Table Of ContentQuench Al.qxp 4/27/2009 2:26 PM Page 1
QUENCHING FUNDAMENTALS
QUENCHING OF
:
ALUMINUM ALLOYS
PROPERTY PREDICTION BY QUENCH FACTOR ANALYSIS
Quench factor analysis During solutionizing of alu- quenching process. The objective is to
minum alloys, the alloying el- quench sufficiently fast to avoid the
(QFA) is a method used to
ements are dissolved in the undesirable concentration of alloying
predict the properties of aluminum lattice structure of elements in the defect and grain
the solid solution, and the ob- boundary structure while at the same
heat treatable aluminum jective is to maximize the concentra- time, not quenching faster than neces-
alloys from cooling tion of these elements, which include sary to minimize residual stresses,
copper, zinc, magnesium, and silicon which may lead to excessive distortion
(time-temperature) curves. in the solid solution[1]. The concentra- or cracking[2, 3]. After quenching, the
tion and rate of dissolution of these el- aluminum alloy is aged. During the
Although the QFA
ements in the solid solution increase aging process, hardening elements pre-
procedure has evolved since with increasing temperature. cipitate in localized areas, which sig-
The aluminum alloy is cooled after nificantly increases the strength of the
its original introduction, the
solutionizing. If cooling is too slow, the part.
original procedure alloying elements diffuse through the Fink and Willey performed an ex-
solid solution and concentrate at grain tensive study on the effects of quench-
continues to be successfully
boundaries, large voids, undissolved ing on the strength of 7075-T6[4]using
used for prediction of yield particles, and other “defect” locations. isothermal quenching techniques. This
The diffusion process is slower for was done by constructing C-curves
and tensile strength,
some alloys than others, thus permit- (Fig. 1), which are plots of times re-
corrosion and other ting slower cooling rates during quired to precipitate sufficient alloy
quenching. For optimal properties, it content to change the strength by a
properties.
is desirable to retard this diffusion certain amount. They identified the
process and maintain the alloying el- critical temperature range; the range
ements in solid solution. For quench- that provided the highest precipitation
Patricia Mariane Kavalco hardenable wrought alloys (2xxx, 6xxx, rates[5]. It is important to note that al-
and Lauralice C. F. Canale* and 7xxx, and casting alloys such as though critical solute temperature may
356), this is accomplished by the be identified from a C-curve for an
University of São Paulo
São Carlos, SP, Brazil
George E. Totten, FASM**
Portland State University
Portland, OR
*Member of ASM International
**Member of ASM International and member, Representative drop bottom furnace for heat treating and quenching aluminum alloys. Courtesy of
ASM Heat Treating Society D. Scott MacKenzie, Houghton International Inc.
HEAT TREATING PROGRESS • MAY/JUNE 2009 23
Quench Al.qxp 4/27/2009 2:26 PM Page 2
alloy (for example, 340°C for 7075-T73), (seconds) to cool from 400 to 290°C,
the specific C-curve obtained varies which will yield an average cooling
depending on the property being rate in °C/s. This is the classical ap-
measured[6]. proach upon which most standards for
Various studies were conducted the heat treatment of aluminum alloys
after Fink and Willey’s work to deter- are written. The maximum attainable
mine the relative quench rate sensi- strength properties are dependent on
tivity to yield different properties for the average cooling rate. Generally,
various alloys. Figure 2 illustrates the faster cooling rates provide greater
effect of cooling rate on tensile strength strengths up to a limit.
for different aluminum alloys and tem- The traditional approach for mod-
pers[5]. The average cooling rate tradi- eling quench sensitivity (which refers
tionally has been defined to be the time to the amount age hardening response
is reduced by slow quench cooling) to
quantitatively correlate quenching
448800
cooling rate with mechanical proper-
ties of aluminum alloys presumes a
110000 linear, well-behaved cooling process
442255 9988
9900 between 400 and 290°C. However, this
is seldom the case, and, therefore, the
8800 classical method of determining the
337700
average cooling rate of aluminum al-
hh
ggtt loys may fail when the quenching
nn
ee,, °°CC 331155 mm ssttrree prurpocteedss o irs dneolnayliende aqru, seuncchh iansg a pnr oincetesrs-.
uurr mmuu Therefore, it is desirable to use an al-
eerraatt aaxxii ternative process, quench factor
pp mm
eemm 226600 ooff analysis (QFA), that correlates actual
TT %% cooling pathway by using a cooling
8800 curve (time-temperature curve) of the
220055 9900 actual cooling process throughout the
quenching cycle for the quenching
9988 process and cross section size being
115500 TTeennssiillee ssttrreennggtthh 110000 used with a C-curve (time-tempera-
YYiieelldd ssttrreennggtthh ture-property curve) for the specific
alloy of interest[7,8]. QFAis now used
9933 routinely by many researchers in
00..11 11 1100 110000 11,,000000 the aluminum thermal processing
TTiimmee,, ss industry.
Over the approximately 25 years
Fig. 1 —C-Curves illustrating the effect of alloy precipitation on tensile strength for 7075-T6 generated by
Fink and Willey. since QFAwas introduced, the original
model has undergone considerable
AAvveerraaggee ccoooolliinngg rraattee ((440000 ttoo 229900°°CC)),, °°CC//ss evolution and improvement. The ob-
110000 11 1100 110022 110033 110044 jective here is review the classical
model, which still has a great deal of
77117788-TT66 utility as it exists, and to highlight
9900 660000 some potential limitations.
77007755-TT66
Discussion
8800 77005500-TT7733
77005500-TT7733 Avrami used isothermal kinetics to
eennggtthh,, kkssii 7700 2222000022114444--TTTT4466 550000 nnggtthh,, MMPPaa suetroutuidesys c tooroaf lnianslgfuo pmrmrionacuetismosne s ad[9lu,l1o0r]yi.n Tsg h acero epn rtodipne---
nnssiillee ssttrr 6600 66007700-TT66 440000 ssiillee ssttrree pperencdipenitta tioonn ththea ta moocucunrts ofd uarlilnoyg
TTee eenn cooling, regardless of the cooling
TT
5500 pathway. The Avrami Equation for
66006611-TT66 330000 isothermal precipitation kinetics is[5]:
4400
(1)
3300 220000 where ζ = fraction of precipitation
11 1100 110022 110033 110044 110055 which has occurred in time tduring
AAvveerraaggee ccoooolliinngg rraattee ((775500 ttoo 555500°°FF)),, °°FF//ss
the quench, and k = temperature-in-
Fig. 2 —Tensile strength as a function average cooling rate for different aluminum alloys and tempers. dependent constant (s). The value of k
24 HEAT TREATING PROGRESS (cid:127) MAY/JUNE 2009
Quench Al.qxp 4/28/2009 1:16 PM Page 3
depends on the degree of supersatu-
555500
ration and the rate of diffusion, and
is determined from the following 550000
equation developed by Evancho and 445500 ∆ttii CC
TTii
Staley[5]: 440000
CC 335500
ee,, °°
uurr 330000
aatt
(2) eerr 225500
pp
where C = critical time (s) required to mm
T ee 220000
precipitate a constant fraction (the equa- TT
115500
tion of the C-curve), k = a constant that
1 QQ == ∑∆ttii // CC
equals the natural logarithm of the 110000 TTii
fraction untransformed (1 - fraction 5500
defined by the C-curve); if 0.5% is un-
00
transformed, then k = -ln(σ/σmax) = 1100-22 1100-11 110000 110011 110022 110033
1 CCrriittiiccaall ttiimmee,, ss
-0.005013, R= ideal gas constant = 8.3143
J.K-1.mol-1, and T = temperature (K). Fig. 3 —Schematic illustration of the experimental method used for calculating a quench factor.
The values of k – k are determined
2 5
by multiple linear regression analysis ical time (s) from the C-curve and is quench factor by[5,14]:
to obtain the best fit to the CT equation calculated from Eq 5, t = time from the
by repeated iterations until minimum cooling curve (s), t0= time at the start (5)
computational error is obtained[5]. A of the quench (s), and tf = time at the
summary of reported k-values for finish of the quench (s). When Q= 1, where σy= predicted yield strength
yield strength that have reported to the fraction transformed equals the (MPa), σmax = yield strength (MPa)
date are provided in Table 1[11]. fraction represented by the C-curve. after an infinite quench (and aging
From these relationships, it is pos- By the Rule of Additivity, the temper- cycle), e = base of the natural loga-
sible to redefine the equation for the ature-time curve is divided into a se- rithm, K1= -ln(0.995) = -0.00501, and
amount of solute precipitated during ries of isothermal time steps as de- Q = quench factor. This relationship is
the quench which is called the quench scribed by Evancho and Staley[5]. For shown graphically in Fig. 4 for the
factor, traditionally designated as “Q”. each time step, the volume fraction of yield strength of 7075-T73.
Cahn showed that transformations the new phase that is formed during In their 1974 paper, Evanco and
that nucleate heterogeneously, such as this time step is calculated by isothermal Staley showed that from the Avrami
aluminum alloys, obey the Rule of Ad- kinetics using the Avrami Equation. This Equation, the attainable strength
ditivity, which states that reactions are is shown in Fig. 3, where the quench is a function of the amount of
additive and therefore transformation factor Qis obtained by combining the solute remaining in solution after
kinetics for nonisothermal conditions, cooling curve for the quenching process the quench and is related to k as
1
such as those that would be present with the C-curve and the value for Qis follows[5]:
during a typical quenching process obtained by[5,13]:
may be described by[12]: (6)
(3) (4) where σ = 0.995 × σ .
x max
The maximum and minimum al-
where: Q= measure of the amount In the original classical approach, lowable values may be determined ex-
transformed (quench factor), C = crit- properties were predicted from the perimentally, or values obtained from
T
Table 1 —Coefficients for Calculating Quench Factors at 99.5% of Attainable Yield Strength
Alloy k(a) k, s k, J/mol k, K k, J/mol Calculated range, °C Ref.
1 2 3 4 5
7010-T76 -0.00501 5.6 ×10-20 5780 897 1.90 ×105 425-150 20
7050-T76 -0.00501 2.2 ×10-19 5190 850 1.8 ×105 425-150 5
7075-T6 -0.00501 4.1 ×10-13 1050 780 1.4 ×105 425-150 5
7075-T73 -0.00501 1.37 × 10-13 1069 737 1.37 ×105 425-150 21
7175-T73 -0.00501 1.8 × 10-9 526 750 1.017×105 425-150 12
2017-T4 -0.00501 6.8 × 10-21 978 822 2.068×105 425-150 21
2024-T6 -0.00501 2.38 × 10-12 1310 840 1.47 ×105 425-150 22
2024-T851 -0.00501 1.72 ×10-11 45 750 3.2×104 425-150 23
2219-T87 -0.00501 0.28 × 10-7 200 900 2.5 ×104 425-150 24
6061-T6 -0.00501 5.1 × 10-8 412 750 9.418×104 425-150 21
356-T6 -0.0066 3.0 × 10-4 61 764 1.3 ×105 425-150 25
357-T6 -0.0062 1.1 × 10-10 154 750 1.31 ×105 425-150 25
Al-2.7Cu-1.6Li-T8 -0.0050 1.8 × 10-8 1520 870 1.02 ×105 425-150 25
(a) k1is a unitless value that corresponds to the unprecipitated fraction. For this analysis, it is usually 0.995 and ln 0.995 = -0.00501.
HEAT TREATING PROGRESS • MAY/JUNE 2009 25
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Table 2 —Relationship between quench factor and yield strength in 7075-T73(a)
Quench Attainable Predicted Quench Attainable Predicted
factor (Q) yield strength, % yield strength, MPa Factor (Q) yield strength, % yield strength, MPa
0.0 100.0 475.1 26.0 87.8 417.2
2.0 99.0 470.2 28.0 86.9 413.0
4.0 98.0 465.4 30.0 86.0 408.9
6.0 97.0 461.3 32.0 85.2 404.7
8.0 96.1 456.5 34.0 84.3 400.8
10.0 95.1 451.6 36.0 83.5 396.5
12.0 94.2 447.5 38.0 82.7 393.0
14.0 93.2 442.7 40.0 81.8 388.9
16.0 92.3 438.5 42.0 81.0 384.7
18.0 91.4 434.4 44.0 80.2 381.3
20.0 90.5 429.6 46.0 79.4 377.2
22.0 89.6 425.4 48.0 78.6 373.7
24.0 88.7 421.3 50.0 77.8 369.6
(a) σmax= 475.1 MPa
used for high-strength alloys because
660000
σ << σ [4]. Staley, et.al., also sub-
min max
sequently stated that this assumption
for σ was made because the strength
min
550000 of aluminum alloys held for infinitely
66 44445544 443333443311335544332222339988223388221111224422113344990011661111113333883355 ltounreg wtimouelsd b beleo zwe rtoh[e16 s].o lFvuurst hteemrmpeorrae-,
this simplification was validated by
440000 2299
PPaa 3377 the excellent fit that the simplified
MM
hh,, value for k1provided for C-curve data
ggtt 2244 developed for 7075-T6 and 2024-T4[5].
nn 330000 1111
dd SSttrree 3344 Fporor vmidanesy ainddeuqustaritael raepspullitcsa wtiohnesn, tthhies
YYiieell σyy == σmmaaxxeeKK11QQ loss in properties is less than 10%[15].
220000 However, Swartzendruber, et.al., sub-
sequently recommended that Eq 6 was
necessary to minimize predictive
errors[17].
110000
From these equations, a number of
observations are made regarding the
quenching process showing the power
00 of QFAin quench process design and
11 1100 110022 110033
QQuueenncchh ffaaccttoorr ((QQ)) analysis:
(cid:127) Low values of Qare associated
Fig. 4 —Yield strength of aluminum 7075-T73 as Mil Handbook 5may be used to obtain with high quench rates, minimum pre-
a function of quench factor of the material.
an estimation of the property of in- cipitation during cooling and high
terest under the experimental yield strengths.
quenching conditions. Table 2 shows (cid:127) Conversely, higher Q-values are
the relationship between quench factor obtained with slower quench rates and
and yield strength for 7075-T73 re- are associated with lower strength
ported previously[8]. values.
When Evancho and Staley analyzed (cid:127) An alloy with a low rate of precip-
7075-T6 and 2024-T4 interrupted itation will produce a lower quench
quenching data previously published factor Qthan an alloy with a high pre-
by Fink and Willey, they obtained a cipitation rate at the same cooling rate.
linear correlation for log (σ/σ ) (cid:127) Quench factors calculated for dif-
min
versus isothermal holding time, and ferent alloys might be different even if
the slope was equal to 1.Therefore, similar section sizes are cooled in the
they set σ = 0 in Eq 9 to predict the same quenchant, because quench fac-
min
extent of transformation in their early tors take into account individual alloy
work[5,15]. In their 1974 paper, Staley precipitation kinetics by means of the
and Evancho further noted that the equation describing the C-curve (C
T
simplified equation for k could be function) for each alloy.
1
26 HEAT TREATING PROGRESS (cid:127) MAY/JUNE 2009
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(cid:127) Solute elements are precipitated IInnsseerrtt hhaannddllee ffuullll ddeepptthh
during cooling from the solution WWeelldd wwaatteerr ttiigghhtt
treating temperature at high Q-values.
As a consequence, an improperly
quenched alloy may not properly 2255..44 mmmm
harden during aging, and it may be
susceptible to intergranular corrosion,
5500 mmmm
stress corrosion, or exfoliation.
The quench factor provided by a 110000 mmmm
particular quenchant or quenching
process can be determined experimen- Fig. 5 —Aluminum bar probe (a) and aluminum
tally by using parts, or sheet, bar, or sheet probe (b)
plate probes instrumented with ther-
culated data for some coefficients[19].
mocouples such as those illustrated in
Fig. 5. The time-temperature data ob-
Conclusions
tained upon immersion of the solution-
To achieve the ideal quench, low
PPrroobbee hhaannddllee
ized instrumented probe (or part) is
values of Qare desirable because they
collected using a data-acquisition
are associated with high quench rates,
system. The time step used in the
minimum precipitation during cooling, TThheerrmmooccoouuppllee
above calculation for Qis typically as-
and high yield strengths. High values wwiirree wweellddeedd
sumed to be the data collection fre- of Q can lead to an improperly WWaatteerr ttiigghhtt ttoo sshheeeett cceenntteerr
quency. The effect of the time step on
quenched alloy that may not properly
the Q-value is shown in Table 3[8].
harden during aging and may be sus-
Although QFAhas been, and con-
ceptible to intergranular corrosion,
tinues to be, used successfully for prop-
stress corrosion, or exfoliation.
erty prediction of heat treatable alu-
Classical QFAhas been used suc-
minum alloys, there are limitations to
cessfully for property prediction of 22 iinn..
the predictive accuracy which include:
heat treatable aluminum alloys. How-
(cid:127) Classical QFAassumes that trans-
ever, there are limitations to the pre-
formational kinetics are described by
dictive accuracy of the classical equa-
a special case of the Avrami Equation
tions, which are attributable to the
where the Avrami coefficient is n= 1.
assumptions made in the theoretical
However, n= 1 is mostly related to for- development. Newer predictive 22 iinn..
mation of non-hardening precipitates
methodologies that address these lim-
within grains during quenching.
itations and expand the potential
(cid:127) By neglecting minimum strength
utility of QFAare being developed
σ in the Avrami Equation, the ability
min and will be reviewed in a subsequent
to successfully predict strength loses
article. HTP
accuracy. As discussed above, Staley
showed that at lower values ofσ/σ ,
max
the predictions are improved by intro- References
ducing σ as a constant related to 1. T. Croucher, Quenching of Aluminum
min
Alloys: What This Key Step Accomplishes,
strength in the absence of hardening
Heat Treating, p 20-21, 1982.
precipitates. The reader is directed to
2. J.C. Chevrier, A. Simon, G. Beck, Optimal
Ref 18 for a rigorous treatment of this
Cooling Rate and Process Control in
approach, which permits the inclusion Metallic Parts Heat Treatment, Heat and
of aging temperature variation, solu- Mass Transfer in Metallurgical Systems, Vol. 9,
tion treatment temperature, and alloy p 535-544, 1981.
composition to be included in the 3. P. Archambault, et, al., AContribution to
model. the 7075 Heat Treatment, Materials Science
(cid:127) Tiryakioglu and Shuey have devel- and Engineering, Vol. 43, p 1-6, 1980.
4. W.L. Fink and L.A. Willey, Quenching of
opeda new QFAmodel that addresses
75S Aluminum Alloy, Trans. AIME, Vol. 175,
many of the deficiencies of the classical
p 414-427, 1948.
model or even the various improve-
5. J.W. Evancho and J.T. Staley, Kinetics of
ments such as establishing process-
Precipitation in Aluminum Alloys During
structure-property relationships, in- Continuous Cooling, Met. Trans., Vol. 5,
cludes multiple quench precipitates, Jan., p. 43-47, 1974.
and utilizes thermodynamic and cal- 6. J.T. Staley, Modeling Quenching of Pre-
Table 3 —Effect of the time step on the quench factor calculated
from a single cooling curve(a)
Time step, s 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
Quench factor 1.19 1.19 1.17 1.14 1.30 1.52 1.53 1.33
(a) 38°C water flowing at 0.25 m/s.
HEAT TREATING PROGRESS (cid:127) MAY/JUNE 2009 27
Quench Al.qxp 4/27/2009 2:26 PM Page 6
cipitation Strengthened Alloys: Applica- AQuench Factor Analysis of the Influence Stress Reduction in 7175-T73, 6061-T6, and
tion to an Aluminum-Copper-Lithium of Water Spray Quenching on the Age- 2017A-T4 Aluminum Alloys Using Quench
Alloy, Ph.D. Thesis, Drexel Univ., 1989. Hardenability of Aluminum Alloys, in Ma- Factor Analysis, J. of Matls Proc. Tech., Vol
7. C.E. Bates, Quench Optimization for Alu- terials Processing in the Computer Age, (R. 153-154, p 346-351, 2004.
minum Alloys, AFS Trans., 93-25, p 1045- Voller, M.S. Stachowicz and B.G. Thomas, 22. D.D. Hall and I. Mudawar, Optimiza-
1054, 1994. Eds.), TMS, p 203-221, 1991. tion of Quench History of Aluminum Parts
8. C.E. Bates and G.E. Totten, Procedure for 16. J.T. Staley, R.D. Doherty, and A.P. Ja- for Superior Mechanical Properties, Intl J.
Quenching Media Selection to Maximize worski, Improved Model to Predict Proper- Heat MassTransfer, Vol. 39, No. 1, p 81-95.
Tensile Properties and Minimize Distortion ties of Aluminum Alloy Products after 1996.
in Aluminum-Alloy Parts, Heat Treatment of Continuous Cooling, Met. Trans. A, Vol. 23. L.K. Ives, et. al., Processing/Microstruc-
Metals, No. 4, p 89-98, 1988. 24A, p 2417-2427, 1993. ture/Property Relationships in 2024 Alu-
9. M. Avrami, Kinetics of Phase Change I, 17. G.E. Totten, G.M. Webster, and C.E. minum Alloy Plates, U.S. Dept. of Com-
Jour. of Chemical Physics, Vol. 7, Feb., p 1103- Bates, Quench Factor Analysis: Step-By- merce, National Bureau of Standards
1112, 1939. Step Procedures for Experimental Deter- Technical Report NBSIR 83-2669, Jan. 1983.
10. M. Avrami, Kinetics of Phase change II, mination, Proc. 1st Intl. Non-Ferrous Pro- 24. L. Swartzendruber, et. al., Nondestruc-
Jour. of Chemical Physics, Vol. 8, Feb., p 212- cessing and Technology Conf., (T. Bains tive Evaluation of Nonuniformities in 2219
224, 1940. and D.S. MacKenzie, Eds.), ASM Intl., Ma- Aluminum Alloy Plate - Relationship to
11. J.W. Cahn, The Kinetics of Grain terials Park, Ohio, p 305-312, Mar. 1997. Processing, U.S. Dept. of Commerce, Na-
Boundary Nucleated Reactions, Acta Met., 18. P.A. Rometsch, M.J. Starink, and P.J. tional Bureau of Standards Technical Re-
Vol. 4, p 449-459, 1956. Gregson, Improvements in Quench Factor port NBSIR 80-2069, Dec. 1980.
12. G.P. Dolan, J.S. Robinson, and A.J. Modeling, Mat. Sci. & Engrg., Vol. A339, p 25. J. Newkirk and D. MacKenzie, The
Morris, Quench Factors and Residual Stress 255-/264, 2003. Jominy End Quench for Light-Weight
Reduction in 7175-T73 Plate, Proc. Matls. 19. M. Tiryakioglu, R.T. Shuey, Quench Sen- Alloy Development, J. Mater. Eng. Perform.,
Solution Conf., Indianapolis, Ind., ASM sitivity of an Al-7% Si-0.6% Mg Alloy: Vol. 9, No. 4, p 408–41, 2000.
Intl., Materials Park, Ohio, p 213-218, 2001. Characterization and Modeling, Met. and
13. C.E. Bates, Predicting Properties and Matls. Trans. B, Vol. 38B, p 575-582, Aug. For more information: George Totten,
Minimizing Residual Stress in Quenched 2007. Portland State University, Department of
Steel Parts, Jour. of Heat Treatment, Vol. 6, p 20. R.J. Flynn and J.S. Robinson, The Ap- Mechanical and Materials Engineering,
27-45, 1988. plication of Advances in Quench Factor Portland, Oreg.; tel: 206-788-0188; e-mail:
14. Quench Factor Analysis in Aluminum Analysis Property Prediction to the Heat [email protected]; or Lauralice C.F. Canale,
Properties and Physical Metallurgy, (J.E. Treatment of 7010 Aluminium Alloy, Jour. University of São Paulo, Department of
Hatch, Ed.), ASM Intl., Materials Park, of Matls. Proc. Tech., Vol. 153-154, p 674–680, Materials, Aeronautical and Automobile
Ohio, p 159-164, 1984. 2004. Engineering, School of Engineering, São
15. J-S. Kim, R.C. Hoff, and D.R. Gaskell, 21. G.P. Dolan and J.S. Robinson, Residual Carlos, SP, Brazil; e-mail: [email protected].
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Moline, IL Black Hawk College JUN 9-11
Orlando, FL University of Central Florida TBA
www.asmfoundation.org Pittsburgh, PA MS&T 2009 OCT 27-28
28 HEAT TREATING PROGRESS (cid:127) MAY/JUNE 2009
