to simplify the calculation, the temperature in the cooling process was fixed at 880°C and set in the analysis model. (IV) Diffusion coefficient D in steel The diffusion coefficient D in the steel was calculated based on equation (3) or equation (4) and used in the diffusion simulation. The carbon concentration C in the austenite contained in equations (3) and (4) γ , activity coefficient in austenite γ γ The diffusion coefficient D in austenite is calculated by thermodynamic calculation from the components at each position in the steel and the set temperature described in (III) above. γ was calculated based on equation (6) and used in the diffusion simulation. The mobility of carbon in austenite, m γThe values ​​calculated by thermodynamic calculation using a thermodynamic database and a diffusion database were used. (V)Labyrinth factor The labyrinth degree was calculated based on equation (5) and used in the diffusion simulation. That is, the labyrinth degree calculated based on equation (5) was multiplied by the right side of equation (3) or equation (4) to calculate the diffusion coefficient D in the steel. The volume fraction of austenite V in Eq. (5) γ The value calculated by thermodynamic calculation was used. n was set to 2. (VI) Thermodynamic calculation Thermodynamic calculations were performed using the commercially available thermodynamic calculation software Thermo-Calc, with the commercially available thermodynamic database TCFE10 and diffusion database MOBFE1. (VII) Correction coefficient k In this example, in order to correspond to the first embodiment, the analysis using multiplication by the correction coefficient k was not performed.

[0045] The conditions of the examples and comparative examples are summarized in Table 3 below. In Comparative Examples 1 and 3, the diffusion coefficient D in the steel material is calculated by the equation (6) for the diffusion coefficient in austenite (i.e., the diffusion coefficient D γ In Comparative Examples 2 and 4, the diffusion coefficient D in the steel material was set to a constant (43 μm 2 / s) was used for the simulation. This constant is based on the literature value. [Table 3] 4 and 5 show the results of the simulation. Note that, in the state of the surface layer under these carburizing conditions, the coarse carbides precipitated in the carburizing process are dissolved in the diffusion process, and no coarse carbides remain. As is clear from Examples 1 to 4, it was found that the analysis accuracy of the carbon concentration distribution can be improved by calculating the diffusion coefficient in the steel material using formula (3) or (4) and performing a diffusion simulation based on a diffusion equation with the carbon concentration gradient in the steel material as the driving force.

[0046] (Second Example) The second example corresponds to the first and second embodiments. (Steel sample and carburizing conditions) The steel composition and sample shape subjected to the reduced pressure carburization treatment were the same as those in the first embodiment. The reduced pressure carburization treatment included a heating process in which the steel sample was heated to the carburization temperature in a reduced pressure heating furnace, a soaking process in which the steel sample was soaked at the carburization temperature, a carburization process in which carburization gas (acetylene gas) was introduced into the furnace and the steel sample was carburized at the carburization temperature, a diffusion process in which the invaded carbon was diffused into the steel sample, a temperature reduction process in which the temperature of the steel sample was reduced to a holding temperature, and a holding process in which the temperature of the steel sample was held at the holding temperature, in this order. Note that no carburization gas was introduced in any process other than the carburization process. The reduced pressure carburization treatment conditions B and C shown in the table below were set as the conditions for the reduced pressure carburization treatment. [Table 4] [Table 5] (Measurement of carbon concentration) The steel samples were subjected to reduced pressure carburization treatment under the above-mentioned carburization conditions, and the carbon concentration (actual measured value) was measured for each of the steel samples after reduced pressure carburization treatment. The carbon concentration was measured in the same manner as in the first embodiment.

[0047] (Diffusion simulation) A modeling method in the diffusion simulation will be described below. In this embodiment, a known analytical software (commercial product) based on the finite element method was used, which incorporates a program for calculating the carbon diffusion flux using the diffusion equation of the above-mentioned formula (1) (a diffusion equation in which the gradient of the carbon concentration in the steel material is used as the driving force). (I) Mesh data It is the same as the first embodiment. (II) Boundary conditions It is the same as the first embodiment. (III) Temperature setting It is the same as the first embodiment. (IV) Diffusion coefficient D in steel The diffusion coefficient D in the steel was calculated based on equation (3) and used in the diffusion simulation. The carbon concentration C in the austenite contained in equation (3) γ The diffusion coefficient D in austenite is calculated by thermodynamic calculation from the components at each position in the steel and the set temperature described in (III) above. γ was calculated based on equation (6) and used for the diffusion simulation. (V)Labyrinth factor The labyrinthiness was calculated based on Equation (5) and used in the diffusion simulation. That is, the labyrinthiness calculated based on Equation (5) was multiplied by the right side of Equation (3). The volume fraction of austenite V in Eq. (5) γ The value calculated by thermodynamic calculation was used for . n was set to 2. (VI) Thermodynamic calculation It is the same as the first embodiment. (VII) Error Calculation The mean absolute error (MAE) between the analytical and measured carbon concentrations was calculated in the range of 0.25 mm from the edge apex of the 60° or 90° corner along the measurement direction MD. (VIII) Setting of correction coefficient k The correction coefficient k was not set in Example 5. That is, Example 5 corresponds to the first embodiment, and the carbon concentration distribution was analyzed using the formulas (1), (2), and (3). In Examples 6 to 8, the correction coefficient k was set in the region where carbide precipitated in the carburization period (carburization process) after the diffusion period (diffusion process) when carbide was dissolved. The correction coefficient was determined so as to improve the analysis accuracy under the conditions shown in Example 6. Specifically, the correction coefficient (0.77) was determined so that the mean absolute error (MAE) was 17% or less. The correction coefficient k was multiplied only to the right side of formula (3). That is, the carbon concentration distribution was analyzed using formulas (1), (2), and (3a). [Table 6]

[0048] 6 to 9 show the results of the simulation. Note that the state of the surface layer under the present carburizing conditions is such that the coarse carbides precipitated in the carburizing process remain after the diffusion process, although some of them are dissolved in solid solution. The range where the carbon concentration is extremely high near the surface corresponds to the range where the coarse carbides remain. As is clear from the analysis results of the carbon concentration distribution in Examples 5 to 8, it was found that the simulation of this embodiment has excellent analysis accuracy of the carbon concentration distribution. Also, as can be seen from the analysis results of Example 5, it was found that even if the correction coefficient is not set, the carbon concentration distribution can be analyzed with high accuracy in the range where no coarse carbides remain (for example, in Example 5, the range from about 0.3 mm from the edge apex to the inside of the steel material). Furthermore, it was found that the simulation of Examples 6 to 8 corrected by the correction coefficient k can analyze the carbon concentration distribution with high accuracy even in the area where the carbon concentration is high near the surface, which corresponds to the range where the coarse carbides remain.

[0049] (Third Example) The third example corresponds to a case where the labyrinth level λ in the first and second embodiments is set differently from the first and second examples. (Steel sample and carburizing conditions) The steel composition and sample shape subjected to the reduced pressure carburizing treatment were the same as those in Examples 1 and 2. The reduced pressure carburizing conditions were either reduced pressure carburizing treatment condition A, reduced pressure carburizing treatment condition B, or reduced pressure carburizing treatment condition C described in Examples 1 and 2. (Measurement of carbon concentration) It is the same as the first embodiment. (Diffusion simulation) A modeling method in the diffusion simulation will be described below. In this embodiment, a known analytical software (commercial product) based on the finite element method was used, which incorporates a program for calculating the carbon diffusion flux using the diffusion equation of the above-mentioned formula (1) (a diffusion equation in which the gradient of the carbon concentration in the steel material is used as the driving force). (I) Mesh data It is the same as the first embodiment. (II) Boundary conditions It is the same as the first embodiment. (III) Temperature setting It is the same as the first embodiment. (IV) Diffusion coefficient D in steel The diffusion coefficient D in the steel was calculated based on equation (3) and used in the diffusion simulation. The carbon concentration C in the austenite contained in equation (3) γ The diffusion coefficient D in austenite is calculated by thermodynamic calculation from the components at each position in the steel and the set temperature described in (III) above. γ was calculated based on equation (6) and used for the diffusion simulation. (V)Labyrinth factor In Examples 9 to 12, the labyrinth degree λ was not set. In Examples 13 to 16, the labyrinthness was calculated based on formula (5) and used in the diffusion simulation. That is, the labyrinthness calculated based on formula (5) was multiplied by the right side of formula (3). The volume fraction Vγ of austenite included in formula (5) was calculated by thermodynamic calculation. n was set to 1. In Examples 17 to 24, the labyrinthness was calculated based on formula (5) and used in the diffusion simulation. That is, the labyrinthness calculated based on formula (5) was multiplied by the right side of formula (3). The volume fraction Vγ of austenite included in formula (5) was calculated by a thermodynamic calculation. n was set to 5 or 8. (VI) Thermodynamic calculation It is the same as the first embodiment. (VII) Error Calculation Calculations were performed under the same conditions as in Example 2 only in the cases of Examples 10-12, 14-16, 18-20, and 22-24 where coarse carbides remained near the apexes of the edge portions. (VIII) Setting of correction coefficient k The correction coefficient k was not set in Example 9, Example 10, Example 13, Example 14, Example 17, Example 18, Example 21, and Example 22. That is, these examples correspond to the first embodiment, and the carbon concentration distribution was analyzed using the formulas (1), (2), and (3). In Example 11, Example 12, Example 15, and Example 16, the correction coefficient k was set in the region where carbide precipitated in the carburization period (carburization process) at the time after the diffusion period (diffusion process) where carbide becomes solid solution. The correction coefficient was determined so that the analysis accuracy was improved under the conditions shown in Example 11 or Example 15. Specifically, in Example 11, the correction coefficient (0.83) was determined so that the mean absolute error (MAE) was 11% or less. In Example 15, the correction coefficient (0.83) was determined so that the mean absolute error (MAE) was 18% or less. In Example 19, Example 20, Example 23, and Example 24, the correction coefficient k was set in the region where carbide precipitated in the carburization period (carburization process) at the time after the diffusion period (diffusion process) where carbide dissolves. The correction coefficient was determined so that the analysis accuracy would improve under the conditions shown in Example 19 or Example 23. Specifically, in Example 19, the correction coefficient (0.50) was determined so that the mean absolute error (MAE) would be 40% or less. In Example 23, the correction coefficient (0.37) was determined so that the mean absolute error (MAE) would be 40% or less. The correction coefficient k was multiplied only to the right side of formula (3). That is, the carbon concentration distribution was analyzed using formulas (1), (2), and (3a). [Table 7]

[0050] 10 to 25 show the results of the simulation. In Examples 10 to 12, 14 to 16, 18 to 20, and 22 to 24, the state near the corner apex is such that the coarse carbides precipitated in the carburizing process are partially dissolved after the diffusion process, but remain. In Examples 9, 13, 17, and 21, the coarse carbides precipitated in the carburizing process are dissolved in the diffusion process, and almost no coarse carbides remain. Therefore, the range where the carbon concentration is extremely high corresponds to the range where the coarse carbides remain. As is clear from the analysis results of the carbon concentration distribution in Examples 9 to 24, it was found that the simulation of this example has better analysis accuracy of the carbon concentration distribution than the comparative example.

[0051] Also, as can be seen from the analysis results of Example 9, Example 10, Example 13, Example 14, Example 17, Example 18, Example 21, and Example 22, it was found that even when the correction coefficient was not set, the carbon concentration distribution could be analyzed with high accuracy in the range where no coarse carbides remained (for example, the range from about 0.3 mm from the edge apex to the inside of the steel material in Example 10). In addition, it was found that the simulations of Example 11, Example 12, Example 15, Example 16, Example 19, Example 20, Example 23, and Example 24 corrected by the correction coefficient k could analyze the carbon concentration distribution with even higher accuracy in the region where the carbon concentration near the surface is high, which corresponds to the range where coarse carbides remain, compared to the case where the correction coefficient was not set.

[0052] As can be seen from the analysis results of the second and third examples, it was found that analysis can be performed with higher accuracy than the comparative example, regardless of whether the labyrinth level is set or the value of the integer n in the labyrinth level. In other words, the integer n in the labyrinth level is not limited to the common values ​​of 1 or 2, and even if it is a larger integer, the required analysis accuracy (i.e., analysis accuracy higher than that of the comparative example) is guaranteed. The upper limit of the integer n cannot be uniquely defined because it differs depending on the degree of carbide formation, which changes depending on the steel composition. The integer n can be set appropriately so that the required analysis accuracy is obtained. [Explanation of symbols]

[0053] L long side S Short side H Height K Square column length

Claims

1. A method for analyzing carbon concentration distribution in a carburized steel material using a diffusion equation, comprising the steps of: Carbide is formed in the steel material by the carburizing treatment, The diffusion equation is represented by the following formula (I) and the following formula (II): A method for analyzing a carbon concentration distribution, comprising calculating D in the following formula (I) from the following formula (III) or the following formula (IV): [0010] In the above formula (I), J is the diffusion flux of carbon, D is the diffusion coefficient of carbon in the steel material, C is the carbon concentration in the steel material, and grad is the position gradient. In the above formula (II), C is the carbon concentration in the steel, t is time, div is the diffusion, and J is the diffusion flux of carbon. In the above formula (III), D γ is the diffusion coefficient of carbon in austenite, C is the carbon concentration in the steel, and C γ is the carbon concentration in austenite. In the above formula (IV), m γ is the mobility of carbon in austenite, R is the gas constant, T is the temperature, C is the carbon concentration in the steel, and C γ is the carbon concentration in austenite, and γ γ is the activity coefficient of carbon in austenite [-].

2. In the carbide precipitation region in the steel material formed by the carburizing treatment, the diffusion coefficient D of formula (I), the diffusion flux J of formula (II), the diffusion coefficient D of formula (III) γ , the mobility m of formula (IV) γ multiplying at least one of the above by a correction coefficient; 2. The method for analyzing a carbon concentration distribution according to claim 1, wherein the correction coefficient is set so as to satisfy a condition that an error between the carbon concentration distribution analyzed from the diffusion equation and the carbon concentration distribution measured in advance is equal to or less than a threshold value.

3. When calculating D in formula (I) from formula (III), multiply the right side of any one of formulas (I), (II), and (III) by the labyrinth degree λ represented by the following formula (V): When calculating D in formula (I) from formula (IV), the right side of any one of formulas (I), (II), and (IV) is multiplied by the labyrinth degree λ represented by the following formula (V):

3. The method for analyzing carbon concentration distribution according to claim 1 or 2. [0025] V γ is the volume fraction of austenite [-], and n is an integer.

Images