JPH0610039A - Method for predicting structure distribution and hardness distribution in austempering treatment - Google Patents

Abstract

PURPOSE:To predict structure distribution and hardness distribution in a material to be treated in a short time by collating the temp. hysteresis in each part of the material to be treated, determined by means of heat transfer analysis, with a CCT curve to predict the duration of transformation in each part of the material to be treated and computing the amount of isothermal transformation occurring in each part of the material to be treated. CONSTITUTION:In the austempering treatment for steel or cast iron, the temp. hysteresis in each part of the material to be treated is determined by means of heat transfer analysis by using a numeric value computing method and this temp. hysteresis is collated with the CCT curve, by which the duration of transformation in each part of the material to be treated is predicted. As to this duration, the amount of isothermal transformation occurring in each part of the material to be treated is computed in the form of the sum total of each trace amount of isothermal transformation DELTAf1, occurring at transformation temp., Tt1, for each trace duration, DELTAtsec and obtained on the basis of a TTT curve and the structure in each part of the material to be treated is obtained on the basis of the resulting value, by which the structure distribution after treatment is predicted. Further, the average transformation temp., TA, for each duration, DELTAtsec, is computed and the hardness in each part of the material to be treated is obtained on the bases of the resulting value, by which hardness distribution after treatment can be predicted.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for predicting the structure distribution and hardness distribution of steel or cast iron after austempering.

[0002]

As shown in the Related Art FIG. 8, for austempering treatment to prevent the occurrence of quenching distortion while improving the hardness and toughness of the steel and cast iron, treated product of the A ₁ transformation temperature or higher austenite region after heating to, M _S at a cooling rate which does not cause pearlite transformation in a fluidized bed or a salt in the bath
Cooling is performed to a temperature range higher than the point (200 to 400 ° C), and bainite transformation is performed at a constant temperature within this temperature range.

For example, as shown in FIG. 9, carbon steel (non-alloy) is pearlite within a region represented by a CCT curve A-1 representing the relationship between the temperature and time at which transformation starts and ends during the cooling process. Causes transformation and CCT curve A
Bainite transformation occurs in the region indicated by -2. When carbon steel having such a CCT curve is cooled along the cooling curve C- ₁ , bainite transformation starts at a temperature T ₁ ,
If this temperature T ₁ is maintained and the bainite transformation proceeds, a bainite structure can be formed in the carbon steel and austempering can be performed.

However, even if a treated product made of the same carbon steel is austempered at the same furnace temperature, a cooling curve C-2 is obtained due to a difference in heat conduction rate at a portion having a large distance from the surface of the treated product. The cooling progresses slowly. With such cooling, the pearlite transformation starts at the temperature T ₂ , and even if the cooling progresses and the pearlite transformation ends and the bainite transformation occurs, the pearlite structure is formed in the steel and the austempering process is smooth. Not done to.

Further, even if the cooling proceeds substantially according to the cooling curve C-1 and the austempering is performed without forming the pearlite structure, the difference between the set temperature of the processing furnace and the temperature of the processed product and the meat of the processed product. Since the start temperature of the bainite transformation in each part differs due to the difference in the heat conduction rate between the thick part and the thin part, the hardness of the formed bainite structure also differs. For example, with respect to the set temperature T ₁ of the processing furnace, if the temperature of the processed product reaches the temperature T ₁ before entering the bainite transformation region, a bainite base at the temperature T ₁ can be obtained.
Bainite transformation starts at a temperature slightly higher than _{1, and} the hardness of the treated product becomes lower than the target hardness. Therefore, such variations in structure and hardness are caused by the difference between the set temperature of the furnace temperature and the temperature of the processed product, and also by the difference in the thickness of each part of the processed product.

Conventionally, in order to predict the structure distribution and hardness distribution of such an austempered product, round bars having various diameters are austempered and the cooling curve of each round bar is measured to obtain the corresponding diameter. A method of estimating the structure and hardness of each part of the actual processed product after austempering is adopted. Further, it is also performed to accumulate experimental data on the structure and hardness of an actual processed product after austempering, and estimate the structure distribution and hardness distribution of the processed product.

[0007]

However, the CCT curve as described above differs depending on the material of the processed product, and for example, the CCT curve of the alloy steel to which Ni, Co, etc. are added is B-1 ( Perlite transformation) and B
-2 (Bainite transformation) requires a longer time for each transformation than carbon steel. Further, in such austempering treatment, in order to obtain hardness that matches the purpose of use of the treated product, treatment may be performed at a temperature at which a pearlite structure is intentionally formed. The shape makes the texture distribution and hardness distribution prediction more complicated and difficult.

Therefore, in the method of estimating the structure distribution and hardness distribution of the actual part after the austempering by actually measuring the cooling curve of the round bar as described above, the cooling curve in each part of the actual processed product having a complicated shape is There is a problem that it is difficult to judge which size of the round bar corresponds, and it is very difficult to accurately predict the hardness distribution and hardness of the processed product. Further, in the method of estimating the tissue distribution and hardness distribution of the processed product from the accumulated experimental data, it is necessary to perform a huge number of experiments in order to make an accurate estimation, which is extremely expensive. There is a problem that accurate prediction is difficult.

In order to solve the above problems, the present invention is capable of predicting the structure and hardness distribution of an austempered product by calculation in a short time without repeating trial and error experiments. And a method for predicting hardness distribution.

[0010]

The method for predicting the structure and hardness distribution in the austempering treatment according to the present invention is (a) a numerical calculation method in the austempering treatment of steel or cast iron in order to achieve the above-mentioned object. The temperature history of each part of the processed product is obtained by the heat conduction analysis using, and the time when the transformation occurs in each part of the processed product is predicted by comparing these temperature histories with the CCT curve.
During the predicted transformation time, the amount of isothermal transformation that occurs in each part of the processed product is the minute isothermal transformation amount Δf _j that is obtained at the transformation temperature Tt _j at every minute time Δt seconds and is obtained based on the TTT curve. Of the treated product based on this isothermal transformation amount, and predicting the tissue distribution after austempering, and (c) the minute time Δt that causes the isothermal transformation amount.
It is characterized in that the average transformation temperature T _A for each second is calculated, and the hardness of each part of the treated product is obtained based on this average transformation temperature T _A to predict the hardness distribution after austempering.

The isothermal transformation amount is calculated by the following equation (1) (Avrami's equation), and the isothermal transformation rate X after t seconds from the start of cooling.
Based on the above, the minute isothermal transformation amount Δf calculated from the minute increase amount ΔX of the isothermal transformation rate during the minute time Δt seconds.
It is preferably calculated as the sum of _j . X = 1-exp (−b × t ⁿ ) (1) X: Isothermal transformation rate b: Constant dependent on transformation temperature n: Constant dependent on transformation phase t: Time from cooling start (seconds)

The hardness of each part of the treated product is as follows.
Average transformation temperature T calculated from equation (2) _ANext based on
It is preferably calculated by the equation (3). T_A= (ΣTt_j× Δf_j) / Fτ (j = 1 to n) (2) Tt_j: Transformation temperature Δf in each Δt second_j: Small amount of isothermal transformation for each Δt seconds fτ: Final amount of transformation n: Minute time of transformation divided by Δt seconds
Accumulated number of times H_B= K₁× T_A ²+ K₂× T_A+ K₃ (3) H_B: Brinell hardness k₁, k₂, k₃:constant

[0013]

In the austempering process of steel or cast iron, the temperature history of each part of the processed product is obtained by the heat conduction analysis using a numerical calculation method such as the finite element method, and the temperature history of these is compared with the CCT curve. Predict the time during which transformation occurs in each part of the processed product. While this transformation is occurring, the isothermal transformation amount Δf generated at each part of the processed product is obtained at the transformation temperature Tt _j at every minute time Δt seconds and obtained based on the TTT curve.
If it is calculated as the sum of _j , it is possible to obtain the structure of each part of the processed product based on this isothermal transformation amount and predict the structure distribution after austempering. This isothermal transformation amount is, for example,
Calculated as the sum of the minute isothermal transformation amount Δf _j calculated from the minute increase amount ΔX of the isothermal transformation rate during the minute time Δt seconds obtained based on the isothermal transformation rate X calculated from the Avrami equation (1). . Furthermore, since the hardness of the treated product is determined by the transformation temperature, the hardness of each part of the treated product is
Based on the average transformation temperature T _A calculated from the equation (2),
The hardness distribution of the processed product can be predicted from the equation (3).

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Next, a specific embodiment of the method for predicting the tissue distribution and hardness distribution in the austempering process according to the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing the configuration of an austempering apparatus 1 to which the method for predicting the tissue distribution and hardness distribution in austempering according to the present invention is applied. In the austemper processing apparatus 1, the size and shape of the processed product, the type of cooling medium, and the set furnace temperature of the austempering processing furnace 3 are input to the CPU 4 from the input unit 2. Also, this C
The set furnace temperature input to the PU 4 is set in the furnace temperature setting unit 5 of the austempering processing furnace 3. In the CPU 4, the processed product is mesh-divided by a known means using the finite element method based on the inputted shape and size of the processed product, and the material composition of the processed product, the cooling medium, The temperature history is obtained by heat conduction analysis based on the furnace temperature, etc., and is also collated with the temperature for each minute time in the cooling process and the CCT curve and TTT curve according to the material composition of the processed product stored in the memory 6, The structure distribution is predicted based on the sum of the minute isothermal transformation amounts that occur every minute time, and the hardness distribution is further predicted based on the average transformation temperature. Then, these predicted results are displayed on the display unit 7.

The test piece 11 used in the present embodiment has C: 3.50%, Si: 2.82%, Mn: 0.26%,
P: 0.068%, S: 0.014%, Mg: 0.037%, Cu:
Spheroidal graphite cast iron containing 0.05%, Mo: 0.55%,
As shown in FIG. 2, it is a stepwise flat plate having a width of 400 mm, a depth of 150 mm and a thickness of 10 to 30 mm in four steps. This spheroidal graphite cast iron causes pearlite transformation and bainite transformation in the CCT curve as shown in FIG. 3, and the isothermal transformation process from austenite to bainite is shown in FIG.
Is shown as the TTT curve of.

Regarding the method of predicting the tissue distribution and hardness distribution in the austempering of the test piece 11 as described above, the cooling curve and CCT curve shown in FIG.
This will be described in detail with reference to the TTT curve shown in FIG. 4 and based on the flowchart shown in FIG. The austempering treatment was performed by austenitizing at 900 ° C. for 1.5 hours, then cooling in a fluidized bed, maintaining a constant temperature at 370 ° C. for 1.5 hours, and then air-cooling. The thermophysical properties used for the thermal conductivity analysis are: density: 7.0 g / cm ³ , thermal conductivity: 0.07 c
al / g ・ ℃, specific heat: 0.155 cal / cm ・ s ・ ℃, latent heat: 30 cal /
g, thermal conductivity coefficient (fluidized bed): 0.007 cal / cm ² · s · ° C.

Step A: Input austempering processing conditions and heat conduction analysis conditions such as the size and shape of the processed product, the material composition of the processed product, the type of cooling medium, the mesh size for analyzing the tissue distribution and the hardness distribution. Step B: The processed product is divided into meshes. The processing from step B to step J is performed for each part of the mesh-divided processed product. Step C: The elapsed time t seconds from the start of cooling is defined as the time elapsed by each minute time Δt seconds, and the processes up to step J are performed every minute time Δt seconds between t and t + Δt seconds. Step D: A heat conduction analysis is performed by a known method using the finite element method, and the temperature T in each mesh is obtained.

Step E: The temperature T obtained in the previous step D is compared with the CCT curve, and if it is within the transformation region where transformation occurs, proceed to Step F, and if it is outside the transformation region, proceed to Step H. Step F: Av shown in equation (1) based on the TTT curve
The isothermal transformation rate X after t seconds from the start of cooling is calculated by the rami equation. Further, a minute increase amount ΔX of the isothermal transformation rate in Δt seconds is obtained. Step G: Based on the minute increase amount ΔX of the isothermal transformation rate in Δt seconds obtained in the previous step F, the transformation latent heat ΔH (cal) generated during this period is calculated by the following equation (4). ΔH = ρ · L · ΔX / Δt (4) ρ: Density (g / cm ³ ) L: 100% Transformation latent heat amount generated during transformation (cal) Step H: Temperature T obtained in Step E or Step G The obtained transformation latent heat ΔH is also included in the heat balance equation. If this heat balance formula is satisfied, the temperature T obtained by the heat conduction analysis is considered to be a reasonable value, and the process proceeds to step I. If the heat balance formula is not satisfied, the process returns to step D and each Perform step processing.

Step I: If the judgment in step E is within the transformation area, proceed to step J, and if it is outside the transformation area, proceed to step K. Step J: The temperature T obtained by the heat conduction analysis is stored in the memory 6 as the isothermal transformation temperature Tt _j for Δt seconds, and the minute isothermal transformation amount Δf _j is calculated based on the minute increment ΔX of the isothermal transformation rate during this period. , This slight isothermal transformation amount Δ
f _{j is} also stored in the memory 6. That is, the isothermal transformation temperature Tt _j and the minute isothermal transformation amount Δf _j are stored in the memory 6 by the number of times n, which is the time during which the transformation is occurring divided by Δt seconds. Step K: Check whether or not the austempering process is completed. If the austempering process is completed, proceed to Step L.
If the austempering process is further continued, the process returns to step C and the process is performed for the time after the lapse of the minute time Δt seconds. Step L: For each part of the processed product, the total sum (j = 1 to n) of the isothermal transformation amount Δf _j at the transformation temperature Tt _j for each Δt seconds stored in the memory 6 is obtained, and the tissue distribution after the austempering treatment is calculated. Predict. Step M: For each part of the processed product, the average transformation temperature T _A is obtained from the above-mentioned equation (2) from the transformation temperature Tt _j and the isothermal transformation amount Δf _j stored in the memory 6 for each Δt second, and this average transformation is calculated. By substituting the temperature T _A into the formula (3), the Brinell hardness H _B is calculated, and the hardness distribution after the austempering is predicted.

In addition, what is shown in FIG. 3 together with the CCT curve is the thickness 30 mm, 20 m in the relationship between the temperature T and the time t obtained for each part of the processed product by the heat conduction analysis.
_{3 is} a cooling curve (dotted line) showing the relationship between temperature and time at the central portions of m and 15 mm (Z ₁ , Z ₂ , Z ₃ in FIG. 2) on a graph. The cooling curve obtained by this analysis agrees very well with the cooling curve (solid line) obtained by actual measurement for the same part, and it was found that latent heat is released during transformation when the pearlite nose is applied even when the thickness is 15 mm. It is clear that the above mentioned heat transfer analysis is reliable.

FIG. 6 (A) shows the distribution of the average transformation temperature T _A at the center of the test piece 11 obtained by heat conduction analysis for the above-mentioned test piece 11, and FIGS. 6 (B) and 6 (C) show the structure. In addition to showing the distribution prediction result, FIG. 7 shows the observation result of the tissue actually obtained by the austempering treatment. By the way, from Fig. 6 (B) and (C), full bainite is predicted in the part with a wall thickness of 10 mm, but a mixed structure of pearlite and bainite is predicted in a part with a wall thickness of 15 mm or more. Tends to increase with increasing. It can be seen that this tendency is in good agreement with the actual tissue observation result shown in FIG. 7.

In the present embodiment, the structure distribution and hardness distribution were obtained after the austempering treatment. However, if the temperature history obtained in the cooling process is fed back to the furnace temperature, the treated product can have a desired hardness.

[0023]

According to the present invention, the structure distribution and hardness distribution of the austempered product can be accurately predicted without the need for trial and error or the collection of enormous amounts of data as in the prior art. Can be reduced to

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of an austempering apparatus to which a method of predicting a tissue distribution and a hardness distribution in an austempering treatment of the present invention is applied.

FIG. 2 is a cross-sectional view of a test piece used for predicting a tissue distribution and hardness distribution in an austempering process in an example.

FIG. 3 is a graph showing a CCT curve and a cooling curve used for predicting a tissue distribution and a hardness distribution in austempering in Examples.

FIG. 4 is a graph showing a TTT curve used for predicting the tissue distribution and hardness distribution in the austempering treatment in Examples.

FIG. 5 is a flowchart illustrating a method of predicting a tissue distribution and a hardness distribution in the austempering process of the present invention.

6A and 6B are prediction results of the structure distribution and hardness distribution of the test piece in the austempering treatment, where FIG. 6A is a diagram showing the distribution of the average transformation temperature, FIG. 6B is a diagram showing the distribution of the bainite structure, and FIG. It is a figure which shows distribution of a ferrite structure and a pearlite structure.

FIG. 7 is a micrograph showing an actual structure in the central portion of each thickness of the test piece after the austempering treatment shown in FIG.

FIG. 8 is an explanatory diagram illustrating a relationship between temperature and time in the austempering process.

FIG. 9 is a graph showing an example of a CCT curve and a cooling curve.

[Explanation of symbols]

 1 Austempering processing device 2 Input section 3 Austempering processing furnace 4 CPU 5 Furnace temperature setting section 6 Memory 7 Display section 11 Test piece

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[Procedure amendment]

[Submission date] December 17, 1992

[Procedure Amendment 1]

[Document name to be amended] Statement

[Name of item to be corrected] Brief description of the drawing

[Correction method] Change

[Correction content]

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of an austempering apparatus to which a method of predicting a tissue distribution and a hardness distribution in an austempering treatment of the present invention is applied.

FIG. 2 is a cross-sectional view of a test piece used for predicting a tissue distribution and hardness distribution in an austempering process in an example.

FIG. 3 is a graph showing a CCT curve and a cooling curve used for predicting a tissue distribution and a hardness distribution in austempering in Examples.

FIG. 4 is a graph showing a TTT curve used for predicting the tissue distribution and hardness distribution in the austempering treatment in Examples.

FIG. 5 is a flowchart illustrating a method of predicting a tissue distribution and a hardness distribution in the austempering process of the present invention.

6A and 6B are prediction results of the structure distribution and hardness distribution of the test piece in the austempering treatment, FIG. 6A shows a distribution of average transformation temperature, and FIG. 6B shows a bainite structure.
FIG. 3C is a diagram showing distribution, and FIG. 6C is a diagram showing distribution of ferrite structure and pearlite structure.

7 is a micrograph showing an actual metallographic structure at the center of each thickness of the test piece after the austempering treatment shown in FIG.

FIG. 8 is an explanatory diagram illustrating a relationship between temperature and time in the austempering process.

FIG. 9 is a graph showing an example of a CCT curve and a cooling curve.

[Explanation of reference numerals] 1 austempering apparatus 2 input section 3 austempering processing furnace 4 CPU 5 furnace temperature setting section 6 memory 7 display section 11 test piece

[Procedure Amendment 2]

[Document name to be corrected] Drawing

[Name of item to be corrected] Figure 7

[Correction method] Change

[Correction content]

[Figure 7]

Claims (3)

[Claims] 1. In austempering of steel or cast iron, (a) the temperature history of each part of the processed product is obtained by heat conduction analysis using a numerical calculation method, and these temperature histories are CC
The time when transformation is occurring in each part of the processed product is predicted by collating with the T curve, and (b) the isothermal transformation amount that occurs in each part of the treated product is minimized at the time when the predicted transformation is generated. Austempering is performed by calculating as the sum of the minute isothermal transformation amount Δf _j generated at the transformation temperature Tt _j every time Δt seconds and obtained based on the TTT curve, and obtaining the structure of each part of the processed product based on this isothermal transformation amount. While predicting the subsequent microstructure distribution, (c) calculating the average transformation temperature T _A for each minute time Δt seconds that causes the isothermal transformation amount, and calculating the average transformation temperature T _A.
A method for predicting a tissue distribution and a hardness distribution in an austempering treatment, which comprises predicting a hardness distribution after austempering treatment by obtaining hardness of each part of the treated product based on the above. 2. The isothermal transformation amount is calculated by the following equation (1) (Avrami
Of the isothermal transformation rate X after t seconds from the start of cooling calculated by the equation (1), the minute isothermal transformation rate Δ calculated from the minute increase ΔX of the isothermal transformation rate during the minute time Δt seconds.
It is calculated as the sum total of f _j.
The method for predicting the tissue distribution and hardness distribution in the austempering treatment described in. X = 1-exp (−b × t ⁿ ) (1) X: Isothermal transformation rate b: Constant dependent on transformation temperature n: Constant dependent on transformation phase t: Time from cooling start (seconds) 3. The hardness of each part of the treated product is determined based on the average transformation temperature T _A calculated by the following equation (2),
The method for predicting the tissue distribution and hardness distribution in the austempering treatment according to claim 1 or 2, which is calculated by a formula. T _A = (ΣTt _j × Δf _j ) / fτ (j = 1 to n) (2) Tt _j : Transformation temperature in each Δt second Δf _j : Small isothermal transformation amount in each Δt second fτ: Final transformation amount n: Transformation number accumulation is divided by that time a minute time Δt seconds resulting _{H B = k 1 × T a} 2 + k 2 × T a + k 3 (3) H B: Brinell hardness _{k 1, k 2, k 3} : constant