Method for predicting martensitic transformation rate and method for setting processing condition
Abstract
A method for predicting a martensitic transformation rate and a method for setting processing conditions capable of improving the accuracy of a prediction of a martensitic transformation rate when a steel material is subjected to deformation processing as well as to heat treatment are provided. A method for predicting a martensitic transformation rate according to an embodiment includes predicting a rate of a transformation to a martensitic phase that appears when a steel material is subjected to deformation processing as well as to heat treatment in which a temperature of the steel material is changed, in which a martensitic transformation rate Vm is calculated by using a prediction formula, the method further including identifying parameters m and n of the prediction formula, and calculating the martensitic transformation rate at a predetermined temperature and a predetermined strain rate by using the prediction formula into which the identified parameters are substituted.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A method for predicting a martensitic transformation rate comprising predicting a rate of a transformation to a martensitic phase that appears when a steel material is subjected to deformation processing as well as to heat treatment in which a temperature of the steel material is changed, wherein a martensitic transformation rate V m in calculated by using a below-shown Expression (1):
V
n
=
(
1
-
V
α
-
V
p
-
V
β
)
[
{
1
-
exp
[
-
0
.
0
1
1
(
M
S
-
T
)
]
}
+
α
·
∑
i
=
t
o
t
n
(
ɛ
.
i
ɛ
*
)
n
]
·
(
ρ
ρ
0
)
m
(
1
)
where: V α is a ferrite rate; V p is a pearlite rate; V β is a bainite rate; and M S satisfies a below-shown Expression (2):
M S =550−350×[C]%−40×[Mn]%−35×[V]%−20×[Cr]% (2)
where: T is a temperature in the heat treatment; ε i with a dot (i.e., ε i with “⋅” added thereon) is a strain rate of the steel material; ε* is a normalization constant; t 0 is a start time of the deformation processing; t n is an end time of the deformation processing; ρ is an average dislocation density of the steel material; ρ 0 is an initial dislocation density of the steel material; and α, m and n are parameters.
2 . The method for predicting a martensitic transformation rate according to claim 1 , comprising:
identifying the parameters α, m and n of the Expression (1); and
calculating the martensitic transformation rate at a predetermined temperature and a predetermined strain rate by using the Expression (1) into which the identified parameters α, m and n are substituted.
3 . The method for predicting a martensitic transformation rate according to claim 2 , wherein the identifying the parameters α, m and n of the Expression (1) comprises:
obtaining a measured value of the martensitic transformation rate by performing a compression test of the steel material;
calculating the martensitic transformation rate from the Expression (1) in which the parameters are changed; and
comparing the measured value with the calculated value, and identifying, as the parameters α, m and n of the Expression (1), parameters with which an error between the measured value and the calculated value falls within a predetermined range.
4 . A method for setting a processing condition, comprising setting a temperature and a strain rate at the time when the steel material is subjected to the deformation processing by using the method for predicting a martensitic transformation rate according to claim 2 so that the resultant steel material has a predetermined martensitic transformation rate.
5 . The method for setting a processing condition according to claim 4 , wherein
the steel material is a material for a gear, the deformation processing is performed by a rotating die, and when the strain rate is set, a rotation condition of the die for forming a predetermined part of the gear is set.Join the waitlist — get patent alerts
Track US2020224289A1 — get alerts on status changes and closely related new filings.
We store only your email — no account needed. See our privacy policy.