JP3365588B2 - Chill prediction method for spheroidal graphite cast iron structure - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a chill prediction method for a spheroidal graphite cast iron structure.

[0002]

2. Description of the Related Art When spheroidal graphite cast iron has a high solidification rate, chill, which is a rapidly cooled cementite, is likely to be formed. The structure produced by chill is hard but brittle. On the other hand, the structure in which chill is not formed generally consists of ferrite, pearlite, and graphite and has toughness. In the industry, the cooling rate of the molten metal has been conventionally increased by using a chiller or the like to actively generate chill, or the cooling rate of the mold is increased by increasing the heat insulating property of the mold, depending on the use such as casting. And actively deter chill. However, these operations must rely heavily on trial and error.

If chills are not formed in the desired structure, a problem arises in that the required hardness of the cast product cannot be obtained. Alternatively, if chills are generated in a tissue in which chilling is not desired, there is a problem that breakage or the like of the cutting tool may occur during processing.

[0004]

SUMMARY OF THE INVENTION The present invention has been made in view of the above situation, and its object is to effectively predict chill generation by using a chill prediction parameter and reduce or avoid trial and error. Another object of the present invention is to provide a method for predicting the chill of a spheroidal graphite cast iron structure, which is advantageous for

[0005]

Means for Solving the Problems The present inventor has found that when the solidification rate of the molten spheroidal graphite cast iron is high, the number of spheroidal graphite particles that precipitate is large, and when the solidification rate of the molten metal is high, the amount of chill formation is large. from becoming, focusing on the correlation between the black Namarikaku production rate and chill emissions. And confirm the correlation in the test,
The invention according to claim 1 has been developed.

Further, the present inventor sets the solid fraction of the molten spheroidal graphite cast iron to F, and when 0 <F <1, the chill prediction parameter and the chill generation amount are correlated if the chill prediction parameter is obtained. Attention was paid to the point of increasing the value, the correlation was confirmed by a test, and the invention according to claim 2 was developed. That chill prediction method of spheroidal graphite cast iron structure according to claim 1 obtains a chill prediction parameters based on the black Namarikaku generation speed that put the molten spheroidal graphite cast iron, chill in ductile iron in accordance with the chill prediction parameters It is characterized by predicting the amount of generation.

A chill prediction method for a spheroidal graphite cast iron structure according to a second aspect of the present invention is such that the solid phase ratio of the molten spheroidal graphite cast iron is F and 0 <
When F <1, black Namarikaku generation speed that put the spheroidal graphite cast iron
A chill prediction parameter is obtained based on the chill prediction parameter, and the chill generation amount in spheroidal graphite cast iron is predicted according to the chill prediction parameter. Where F = 0 is the liquid phase
Means the solid state, where F = 1 means the solid state only.
To taste.

[0008]

According to the method of claim 1, according to the action and the present invention, it obtains a chill prediction parameters related black Namarikaku production rate that put the molten spheroidal graphite cast iron, predicts the chill generation amount based on the chill prediction parameters. According to this method, the chill prediction parameter correlates with the chill generation amount, and the actual chill generation amount in spheroidal graphite cast iron is effectively predicted.

The graphite nucleation number and the graphite nucleation rate correspond to each other, and if the graphite nucleation rate is high, the graphite nucleation number also increases. According to the method of claim 2, when the solid phase ratio F of the molten spheroidal graphite cast iron is 0 <F <1, the chill prediction parameter is obtained. According to the second aspect, the correlation between the chill prediction parameter and the chill generation amount is further improved, and the chill generation amount in the spheroidal graphite cast iron is effectively predicted.

As described above, according to the first and second aspects, since the amount of chill formation in the spheroidal graphite cast iron can be predicted, it is possible to improve the point that largely depends on the trial and error as in the conventional case. Therefore, when the chill is used to accelerate the cooling rate of the molten metal to positively generate chill, an appropriate chill generation operation can be performed. Alternatively, when the cooling rate is slowed by, for example, increasing the heat insulating property of the mold to positively suppress the chill, an appropriate chill suppressing operation can be performed.

Therefore, according to the method of the present invention, chill is not generated in the tissue in which chill needs to be generated,
Alternatively, it is advantageous in reducing or avoiding the problem that chills are generated in tissues where chills are not desired. Therefore, it is advantageous for reducing the defective rate and improving the productivity of the spheroidal graphite cast iron casting. It is also advantageous for reducing and avoiding the problem that the casting thickness is increased more than necessary in order to avoid chill formation, and can contribute to weight reduction and price reduction in the spheroidal graphite cast iron casting.

[0012]

EXAMPLE In this example, the eutectic composition or a similar eutectic composition system was applied to spheroidal graphite cast iron. This spheroidal graphite cast iron draws a cooling curve as schematically shown in FIG. In the region A, the temperature of the molten metal drops with time. The temperature rise in the region B where eutectic is generated is due to the effect of latent heat generated from the solid phase due to the solidification of spheroidal graphite cast iron. When completely solidified, the generation of latent heat is stopped, so that the temperature is lowered with the passage of time as shown in region C.

In this example, the difference method is adopted and the processing is executed for each of the divided elements. FIG. 2 shows a flowchart of a main routine executed by the computer.
In addition, the small letter t means time, and the upper case T means temperature of spheroidal graphite cast iron. In step S2, initial conditions such as the molten metal pouring temperature of the spheroidal graphite cast iron, the temperature of the mold, and the amount of Si in the spheroidal graphite cast iron are input from a setting means such as a keyboard. Therefore, step S2 constitutes the pouring temperature setting means, the mold temperature setting means, and the Si content setting means. In step S4, a molten metal flow calculation processing subroutine is executed. The molten metal flow calculation processing subroutine calculates the filling degree of the molten metal and the temperature of the molten metal that has been lowered according to the molten metal flow according to the casting method.

In step S6, it is determined whether or not the mold is completely filled. If the filling is completed, the temperature calculation processing subroutine during solidification is executed in step S8, and the temperature T of the spheroidal graphite cast iron (generally, the molten metal of spheroidal graphite cast iron), that is, the temperature T (t) at the time t is set as a unit time. Ask for each.
Next, in step S10, it is determined whether or not the solid fraction F is more than 0 and less than 1, that is, the region of O <F <1, in other words, the solid and liquid phases are coexisting. To do. Therefore, step S10 constitutes solid-liquid coexistence determining means. The solid phase ratio "0" means only the liquid phase, and the solid phase ratio "1" means only the solid phase.

If NO, the process proceeds from step S10 to step S14. If YES, the process proceeds from step S10 to step S12 to execute a chill prediction parameter calculation processing subroutine. Next, in step S14, it is determined whether or not the calculation is completed, that is, whether or not all the elements in the difference method have been calculated. If NO, the process proceeds to step S8 and the same operation is repeated.

If YES, the process proceeds from step S14 to step S16, a determination process is performed for chill evaluation, and in step S18, both the value of the chill prediction parameter P and the chill occurrence amount evaluation point M are output to an output means such as a display or a printer. Output. FIG. 3 shows a flowchart of the above temperature calculation processing subroutine. In step S802,
The temperature T ′ (t + Δt) of the spheroidal graphite cast iron at the time (t + Δt) ignoring the latent heat is obtained from the heat transfer equation f. In step S804, the degree of supercooling θ of the molten metal is calculated from the equation θ = TLI−T. Here, TLI indicates a stable equilibrium eutectic temperature, and TLI = (1154.4 + 6.5 ×% Si)
It is a value determined according to the Si content based on [° C]. Therefore, step S804 constitutes supercooling degree calculating means for obtaining the supercooling degree of the molten metal.

Next, in step S806, ΔF = (θ
² × Δt / constant), the change in the solid fraction F, that is, the solid fraction change ΔF is obtained. Here, the constant is a value obtained by an experimental value. Therefore, step S806 constitutes a solid fraction change calculation means. Next, in step S808,
The recovery temperature ΔT of the molten metal due to latent heat is calculated from the formula ΔT = ΔF × Q / ρ. This is because latent heat is generated with solidification and the temperature rises due to the latent heat. Accordingly, step S808 constitutes a latent heat recovery temperature calculation means for obtaining the latent heat of the molten spheroidal graphite cast iron. Here, Q represents the total latent heat [J / mol] generated until the liquid phase is completely solidified. ρ indicates a specific heat [J / mol / k].

Next, in step S810, T (t + Δ
t) = {T ′ (t + Δt) + ΔT} is substituted with the above-mentioned T ′ (t + Δt) and ΔT, respectively, so that Δt [sec] has elapsed from the time (t), that is, the time ( Temperature of spheroidal graphite cast iron at t + Δt T (t + Δt
t) is obtained and the process returns to the main routine. FIG. 4 shows a flowchart of the chill prediction parameter calculation processing subroutine. In step S1202, E = constant × 1 /
The graphite critical nucleation energy-E is calculated from the equation (dF / dt). Therefore, step S1202 constitutes a graphite critical nucleation energy-calculation means.

In step S1204, Vc = constant × e
xp (−E / (R · T)) formula, the graphite nucleation rate Vc
Ask for. Therefore, step S1204 constitutes graphite nucleation rate calculation means for obtaining the rate Vc of graphite nucleation in the molten spheroidal graphite cast iron. Next, proceeding to step S1206, the chill prediction parameter P is obtained from the equation P = Σ (constant × graphite nucleation rate Vc × Δt). Σ means that the difference elements are integrated. Therefore, step S1206 constitutes a chill prediction parameter calculation means corresponding to chill formation in spheroidal graphite cast iron.

The determination processing in step S16 shown in FIG. 2 is based on the data in the graph shown in FIG. That is, as shown in FIG. 5, the value of the chill prediction parameter P obtained by calculation is taken as the horizontal axis, the chill generation amount evaluation point M in the structure of the actually cast spheroidal graphite cast iron is taken as the vertical axis, and the chill prediction parameter P is Chill generation amount evaluation point M
Are associated with each other and the characteristic line K is defined. Data regarding the graph is stored in a storage unit such as a memory.
Then, in the determination process, based on the characteristic line K, from the value of the chill prediction parameter P obtained by the calculation, the chill occurrence amount evaluation point M corresponding thereto is obtained.

Here, how to determine the chill generation amount evaluation point M will be described. That is, FIG. 6 shows chill generation amount evaluation points according to the structure of the actually cast spheroidal graphite cast iron (optical microscope; magnification 100 times). In FIG. 6 (A), the spheroidal graphite is fine and has a large number of grains, and more chills are produced, and the chill generation amount evaluation point is 5. In FIG. 6 (B), the spheroidal graphite is slightly large, the number of particles is slightly reduced, and the chill amount is reduced, but the chill still remains, and the chill generation amount evaluation point is 4. In FIG. 6 (C), chill is significantly reduced, the particle size of spheroidal graphite is also large, and the number of spheroidal graphite is also considerably reduced, and the chill generation amount evaluation point is 3. Figure 6
In (D), chill is not substantially generated, the particle size of the spherical graphite is large, the number of particles is decreasing, and the chill generation amount evaluation point is 2.

When the carbon content of the spheroidal graphite cast iron was changed, spheroidal graphite cast iron corresponding to the changed carbon content was actually cast to correspond to the state of spheroidal graphite or the chill state in the actual structure. A graph showing the relationship between the chill occurrence evaluation point M and the chill prediction parameter P, that is, a characteristic line K is created. When the chill prediction parameter P generated by chill or the value of the chill occurrence evaluation point M is output in the chill prediction process described above, the chill indicates the cooling rate of the cavity of the portion of the mold such as a sand mold or a mold where chill is generated. A cooling rate adjusting step is performed to adjust the generation.

After that, a molten metal casting step is carried out in which the cavity of the mold is charged with a high temperature molten spheroidal graphite cast iron, cast, and solidified to obtain a spheroidal graphite cast iron casting in which chill is reduced or avoided. As described above, according to the present embodiment, the chill prediction parameter P based on the graphite nucleation rate Vc in the molten spheroidal graphite cast iron is used to predict the chill generation amount in the spheroidal graphite cast iron according to the chill prediction parameter P. According to this method, since the chill prediction parameter P correlates with the chill generation amount, the chill generation amount in the spheroidal graphite cast iron when the molten metal is actually poured can be predicted effectively.

Further, according to the present embodiment, when the solid fraction F of the molten spheroidal graphite cast iron is in the region of 0 <F <1, the chill prediction parameter P and the chill occurrence are obtained because the chill prediction parameter P is obtained. The correlation with the amount is further improved, and the amount of chill formation in spheroidal graphite cast iron when actually pouring is predicted effectively. As described above, according to the present embodiment, the amount of chill formation can be effectively predicted, so that it is possible to improve the point that is largely dependent on the trial and error as in the conventional case. Therefore, it is advantageous to perform an appropriate chill generation operation when the chill is used to accelerate the cooling rate of the molten metal to positively generate chill. Alternatively, it is advantageous to perform an appropriate chill suppressing operation when the cooling rate is slowed by positively suppressing the chill by increasing the heat insulating property of the mold.

In addition, the solid phase ratio change ΔF is ΔF = (θ ² ×
According to the present embodiment in which Δt / constant) is set, it is advantageous to obtain an appropriate value of the chill prediction parameter P even when there is a temperature recovery due to latent heat. It is confirmed by the test by the person. According to the above-described embodiment, as can be understood from step S10 shown in FIG. 2, whether the solid phase ratio F exceeds 0 and is less than 1, that is, whether the solid phase and the liquid phase are mixed. It is judged whether or not 0 <F
If <1, the process proceeds to step S12 and the chill prediction parameter calculation process is executed, but instead of this, in step S10, the temperature of the molten metal is equal to or lower than the metastable eutectic temperature TLJ and the solidification completion temperature. (FT: Final
It is also possible to determine whether or not (Temperature = temperature when the solid fraction is 1) or more, and if YES, proceed to step S12.

Here, TLJ is a value obtained based on TLJ = 11104.0 + 9.8 × (% C−1.23 ×% Si−3.0 ×% P). ○ Next, the derivation form of the above-mentioned arithmetic expression is as follows (A) (B)
Will be explained. (A) Chill prediction parameter P The chill prediction parameter P is based on the equation (1). Chill prediction parameter P≡Σ (constant × graphite nucleation rate Vc × Δt) (1) where Δt is a thermal calculation time step [s in the difference method
ec]. The graphite nucleation rate Vc in the equation (1) was based on the equation (2). Graphite nucleation rate Vc≡constant × exp (−E / (R · T)) (2) where R is a gas constant and E is a graphite critical nucleation energy [J]. This graphite critical nucleation energy E was based on the equation (3).

Graphite critical nucleation energy E [J] = (16 · π) / (3 · γ ³ ) / (Gv ² ) ≈constant 1 / θ ² (3) where Gv is the solidification energy per unit volume− Amount of change [J
/ Cm ³ ], which is based on the equation (4). Gv = (θ / TLI) · (latent heat of solidification per unit volume) ≈constant × θ ... (4) where γ: surface tension energy− [J / cm ² ] ≈constant (5) θ is supercooling , (TLI-T), and TLI: metastable equilibrium eutectic temperature (= 1154.4 + 6.5).
X% Si [° C]) T: Element temperature [° C] dF / dt≅constant × θ ² (6) Therefore, the above-mentioned graphite critical nucleation energy E can be converted into the equation (7).

Graphite critical nucleation energy E [J] ≈constant × 1 / (dF / dt) (7) Therefore, the above equation (1) can be converted into equation (8). Chill prediction parameter P = Σ [[exp {-[constant / (dF / dt)] / [R · T]}] × Δt] (8) (B) Temperature calculation during solidification of molten metal Δt [sec] The form of deriving the temperature T (t + Δt) of the subsequent molten metal is as follows. The temperature T (t + Δt) is (9)
Based on the formula.

T (t + Δt) = T ′ (t + Δt) + ΔT (9) T ′ (t + Δt) is Δt [sec] calculated from the heat transfer equation f when latent heat is ignored. It shows the temperature of the molten metal. ΔT represents the recovery temperature due to latent heat and is based on the equation (10). Recovery temperature due to latent heat ΔT = ΔQ / ρ = ΔF × Q / ρ (10) where ΔQ is the latent heat generated during Δt [sec],
ρ represents the specific heat [J / mol / k], Q represents the total latent heat [J / mol] generated until the liquid phase is completely solidified,
ΔF represents a change in the solid phase ratio F, that is, a change in the solid phase ratio.

The solid phase ratio change ΔF is based on the equation (11). Solid phase change ΔF = θ ² × Δt / constant (11) Here, constant = Σ (θ × Δt) = 35125.0 (based on experimental value) (12) Therefore, the above equation (9) ), T (t + Δt) = T ′ (t + Δt) + θ ² × Δt × constant (13) According to the prior art, in general, the solid phase change ΔF is (1
It is based on equation 4). Change in solid fraction ΔF = [{liquidus temperature− (liquidus temperature−solidus temperature) × F (t)} − T ′ (t + Δt)] × specific heat / total latent heat (14) As described above, according to the conventional technique, T ′ (t + Δt) located in the numerator of Expression (14) is calculated from time (t) to time (t + Δt).
It means the temperature ignoring the latent heat when the temperature is lowered to t). As described above, according to the solid-phase-ratio change ΔF according to the conventional technique, the latent heat at the time of supercooling (at the time of chill generation) is ignored. The recovery temperature ΔT due to the latent heat when cold (when a chill occurs) is taken into consideration. Block Diagram FIG. 7 shows a block diagram according to the above embodiment. As shown in FIG. 7, the pouring temperature data from the molten metal temperature setting means is inputted to the heat transfer type temperature calculating means through the above-mentioned molten metal flow calculating processing. Then, the temperature calculation means obtains the temperature T'ignoring the latent heat. Further, data relating to the Si content that affects the TLI value is input from the Si content setting means to the supercooling degree calculating means. Degree of supercooling of molten metal θ
Is required. The degree of supercooling θ is input to the solid-phase-ratio change calculating means, and the solid-phase-ratio change ΔF is obtained.

The temperature T'ignoring the latent heat, the recovery temperature ΔT due to the latent heat, and the solid fraction change ΔF are input to the temperature calculating means during solidification. The temperature T of the molten metal at the time (t + Δt) considering the latent heat recovery is calculated by the temperature calculating means during solidification.
(T + Δt) is obtained. When the solid-liquid coexistence determining means determines that the solid-liquid coexistence state is present, a start command for starting the parameter arithmetic processing is input to the chill prediction parameter arithmetic means.

The graphite critical nucleation energy E obtained from the graphite critical nucleation energy calculating means and the graphite nucleation rate Vc obtained from the graphite nucleation rate calculating means are input to the chill prediction parameter calculating means. Then, the chill prediction parameter P obtained from the chill prediction parameter calculation means
Is converted into a chill occurrence amount evaluation point M by the determination means, and the chill prediction parameter P is output together with the chill occurrence amount evaluation point M to output means such as a display or a printer.

(Supplementary Note) The following technical idea can be understood from the above-described embodiments. -Appendix 1 The temperature T'ignoring the latent heat is calculated by the heat transfer type temperature calculating means, the solid fraction change ΔF is calculated by the solid fraction change calculating means, and the recovery temperature ΔT is calculated by the latent heat recovery temperature calculating means. The temperatures T ′, ΔF, and ΔT are input to the temperature calculating means during solidification, and the solid-liquid coexistence determining means determines whether the molten metal is in the solid-liquid coexisting area. The method according to claim 1, wherein the chill prediction parameter P is obtained by means. -Appendix 2 Graphite critical nucleation energy-E is calculated by the graphite critical nucleation energy calculating means, and graphite nucleation rate Vc is calculated by the graphite nucleation rate calculating means. The method according to claim 1, wherein the chill prediction parameter P is obtained by the chill prediction parameter calculation means based on both Vc. Supplementary Note 3 A melt temperature setting means for inputting the melt temperature data, and a heat transfer type temperature calculating means for calculating the melt temperature T ′ ignoring latent heat by a heat transfer method based on the melt temperature data. The temperature T'ignoring the latent heat obtained by the heat transfer type temperature calculating means, and the solid fraction change Δ calculated by the solid fraction change calculating means
F, the temperature T during solidification in consideration of latent heat recovery, based on the recovery temperature ΔT obtained by the recovery temperature calculation means by latent heat
A solid-liquid temperature calculating means for obtaining (t + Δt) and whether or not the solid-liquid coexistence state is determined based on the solid phase ratio F, and a start command for outputting a chill prediction parameter in the solid-liquid coexistence state is output. Coexistence state determining means, graphite critical nucleation energy calculating means for determining graphite critical nucleation energy-E, graphite nucleation rate calculating means for determining graphite nucleation rate Vc, and graphite critical when a start command is issued. A chill prediction parameter calculation means for obtaining a chill prediction parameter P based on the nucleation energy E and the graphite nucleation rate Vc, and a chill generation amount evaluation point according to the value of the chill prediction parameter P obtained from the chill prediction parameter calculation means. Judgment means for judging M, chill prediction parameter P, and chill occurrence amount evaluation point M
A chill predicting device for spheroidal graphite cast iron, comprising: (Appendix 4) When the metastable eutectic temperature is TLI, the temperature including the temperature recovery due to latent heat is T, and the degree of supercooling is θ, the degree of supercooling θ is calculated by the supercooling degree calculating means (θ = TLI -T) The method according to claim 1 defined by (Appendix 5) The method according to Appendix 4, wherein the solid fraction change ΔF is set to a value proportional to θ ^2, where the degree of supercooling is θ. Supplementary Note 6 A chill prediction parameter P is calculated based on at least one of the number of graphite nucleation and the rate of graphite nucleation in the molten spheroidal graphite cast iron, and the chill generation amount is predicted in the spheroidal graphite cast iron according to the chill prediction parameter P. When the prediction step and the value of the chill prediction parameter P generated by chill in the chill prediction step are output, a cooling rate adjustment step of adjusting the cooling rate of the cavity of the portion of the mold where chill is generated is performed, and then the mold The spheroidal graphite cast iron casting is characterized in that the cavity is filled with molten spheroidal graphite cast iron, cast, and solidified to obtain a spheroidal graphite cast iron casting in which chill is reduced or avoided Casting method.

In the cooling rate adjusting step described above, the cavity in the portion where the chill is generated is made thicker to delay the cooling rate of the molten metal, and the shape of the cavity in the portion where the chill is generated is changed to cool the molten metal. The shape is changed to delay the speed, the radius of curvature of the cavity of the portion where the chill is generated is increased to delay the cooling rate of the molten metal, and the molten metal pool is formed at a position corresponding to the portion where the chill is generated. At least one of forming a molten metal pool portion that delays the cooling rate of the molten metal at a position, and disposing a heat insulating material at a position corresponding to the portion where the chill is generated to delay the cooling rate of the molten metal at the position.

This casting method is advantageous in obtaining a sound spheroidal graphite cast iron casting in which chill is reduced or avoided.

[Brief description of drawings]

FIG. 1 is a graph schematically showing a cooling curve of spheroidal graphite cast iron.

FIG. 2 is a flowchart of a main routine executed by a computer.

FIG. 3 is a flowchart of a temperature calculation processing subroutine.

FIG. 4 is a flowchart of a chill prediction parameter calculation process.

FIG. 5 is a graph showing a correlation between a chill prediction parameter and a chill generation amount evaluation point.

FIG. 6 is a diagram showing a relationship between a metal structure of spheroidal graphite cast iron and an evaluation point of chill generation amount by an optical microscope.

FIG. 7 is a block diagram according to an embodiment.

─────────────────────────────────────────────────── --Continued from the front page (56) Reference JP-A-7-276036 (JP, A) JP-A-8-333650 (JP, A) JP-A-8-122324 (JP, A) JP-A-7- 113771 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) B22D 27/20 B22D 46/00

Claims (2)

(57) [Claims] 1. A black Namarikaku generation speed that put the molten spheroidal graphite cast iron
A chill prediction method for a spheroidal graphite cast iron structure, characterized in that a chill prediction parameter is obtained based on a degree , and a chill generation amount in the spheroidal graphite cast iron is predicted according to the chill prediction parameter. 2. A solid phase ratio of the molten spheroidal graphite cast iron is defined as F, and 0
<When F <1, obtains a chill prediction parameters based on the put that black Namarikaku product <br /> speed in spherical graphite cast iron, a chill emissions for the spherical graphite cast iron according to the chill prediction parameters A method for predicting chill in a spheroidal graphite cast iron structure characterized by predicting. Here, F = 0 means only the liquid phase.
Taste, F = 1 means the state of solid phase only.