ASM Metals HandBook Vol. 14 - Forming and Forging
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Acquisition of Data for Forging Process Design
H.L. Gegel and J.C. Malas, Air Force Wright Aeronautical Laboratories/Materials Laboratory; S.M. Doraivelu and V.A. Shende,
Universal Energy Systems, Knowledge Integration Center
Introduction
A number of experimental techniques are available for gathering necessary material-behavior data. These techniques
include hot compression tests, hot torsion tests, hot tensile tests, and subscale metal-forming operations. These methods
are reviewed in Ref 1 and 2 and are discussed in detail in the Section "Evaluation of Workability" in this Volume.
References
1.
A. Aran, An Experimental Comparison of Different Methods to Determine the Strain Rate Sensitivity Index
of Superplastic Materials, Scr. Metall., Vol 13, 1979, p 843
2.
K.P. Rao, S.M. Doraivelu, and V. Gop
inathan, Flow Curves and Deformation Mechanisms at Different
Temperatures and Strain Rates, J. Mech. Work. Technol., Vol 6, 1982, p 63
Acquisition of Data for Forging Process Design
H.L. Gegel and J.C. Malas, Air Force Wright Aeronautical Laboratories/Materials Laboratory; S.M. Doraivelu and V.A. Shende,
Universal Energy Systems, Knowledge Integration Center
Hot Compression Testing
Hot compression testing has become increasingly popular for several reasons, in particular:
• Uniform deformation can be maintained to large strains with proper lubrication
• Isothermal conditions can be easily achieved
•
The compressive state closely represents the conditions present in forging, extrusion, and rolling
processes
Among the various types of hot compression tests, the constant strain rate test is preferred because it yields both the flow
stress data required for finite-element method applications and the strain rate sensitivity and temperature sensitivity data
needed for dynamic material modeling from the same set of tests (Ref 3).
Generation of Flow Curves. Compression testing is usually conducted on a servohydraulic computer-controlled load-
frame with data acquisition instrumentation. Upon completion of the test, load-stroke data that have been written into
microcomputer memory are converted from the resolution-step format generated by an analog-to-digital converter to the
actual force (MPa) and displacement (mm) units. This new data set is written to disk for permanent storage and is also
read for further analysis. Software is then used to calculate true stress and true strain, as discussed below.
First, plastic deformation is determined from the load-stroke curve by determining the elastic component and then
subtracting it from the stroke. The true stress and true strain are then calculated. The resulting true stress-true plastic strain
data are stored on disk for plotting the flow curves and for further analysis.
Software routines, which correct the true stress-true plastic strain curves for the temperature increase T due to the heat
of deformation, are based on:
(Eq 1)
where is the true stress, is the true plastic strain, is the density, C is the heat capacity, h is the deformation heat factor
= (A/1 + m), m is the strain rate sensitivity, and A is the heat retention factor.
The calculated temperature increase is used to offset the pseudo flow softening by correcting the flow stress using:
(Eq 2)
(Eq 3)
The value of d /dT is determined from the uncorrected experimental data at small strains by plotting versus T at a
particular strain rate. The slope of the least squares fit of this plot is taken as d /dT.
Typically, several corrected flow curves are generated on a single plot, as shown in Fig. 1. Figure 2 shows the corrected
flow curve and the uncorrected flow curve.
Fig. 1 Corrected flow curves at different temperatures with log = 0.
Fig. 2 Corrected and uncorrected flow curves at 1100 °C (2010 °F) and log = 0.
Effective Stress/Effective Strain Rate/Temperature Relationships. Effective stress and effective strain rate
values are extracted at various strain levels and test temperatures from the flow curves and are converted into log and
log The constitutive relationship is obtained by fitting data points to piecewise quadratic functions. Quadratic functions
are selected to ensure that the convexity conditions is satisfied. At the intersection of two equations, suitable methods are
used to obtain a smooth transition from one equation to another. In the region where two equations overlap, log values
are generated by averaging the values obtained by two close equations. Therefore, a large number of log values are
generated at very close intervals of log values. These values can be used for representing flow stress as a function of log
and T, and they are also used as a subroutine in the finite-element analysis. Linear interpolation could be used if a value
is required between the generated values. A similar procedure is used to generate intermediate points between the
experimental data along the temperature axis. A minimum of 40 compression tests are generally recommended to obtain a
good fit and accurate results.
Reference cited in this section
3.
D.R. Barker, S.M. Doraivelu, H.L. Gegel, Y.V.R.K. Prasad, J.C. Malas, J.T. Morgan, and K.A. Lark,
Computer-Aided Data Acquisition During Controlled Strain Rate Upsettin
g Test and Analysis for Metal
Forming Applications, in Computers in Engineering,
Vol 2, Proceedings of the International Computers in
Engineering Conference and Exhibit, Las Vegas, NV, American Society for Mechanical Engineers, 1984, p
532-536
Acquisition of Data for Forging Process Design
H.L. Gegel and J.C. Malas, Air Force Wright Aeronautical Laboratories/Materials Laboratory; S.M. Doraivelu and V.A. Shende,
Universal Energy Systems, Knowledge Integration Center
Workability Data
Determination of m, η, and η/ log . The strain rate sensitivity parameter m is calculated by using the flow
stress values generated as a function of log at various test temperatures for a given effective strain. A pair of flow stress
values taken at very close intervals of log values are inserted into Eq 4, and the values of m are obtained as a function of
log at a given temperature and effective strain. This should be repeated at each test temperature to cover the entire range
of test temperatures and strain rates for the given effective strain.
The efficiency parameter can be determined by using the calculated m values and Eq 4:
(Eq 4)
The values of as a function of temperature and log can be output compatible with a graphics package such as
MOVIE.BYU (the graphics software package used to generate the graph). A three-dimensional (3-D) plot of as a
function of temperature and log and the corresponding efficiency contour plot can then be generated. A sample
representation of a 3-D plot is shown in Fig. 3 (Ref 4).
Fig. 3 Three-
dimensional surface plot of efficiency of power dissipation as a function of strain rate and
temperature of aluminum alloy 2024 with 20 vol% SiC.
Values of / log are required to identify stable and unstable regions. The loci of all values of / log = 0
separate these regions. These values are calculated based on the values at very close intervals of log and using the
formula (
2
-
1
)/(log
2
- log
1
). The values can be plotted on a two-dimensional (2-D) efficiency contour plot.
Determination of s and s/ log The entropy rate ratio, s, can be calculated by using the log values generated
from the experimental values at very close temperature intervals for a given effective strain rate and strain (see the section
"Dynamic Material Modeling" in the article "Modeling Techniques Used in Forging Process Design" in this Volume).
The following relationship is used for this calculation:
(Eq 5)
This value will be represented at the temperature:
(Eq 6)
Similarly, s is calculated at various temperatures and effective strain rates for a given effective strain, and these values
will be subsequently used for the calculation of s/ log The variation of s with strain rate is also calculated by using a
pair of values and Eq 7:
(Eq 7)
For delineating the stable and unstable regions, the loci of all values of s/ log = 0 are used. These points can also be
plotted on the same efficiency 2-D contour plot, along with the values of / log for the development of processing
maps. Such a map is shown in Fig. 4 (Ref 4).
Fig. 4 Processing map showing areas of identical efficiency as a function of log and temperature. T
he contour
plot also shows stable regions (shaded areas) recommended for processing aluminum alloy 2024 with 20 vol%
SiC.
Development and Interpretation of Processing Map. The processing map developed for each initial condition
of the experiment provides stable and unstable regions in temperature and effective strain rate space. Stable regions are
recommended for processing. In the stable region, the optimum combination of temperature and effective strain rate can
be selected based on the required microstructure, the availability of equipment, and the ease with which processing
parameters can be controlled.
On the 2-D efficiency contour map, the lines that represent the loci of all
and
(Eq 8)
values can be superimposed as shown in Fig. 4 to generate a comprehensive processing map.
Microstructural data should be incorporated into the processing map to correlate the types of microstructures and
metallurgical processes. The aim of this evaluation is to identify dissipative processes such as the occurrence of dynamic
recrystallization, microcracking, phase transformation, and primary and secondary grain growth. These can be correlated
with different regimes on the processing maps in order to interpret the map and to arrive at an optimum range of
temperature and strain rate for billet conditioning or hot working.
Reference cited in this section
4.
S. Gopinath, "Automatio
n of the Data Analysis System Used in Process Modeling Applications," M.S. thesis,
Ohio University, June 1986
Acquisition of Data for Forging Process Design
H.L. Gegel and J.C. Malas, Air Force Wright Aeronautical Laboratories/Materials Laboratory; S.M. Doraivelu and V.A. Shende,
Universal Energy Systems, Knowledge Integration Center
Interface Data
Determination of m' (Friction Factor). The ring compression test is commonly used for the measurement of the
interface friction factor. Ring specimens of standard size are compressed between flat dies to a known reduction under
optimum working conditions selected on the basis of dynamic material behavior modeling. The change in the internal
diameter of the ring is measured to quantify the friction. The measured dimensions (reduction in height and variation in
external diameter) are placed on the appropriate calibration curves to arrive at the friction factor. These analytical
calibration curves are available in the literature.
The test can be conducted with different surface roughnesses of the flat dies, using a variety of lubricants. Thus, a
complete variation of the friction coefficient is obtained as a function of temperatures, lubricants, surface conditions, and
so on.
Determination of h (Heat-Transfer Coefficient). The thermal resistance of a contact is also a surface effect,
coupled with the thermal and mechanical properties of the materials making up this contact as well as the interstitial fluid.
The absence of either physical contact or an interstitial fluid results in poor contact. The most reliable contact involving
metallic conduction results in the case of completely welded or brazed joints. All other cases fall in between these two
extremes.
When two surfaces are held together under pressure, the effective contact area is a function of the contact materials,
surface conditions, surface flatness, and the contact pressure. The thermal interface conductance is a function of the
effective contact area, which is made up of many small points of contact and is only a small fraction of the nominal
contact area. Figure 5 shows a representative view of the asperities that make up a contact. These contact points are
distributed quite uniformly, so that an increase in pressure causes an increase in the number of points of contact, resulting
in an increase in total true contact area.
Fig. 5
Physical arrangement and temperature variation for the contact conductance phenomena. (a) Magnified
view of contact cross section of bars. (b) Diagram of two bars jointed by contact pressure P with T
1
> T
2
and
heat flowing from bar 1 to bar 2. (c) Temperature variations at points x
1
through x
4
used to extrapolate
junction temperatures T'
2
and T'
3
.
From the basic Fourier equation, the steady-state heat flow at any part of the heat path is given by:
(Eq 9)
If the thermal conductance of the interface is defined as:
(Eq 10)
where q is the heat flow (in Btu/h/ft
2
), k is the thermal conductivity (in Btu/h/ft/°F), T is the temperature (in °F), h is the
conductance at interface (in Btu/h/ft
2
/°F), and x is the distance in the direction of heat flow (in feet). Then:
(Eq 11)
or
(Eq 12)
The thermal resistance is defined as r = 1/h.
Figure 5 shows two bars held in position by a pressure, P. Under steady-state conditions, neglecting any losses when T
1
>
T
2
, the heat flux flows from left to right, and q
1
= q
j
= q
2
, where q
j
is the heat flux through the junction of cross-sectional
area A. If temperature measurements are made at locations x
1
, x
2
, x
3
, and x
4
as shown in Fig. 5 and if the conductivities k
1
and k
2
are assumed to be independent of the temperature, the junction temperatures T'
2
and T'
3
can be obtained by
extrapolation. The interface conductance, h, for the joint can then be determined by:
(Eq 13)
A test fixture, as shown in Fig. 6, is used to measure the thermal contact conductance between two dies. It consists of a
hollow punch that is machined, ground, and then screwed onto a steel punch adaptor. The adaptor is fastened to the upper
platen of the testing machine. A copper disk with cartridge heaters is used to heat the punch head.
Fig. 6 Schematic of heat-
transfer coefficient test fixture for measuring thermal contact conductance between
two dies. The sample material tested is aluminum.
The punch is machined in two pieces to facilitate insertion of the copper plate. A voltage regulator is used to vary the
heater output. The base of the fixture is mounted on the lower platen of the testing machine and can be cooled by water. A
number of instrumented dies machined from various superalloys, such as Waspaloy, Alloy 901 (UNS N09901), Alloy 100
(Ni-15Co-10Cr-5.5Al - 4.7Ti - 3.0Mo - 1.0V - 0.6Fe - 0.15C-0.06Zr-0.015B), H-12 tool steel, and type 347 can be