processing map of as-cast 7075 aluminum alloy for …abstract the true stress–strain curves of...
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Chinese Journal of Aeronautics, (2015), 28(6): 1774–1783
Chinese Society of Aeronautics and Astronautics& Beihang University
Chinese Journal of Aeronautics
Processing map of as-cast 7075 aluminum alloy
for hot working
* Corresponding author. Tel.: +86 29 88460212 801.
E-mail address: [email protected] (H. Yang).
Peer review under responsibility of Editorial Committee of CJA.
Production and hosting by Elsevier
http://dx.doi.org/10.1016/j.cja.2015.08.0021000-9361 � 2015 Production and hosting by Elsevier Ltd. on behalf of CSAA & BUAA.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Guo Lianggang a, Yang Shuang a, Yang He a,*, Zhang Jun b
aState Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an 710072, ChinabChina National Heavy Machinery Research Institute Co. Ltd, Xi’an 710032, China
Received 24 June 2015; revised 14 July 2015; accepted 2 August 2015Available online 28 August 2015
KEYWORDS
As-cast 7075 aluminum
alloy;
Hot compression test;
Hot working;
Processing map;
Processing window
Abstract The true stress–strain curves of as-cast 7075 aluminum alloy have been obtained by
isothermal compression tests at temperatures of 300–500 �C and strain rates of 0.01–10 s�1. The
plastic flow instability map is established based on Gegel B and Murthy instability criteria because
the deformed compression samples suggest that the combination of the above two instability criteria
has more comprehensive crack prediction ability. And the processing map based on Dynamic Mate-
rial Model (DMM) of as-cast 7075 aluminum alloy has been developed through a superposition of
the established instability map and power dissipation map. In terms of microstructure of the
deformed samples and whether plastic flow is stable or not, the processing map can be divided into
five areas: stable area with as-cast grain, stable area with homogeneous grain resulting from
dynamic recovery, instability area with as-cast grain, instability area with the second phase and
instability area with mixed grains. In consideration of microstructure characteristics in the above
five areas of the processing map, the stable area with homogeneous grain resulting from dynamic
recovery, namely the temperatures at 425–465 �C and the strain rates at 0.01–1 s�1, is suggested
to be suitable processing window for the as-cast 7075 aluminum alloy.� 2015 Production and hosting by Elsevier Ltd. on behalf of CSAA & BUAA. This is an open access
article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
The 7075 aluminum alloy has been widely used in aerospaceand automobile industries because of its excellent properties
such as light weight, high strength and high stress corrosion
resistance.1 In order to shorten the process, the as-cast 7075aluminum alloy is directly used as billet in some hot workingprocesses such as extrusion. The short-process hot working
technology based on as-cast billet will greatly save energyand lower the cost by avoiding long preforming process formanufacturing forging state billet. However, it is well-known
that the as-cast 7075 aluminum alloy is such sensitive to defor-mation temperature and strain rate that it has pretty narrowforming window due to the dendrite and the second phase inas-cast structure.2,3 Especially, the alloy is very easy to crack
during hot plastic deformation. Therefore, a fundamentaland important issue for planning and optimizing hot workingprocesses based on as-cast 7075 aluminum alloy billet is to
Processing map of as-cast 7075 aluminum alloy for hot working 1775
establish its hot processing map, which can be used to describehot workability of the alloy and determine suitable processingwindow with preferable microstructure and free from forming
defects such as crack.The processing map based on Dynamic Material Model
(DMM) is an important method which is usually used to
describe the response relationship between workability andprocessing parameters, thus having a great significance in plan-ning and optimizing hot working processes in practice.4,5 Lin
et al.6 established the hot processing map of as-forged 7075aluminum alloy based on DDM using Prasad instabilitycriterion by isothermal compression tests and determined theoptimum hot working area by analyzing the deformed
microstructures in different areas in the processing map. Yanget al.7 established the hot processing map of as-extruded 7075aluminum alloy and found out the influences of loading direc-
tion to the axis of extruded 7075 aluminum alloy bar on theflow stress behavior. Taheri-Mandarjani et al.8 studied theductility behavior of extruded 7075 aluminum alloy using the
tensile testing method. Yan et al.9 investigated the flow stressbehavior and microstructural evolution of Al–6.2Zn–0.70Mg–0.3Mn–0.17Zr alloy during the hot deformation process
using hot compression test. Mirzadeh10 explored the hot work-ing behavior of 7075 aluminum alloys and establishedphysically-based constitutive equations for this material. Usingthe developed processing map based on flow localization
parameter, Jenab and Taheri11 revealed the thermomechanicalbehavior of as-extruded 7075 aluminum alloy and obtained thereasonable range of deformation temperature and strain rate
by analyzing the deformed microstructure of different areasin the processing map. But the above studies all focus ondeformed aluminum alloy which has obvious different hot
deformation behavior compared with as-cast aluminum alloy.So the motivation of this work is to establish processing mapof as-cast 7075 aluminum alloy during hot plastic deformation
based on DMM, consequently to provide a basis for planningand optimizing some advanced shot-process metal formingprocesses such as profile extrusion based on as-cast billet.
In this work, firstly, the true stress–strain curves under dif-
ferent deformation conditions have been obtained by thermalcompression tests on Gleeble thermal simulator. Secondly,the appropriate instability criterion is selected according to
the crack prediction ability, then we establish the hot process-ing map of as-cast 7075 aluminum alloy-based DMM model.Lastly, a suitable working window for as-cast 7075 aluminum
alloy has been suggested through analyzing the deformedmicrostructure of different deformation areas in the processingmap.
2. Experimental
The experimental material used is the industrial 7075 aluminumalloy ingot prepared by the same level hot-top casting whose
chemical compositions are shown inTable 1. The sizes of the usedcylindrical compression specimens, randomly taken from arbi-
Table 1 Chemical compositions of as-cast 7075 aluminum alloy.
Composition Cu Mg Mn Fe
Content (wt%) 1.58 2.51 0.23 0.28
trary positions in the axial direction of the ingot, are 10 mm indiameter and 15 mm in height. The isothermal compression testswere conducted on the Gleeble1500 thermal simulator at temper-
atures of 300–500 �C and strain rates of 0.01–10 s�1 to a heightreduction of 50% (strain is 0.7). The microstructure after defor-mation was observed on Leica DMI3000 M optical microscope.
The initial microstructure of the alloy before compression pre-sents a dendritic network structure with rods’ second phase dis-tributing on the material matrix, as shown in Fig. 1.
3. Results and discussion
3.1. True stress–strain curves
The hot processing map based on DMM is usually established
by a superimposition of power dissipation map and instabilitymap developed from calculating the data of true stress–straincurves.12 Therefore, the true stress–strain curves (see Fig. 2)of as-cast 7075 aluminum alloy at different temperatures (T)
and strain rates have been obtained from the isothermal hotcompression tests in order to establish the hot processingmap of the material. The flow stress increases sharply until a
peak stress with the increase of the strain at the early deforma-tion stage, and then slightly decreases as a result of thedynamic softening. And the flow stress increases with decreas-
ing the deformation temperature and increasing the strain rate.And it can be seen from Fig. 2(d) that the stress–strain curvesappear fluctuation when the temperature is higher than 350 �C.This may be the result from combined action of the secondphase particles’ strengthening and dynamic recovery softening.
Fig. 3 shows the true stress–strain curves of as-forged 7075aluminum alloy at strain rates of 0.1 and 1 s�1 in Ref.6 Com-
pared with Figs. 2 and 3 shows that the peak stress and the cor-responding strain of as-forged 7075 aluminum alloy are largerthan those of as-cast 7075 aluminum alloy at the same defor-
mation temperature and strain rate. This is because the as-forged alloy usually has higher dislocation density and storageenergy resulting from plastic deformation. Besides, the loose
and inhomogeneous structure of as-cast 7075 aluminum alloyalso leads to the lower strength level.
3.2. Establishment of hot processing map for as-cast 7075aluminum alloy
3.2.1. Power dissipation map
The DMM theory claims that (1) the material under deforma-tion is a nonlinear energy dissipation body; (2) the total energy(P) absorbed by the material can be divided into two parts: the
first part is called dissipation energy (G content) which is usedto produce plastic deformation and another part is called com-plementary dissipation energy (J co-content) which is used to
produce material microstructure evolution. According to theabove theory, the relationship between the total energy P, Jco-content and G content can be expressed as13
Si Zn Cr Ni Ti
0.1 5.75 0.211 <0.001 0.06
Fig. 1 Raw microstructure of as-cast 7075 aluminum alloy.
1776 L. Guo et al.
P ¼ r_e ¼ Gþ J ¼Z _e
0
rd_eþZ r
0
_edr ð1Þ
where r is true stress and _e strain rate. The distribution rela-tionship between J co-content and G content is decided by
the strain rate sensitivity m, which is expressed by
m ¼ @J
@G¼ _e@r
r@ _e¼ @ lnr
@ ln _eð2Þ
Meanwhile, the efficiency factor of power dissipation g isdefined as14
g ¼ 2m
mþ 1ð3Þ
The greater the g value, the better the formed microstruc-ture can be improved, which may lead to dynamic recoveryor dynamic recrystallization and local flow instability.15 The
Fig. 2 True stress–strain curves o
power dissipation map is built by the contour map of g withthe variation of temperature and strain rate. The calculatedvalues of power dissipation efficiency factor at strain of 0.7
from true stress–strain data at different temperatures andstrain rates are shown in Table 2. So the power dissipationmap has been built as shown in Fig. 4. It can be seen that
the efficiency factor g of power dissipation has higher valuesin the temperature range of 400–500 �C and strain rate rangeof 0.01–1 s�1. This indicates that in the above temperature
and strain rate ranges, the as-cast microstructure of 7075aluminum alloy is most possibly improved due to dynamicrecovery or dynamic recrystallization although the local flowinstability may occur.
3.2.2. Instability map
Though the power dissipation map can reflect the microstructure
evolution to some extent under different compression conditions,the adverse micro-mechanism such as dynamic strain aging andadiabatic shear band during the hot working is difficult to bereflected in the power dissipation map. Therefore, it is necessary
to establish the processing instability map by which the workinginstability area of the alloy can be determined.13
In most literature,16–18 only one instability criterion was usu-
ally used to establish the instability map of materials. However,the work carried out in literature19,20 demonstrated that theproper instability criterion should be selected according to
experimental results about unstable plastic flow during hotplastic forming process. Therefore, in consideration of the fea-
f as-cast 7075 aluminum alloy.
Fig. 3 True stress–strain curves of as-forged 7075 aluminum alloy.
Table 2 Possessing map data of as-cast 7075 aluminum alloy.
Temperature (�C) Strain rate (s�1) Power dissipation efficiency factor Value of various instability criteria
g Prasad Murthy Gegel A Gegel B Gegel C Malas
300 0.01 19.763 0.102 0.110 �0.369 �0.093 0.948 �0.002
0.1 17.852 0.015 0.0436 �3.401 �0.314 0.793 �0.021
1 12.606 �0.166 �0.093 �6.774 �0.227 0.751 �0.039
10 4.4669 �0.466 �0.423 �5.204 0.546 0.562 �0.027
350 0.01 17.713 0.210 0.097 4.639 0.093 0.825 0.028
0.1 22.084 0.121 0.175 �0.153 0.068 0.811 �0.001
1 16.44 �0.202 �0.066 �11.028 0.095 0.605 �0.065
10 �0.082 �1.487 �1.011 �12.198 0.168 0.575 �0.061
400 0.01 18.677 0.246 0.221 6.200 0.165 1.080 0.0378
0.1 25.130 0.165 0.008 1.227 �0.320 0.898 0.008
1 20.178 �0.127 �0.012 �11.085 �0.308 0.535 �0.068
10 2.776 �1.796 �0.729 �13.181 0.228 0.407 �0.068
450 0.01 18.055 0.389 0.075 0.099 0.560 1.316 0.075
0.1 31.670 0.255 0.034 4.854 0.218 1.107 0.034
1 26.969 �0.077 0.047 �14.419 0.318 0.909 �0.096
10 1.605 �4.112 �0.874 �20.674 0.843 0.447 �0.106
500 0.01 0.435 11.188 0.002 27.310 4.678 1.823 0.138
0.1 29.677 0.344 0.606 11.562 0.441 2.858 0.080
1 24.713 �0.248 �0.007 �22.072 0.831 3.356 �0.144
10 �20.197 0.845 �14.470 �40.809 5.7801 5.041 �0.170
Processing map of as-cast 7075 aluminum alloy for hot working 1777
ture of being easy to crack of as-cast 7075 aluminum alloy, theappropriate instability criteria have been selected by comparing
the crack prediction ability of different plastic flow instabilitycriteria. And then the instability map of as-cast 7075 aluminumalloy has been established based on the selected instability crite-
ria. The main flow instability criteria are as follows:
(1) Prasad instability criterion
According to the principle of maximum entropy productionrate, Prasad and Seshacharyulu14 gave the following instabilitycriterion expressed by
nð_eÞ ¼ @ lnðm=mþ 1Þ=@ ln _eþm < 0 ð4Þ
So the instability map based on the Prasad instabilitycriterion can be plotted according to the function of nð_eÞcorrelating to temperature and strain rate based on theprocessing map data in Table 2. The area with positive valuesof nð_eÞ in the instability map represents stable area, as shown
in Fig. 5(a).
(2) Murthy instability criterion
For the case of non-constant strain rate sensitivity param-eter m, Murthy and Rao21 proposed the instability criterionwhich is applicable of any type of r–e curves:
2m < g 6 0 ð5Þ
Fig. 4 Power dissipation map at strain of 0.7.
1778 L. Guo et al.
The parameter g is power dissipation efficiency factor. Sothe instability map based on Murthy instability criterion can
be plotted based on the processing map data in Table 2, asshown in Fig. 5(b).
(3) Gegel instability criterion
Gegel22 proposed three instability criteria which are called
Gegel A, Gegel B and Gegel C in this work:
Gegel A:
@g@ lg _e
> 0 ð6Þ
Gegel B:
@s
@ lg _e> 0 ð7Þ
Gegel C:
s ¼ 1
T
@ lg r@ð1=TÞ
� �_e;e
< 1 ð8Þ
The parameter s is temperature sensitivity. So the instabilitymaps based on the Gegel A, Gegel B and Gegel C instabilitycriteria can be plotted based on the processing map data in
Table 2, as shown in Fig. 5(c)–(e), respectively.
(4) Malas instability criterion
Malas and Seetharaman23 proposed another instability cri-terion expressed by
@m
@ lg _e> 0 ð9Þ
So the instability map based on Malas instability criterioncan be plotted according to the processing map data in Table 2,as shown in Fig. 5(f).
In Fig. 5, the points (A–E) represent the deformation con-ditions under which the compressed samples produce cracks asshown in Fig. 6. This indicates that unstable plastic flow occursunder the deformation conditions represented by those points
(A–E).From Fig. 5(a) and (b), we can see that the red point A
locates in stable areas of the instability maps based on Prasad
and Murthy instability criteria. But the unstable plastic flowoccurs under the deformation condition represented by redpoint A because the compressed sample produces crack, as
shown in Fig. 6(a). This indicates that the instability mapsbased on the Prasad and Murthy instability criteria cannotpredict unstable plastic flow under the deformation condition
represented by red point A. For the same reason, the instabilitymap based on Gegel A cannot predict the unstable plastic flowunder the deformation conditions represented by points B, C,
D and E (Fig. 5(c)); the instability map based on Gegel Bcannot predict the unstable plastic flow under the deformationcondition represented by red point E (Fig. 5(d)); the instabilitymap based on Gegel C cannot predict the unstable plastic
flow under the deformation conditions represented bypoints A, B, C and D (Fig. 5(e)); the instability map basedon Malas cannot predict the unstable plastic flow under the
deformation conditions represented by points B, C, D and E(Fig. 5(f)).
From the above analysis, we can know that the instability
maps based on Prasad, Murthy and Gegel B instability criteriahave better abilities of predicting unstable plastic flow due toleast instability points (only point A or E) locating in their
stable areas. Considering that the theoretical derivation ofMurthy instability criterion is stricter than Prasad instabilitycriterion,20 we have established instability map of as-cast7075 aluminum alloy, as shown in Fig. 7, by the superposition
of the instability maps based on Murthy and Gegel B instabil-ity criteria. In the stable area of the developed instability mapof as-cast 7075 aluminum alloy, all instability points are
removed, so it has more comprehensive ability of predictingunstable plastic flow.
3.2.3. Processing map
The hot processing map of as-cast 7075 aluminum alloy basedon DMM with a strain of 0.7 has been established by a super-imposition of the power dissipation map (see Fig. 4) and insta-
bility map (see Fig. 7), as shown in Fig. 8.
3.3. Analysis of processing map of as-cast 7075 aluminum alloy
According to the microstructure characteristics and whetherplastic flow is stable or not, the hot processing map of as-cast 7075 aluminum alloy can be divided into five areas: stablearea with as-cast grain (A0), stable area with homogeneous
grain resulting from dynamic recovery (B0), instability areawith as-cast grain (C0), instability area with the second phase(D0), and instability area with mixed grains (E0).
In the stable area (A0) of the processing map, the typicalmetallographic microstructure, obtained at a temperature of400 �C and strain rate of 0.1 s�1, is shown in Fig. 9. We can
see that it still remains dendrite network structure like the ini-tial as-cast microstructure. So, it is not suitable to deform thealloy under the deformation conditions locating in area A0,because the as-cast microstructure cannot be eliminated effec-tively although unstable plastic flow cannot occur.
In the stable area B0 of the processing map, the typical met-allographic microstructures of the deformed alloy, obtained at
the temperature of 450 �C and strain rates of 0.01, 0.1, 1 s�1,are shown in Fig. 10. We can observe that (1) the as-cast den-dritic microstructures have been fully eliminated; (2) the
microstructure and grain boundaries are clear; and (3) the
Fig. 5 Instability maps based on various instability criteria.
Processing map of as-cast 7075 aluminum alloy for hot working 1779
dynamic recrystallization phenomenon seems not apparent,
but the microstructure presents typical dynamic recovery char-acteristics and the grain size is uniform. The alloy deformed inarea stable B0 of the processing map not only can get uniform
microstructure but also has the as-cast microstructure defectseliminated effectively by dynamic recovery.17 Therefore, the
stable area B0 with homogeneous grain resulting from dynamic
recovery, namely the temperatures at 425–465 �C and thestrain rates at 0.01–1 s�1, is suitable processing area for theas-cast 7075 aluminum alloy.
In the instability area C0 of the processing map, the typicalmetallographic microstructure of the deformed alloy, obtained
Fig. 6 Compressed samples with cracks under various conditions.
Fig. 7 Instability map based on Gegel B and Murthy instability
criteria.
Fig. 8 Processing map of as-cast 7075 alloy aluminum.
1780 L. Guo et al.
at the temperature of 400 �C and strain rate of 10 s�1, is shownin Fig. 11(a). We can see that it still remains dendrite networkstructure like the initial as-cast microstructure. Fig. 11(b)
shows the deformed compression sample, which has a plicatedand rough surface indicating a cracking trend. The reason isthat the as-cast 7075 aluminum alloy is easier to generate dam-
age for high deformation resistance at the temperature of400 �C and strain rate of 10 s�1 as shown in Fig. 2(d). Thusit is not suitable to deform the alloy under the deformationconditions locating in the instability area C0 of the processing
map due to the as-cast microstructure like the initial billet andpossible plastic flow instability.
In the instability area D0 of the processing map, the typical
metallographic microstructure (see Fig. 12) of the deformedalloy, obtained at the temperature of 450 �C and strain rateof 10 s�1, illustrates that no obvious recrystallization phe-
nomenon occurs. A large amount of the second-phase present-ing gathered state is distributed along grain boundaries. Theseunevenly distributed second phases not only lead to uneven
microstructure of the deformed alloy but also become stress
Fig. 9 Microstructure of deformed sample at temperature of
400 �C and strain rate of 0.01 s�1.
Fig. 10 Microstructures of deformed samples at temperature of 450 �C and strain rates.
Fig. 11 Microstructure and compressed sample at temperature of 400 �C and strain rate of 10 s�1.
Fig. 12 Microstructure of deformed sample at temperature of
450 �C and strain rate of 10 s�1.
Processing map of as-cast 7075 aluminum alloy for hot working 1781
concentration area and crack source during deformation,which will reduce the plasticity and toughness of alloy and gen-
erate plastic flow instability.24,25 The evidence is that the com-pressed sample under the same deformation conditionproduces crack, as shown in Fig. 6(e). Thus it is not suitable
to deform the alloy under the deformation conditions locatingin the instability area D0 of the processing map.
In the instability area E0 of the processing map, the typical
metallographic microstructures (see Fig. 13) of the deformedsamples illustrate that obvious recrystallization phenomenonoccurs because the fine dynamic recrystallization grains canbe observed clearly in grain boundaries. But the degree of
the dynamic recrystallization is small, so the microstructureof the deformed samples is very uneven due to the mixtureof fine dynamic recrystallization grains and original coarse
grains of the billet. This will reduce the formability of thematerials and lead to unstable plastic flow easily. The evi-dences are that the compressed samples under the same defor-
mation conditions produce cracks, as shown in Fig. 6(b) and (d). Thus it is not suitable to deform the alloy underthe deformation conditions locating in the instability area E0
of the processing map.
On the basis of the above analysis of the microstructurecharacteristics of the samples deformed in the five areas ofthe established processing map, the stable area with homoge-
neous grain resulting from dynamic recovery, namely the tem-peratures at 425–465 �C and the strain rates at 0.01–1 s�1, is
Fig. 13 Microstructures of deformed samples under various conditions locating in instability area (E’).
1782 L. Guo et al.
suggested to be the suitable processing window for the as-cast7075 aluminum alloy.
4. Conclusions
(1) The true stress–strain curves at temperatures of300–500 �C and strain rates of 0.01–10 s�1 are obtainedby the isothermal compression tests, providing a data basis
for the establishment of hot processing map of as-cast7075 aluminum alloy. Compared with as-forged 7075aluminum alloy, the peak stress and the corresponding
strain of as-cast 7075 aluminum alloy are smaller underthe same deformation temperature and strain rate.
(2) The prediction abilities of cracks of different instability
criteria are compared by compression tests. The resultsshow that the Murthy and Gegel B instability criteriahave better crack prediction abilities. Thus the instabil-
ity map of as-cast 7075 aluminum alloy with comprehen-sive crack prediction ability has been developed by thesuperposition of the instability maps based on Murthyand Gegel B instability criteria.
(3) The hot processing map of as-cast 7075 aluminum alloyhas been established by superimposing the instabilitymap on the power dissipation map. According to the
microstructure characteristics of compressed samplesand whether plastic flow is stable or not, it can bedivided into five areas: stable area with as-cast grain,
stable area with homogeneous grain resulting fromdynamic recovery, instability area with as-cast grain,instability area with the second phase, and instability
area with mixed grains.(4) In terms of the microstructure characteristics of the sam-
ples deformed in the five areas of the established pro-cessing map, the stable area with homogeneous grain
resulting from dynamic recovery, namely the tempera-tures at 425–465 �C and the strain rates at 0.01–1 s�1,is suggested to be the suitable processing window for
the as-cast 7075 aluminum alloy.
Acknowledgments
This work was financially supported by the National Science
and Technology Major Project of China (No. 2009ZX04005-031-11), the EU Marie Curie Actions – MatProFuture Project
(No. FP7-PEOPLE-2012-IRSES-318968) and the ‘‘111”Project of China (No. B08040).
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Int 2012;18(1):69–75.
Guo Lianggang is an associate professor at Northwestern Polytechnical
University. He mainly focuses on some special forming processes such
as ring rolling and extrusion for difficult-to-deform materials which are
widely used in the aerospace industry. In addition, his research interest
is intelligent modeling and simulation of an entire manufacturing
process for core aerospace components with key fundamental mate-
rials.
Yang He is the President of China Society for Technology of Plasticity,
‘‘Cheung Kong” Chair Professor, Professor and Chairman of the
Department of Materials Forming and Control Engineering at
Northwestern Polytechnical University. His main research interests
include control of unequal deformation via local-loading, precise/high-
efficiency/load-saving plastic forming of difficult-to-deform materials,
precision forming for large-scale complex and lightweight components,
and digital precision plastic forming based on multi-scale modeling
and simulation.