Abstract: High temperature deformation behavior of Al-5.9, Cu-0.5%, Mg alloy and Al-5.9, Cu-0.5%, Mg alloy containing 0.06 wt.% Sn was studied by hot compression tests conducted at different temperatures and strain rates. Trace content of Sn resulted in a significant increase of flow stress for various processing conditions. Artificial Neural Network (ANN) modeling was applied providing excellent prediction of flow stress at different combinations of strain, strain rate and deformation temperature. While validation, it was possible to predict 100 and 89% of the flow stress values of the respective alloys within an error less than±10%. The flow stress data thus generated using the ANN architectures was used to develop power dissipation efficiency maps, instability maps and subsequently the processing maps which would delineate the process domains for safe metal working. Optimum hot processing window was suggested for the investigated alloys, providing intelligent processing and manufacturing system of these wrought microalloyed Al alloys, extensively used in aircraft and space applications. The power dissipation efficiency maps revealed a maximum efficiency of 60% for the alloy without Sn content, while a comparatively lower value of 40% for the microalloyed material. The instability maps generated for the alloy containing Sn, revealed only one instability regime. The safe regimes for hot working of the base alloy without Sn content were observed at (i) very low strain rate (<0.003 sec-1) with temperature <450°C and (ii) high temperature (>400°C) with strain rate >0.02 sec-1. The safe processing zone of the alloy with trace content of Sn, is at low strain rate (<0.01 sec-1) for the entire range of temperatures studied. Microstructural analysis confirmed that dynamic recovery (DRV) and dynamic recrystallization (DRX) characterized the safe processing regimes of both the alloys. Instability during hot deformation was observed to be driven mainly by shear band formation and/or intercrystalline cracking for the investigated Al alloys.
INTRODUCTION
The high demand and interest in aircraft and space related applications in the recent years have resulted in a thrust for development of light weight alloys exhibiting high specific strength, reasonable ductility, high fracture toughness and good corrosion resistance properties (Heinz et al., 2000; ASM International Handbook Committee, 1990). Aluminum alloys, especially the wrought and precipitation strengthened Al-Cu (2xxx), Al-Mg-Si (6xxx) and Al-Zn-Mg-Cu (7xxx) series of alloys, were developed because of their high strength to weight ratio. The 2xxx series of Al alloys are used for high strength structural applications such as aircraft fittings and wheels, rocket fins, military vehicles and bridges, forgings for trucks, etc., the Al-Cu-Mg alloys of 2124, 2219 and 2618 are extensively used even in aerospace structures demanding good heat resistance properties up to 150°C (Sukumaran et al., 2008; Raju et al., 2007).
The mechanical properties of these alloys are affected even by minute variations in composition, strain history and the microstructure resulting from the thermo-mechanical treatment imparted before the final use. Subsequently, the present research trend is to develop increased strength combined with properties of reasonable toughness and low density by the addition of trace elements (microalloying i.e., alloying elements <0.1 wt. %) like Sn, In, Cd, Ag, Si, etc., in to the alloy matrix (Hirosawa et al., 2000; Sercombe and Schaffer, 1999).
These wrought alloys need to undergo a thermo-mechanical treatment prior to
their final use, to reduce the defects (viz. segregations, dendrite structures,
gas defects, inclusions etc.) induced during casting. This deformation process
is generally carried out at high homologous temperatures i.e., T/Tm
>0.5 where, T and Tm are the absolute working temperature and
melting temperature of the material, respectively. A clear understanding of
the process variables and material parameters is required for successfully deforming
these materials within a range of strain rates (
Workability is an important parameter in mechanical working which refers to the relative ease with which a metal can be shaped through plastic deformation without introducing any defect. One of the most important methods to demonstrate hot workability of a material is by means of processing maps. Various models were developed through decades, for understanding the deformation behavior of metallic alloys, viz. Kinetic models proposed by Flynn et al. (1961) and reviewed by Jonas et al. (1969), Ashby maps (Atomistic mechanism maps) Frost and Ashby (1982) representing the materials response in the form of deformation mechanism maps and finally (Raj, 1981) to construct processing maps. Dynamic Materials Model (DMM) was developed (Prasad and Sasidhara, 1997; Prasad et al., 1984) for studying the workability parameter, based on principles of continuum mechanics of large plastic flow using the concepts of physical systems modeling and extremum principles o f irreversible thermodynamics. This model for hot deformation is expected to predict: (1) The response of the workpiece material in terms of microstructural evolution, (2) Optimum process parameters without trial and error and (3) Process limits for controlling the manufacturing environment. The approaches available for modeling hot deformation behavior have been reviewed earlier by Prasad (1990) and Kutumarao and Rajagopalachary (1996). It was possible by DMM to bridge the principles of continuum mechanics of large plastic deformation and microstructural evolution in materials.
The major irreversible changes in the microstructure and their salient features
are: (i) Dynamic recrystallization (DRX) in the temperature range of 0.7-0.8
Tm and at intermediate
True stress (σ) vs. true strain (ε) curves provide microstructural
information related to the mechanisms of hot deformation. Different safe
and damage mechanisms occur at various zones of
Processing maps for a large number of metals, alloys, intermetallics and metal matrix composites have been systematically compiled along with a summary of metallurgical interpretations (Prasad and Sasidhara, 1997). However, only a few reports are available on the effect of alloying elements and the corresponding microstructural changes and processing maps of some commercial Al alloys (Cavaliere, 2002; Kaibyshev et al., 2002). The purpose of the present study was therefore, to investigate the influence of trace additions of tin (Sn) on the high temperature deformation/flow behavior and workability of Al-Cu-Mg alloys and subsequently to generate the processing maps for these alloys. Selecting elemental Sn becomes a worthy of investigation since Sn has already been reported to affect the mechanical properties of some Al alloys (Sercombe and Schaffer, 1999). The deformation behavior of the alloys was studied by hot compression tests performed at various temperatures and strain rates. Neural network has been successfully demonstrated as a more robust technique than any other conventional methods for generating the processing maps (Robi and Dixit, 2003). The flow stresses (σ) was hence modeled by Artificial Neural Network (ANN) and the generated σ values were used to develop high temperature processing maps for the alloys. To the best of the investigators knowledge, this is the first attempt made to propose the optimum hot processing window for industrial production of these highly applicable wrought 2xxx series Al-Cu-Mg alloys microalloyed with Sn and thereby to provide an intelligent processing and manufacturing system for the same.
EXPERIMENTAL PROCEDURES AND METHODOLOGY ADOPTED
Al: 5.9 wt.%, Cu: 0.5 wt.%, Mg alloy (Alloy-A, composition close to 2219 Al alloy) and Al: 5.9 wt.%, Cu: 0.5 wt.%, Mg alloy containing 0.06 wt.% Sn (Alloy-B) were prepared from aluminum ingots by a casting route. The cylindrical samples cast in graphite moulds were machined to 12 mm diameter and 200 mm length. The machined sample rods were then homogenized at 510°C for 10 h to reduce the non-homogeneity in composition and microstructure resulting from coring and segregation during solidification. Cylindrical specimens having dimensions of 10 mm diameter and 15 mm height were then machined from the annealed rods for hot compression testing.
High temperature compression tests were carried out using a servo-hydraulic
controlled dynamic 100 kN capacity universal testing machine (UTM, make: INSTRON,
Model: 8801). A split-type resistance heated furnace was fabricated and attached
to the UTM to maintain a constant test temperature. The cross head velocity
of the UTM actuator was varied such that a constant true strain rate was maintained
during the entire duration of each compression test. The actuator displacement
at any instant of time was controlled by the closed loop servo-hydraulic control
of the UTM using MAXTM software. The strain rates (
The flow stress of the two alloys was then modeled by artificial neural network (ANN). The ANN modeling was carried out by the Multiple Layer Perception (MLP) feed forward back propagation network.
Table 1: | Strain rates and temperatures of the hot compression tests |
The input layer consisting of three neurons (ε,
The flow stress values as predicted by ANN were used to generate the processing
maps for the investigated alloys. These maps can be generated from hot compression
tests data acquired at constant
The efficiency of power dissipation according to the DMM model and as proposed by Prasad et al. (1984) is:
(1) |
The term m, the strain rate sensitivity factor, is strain rate dependent. As proposed by Murty et al. (2000), the efficiency of power dissipation can be obtained from the flow stress as:
(2) |
As proposed by Prasad et al. (1984), the following metallurgical instability criterion was subsequently arrived:
(3) |
The parameter ξ(
Immediately after the test, each cylindrical compressed sample was water quenched in situ to avoid any metadynamic process, sectioned parallel to the axis and prepared for Optical Microscope (OM) using standard metallographic technique. The polished specimens were then observed under an upright optical microscope (Carl Ziess, Axiotech) equipped with Kontron KS-400 image analysis system, in order to identify the irreversible changes induced in the microstructure as a result of deforming them to a true stain value of 0.6.
RESULTS AND DISCUSSION
Flow stress behavior: The flow curves (σ vs. ε) obtained for
Alloy-A at various strain rates (
Fig. 1(a-b): | Flow curves at strain rates of (a) 0.001 sec-1 and (b) 1.0 sec-1 |
However, the flow softening after attaining the peak stress was considerable
only at the lowest
Generation of processing maps for hot workability: The ANN modeling
carried out provided excellent prediction of flow stress, σ (ε,
The efficiency of power dissipation (η) and strain rate sensitivity factor
(m) of the two alloys were contour plotted as a function of
Isoefficiency plots obtained for Alloy-B after deformation to ε values
of 0.2 and 0.6 are shown in Fig. 3. The η contours are
more widely spaced for Alloys B, as compared to those of the base alloy (Alloy-A).
In the
A convenient way of locating the optimum processing conditions is to locate regimes where the isoefficiency contours are widely spaced.
Fig. 2(a-d): | Contour plots of η at ε of (a) 0.2 (b) 0.4 (c) 0.6 and (d) contour plot of m at ε of 0.2 for Alloy-A |
Fig. 3(a-b): | Contour plots of η for Alloy-B at ε of (a) 0.2 and (b) 0.6 |
Table 2: | Process parameters for maximum power dissipation efficiency values of the investigated alloys |
Several dynamic metallurgical processes contribute to power dissipation during the hot deformation of materials. These metallurgical processes have characteristic ranges of efficiencies of power dissipation. Depending upon the microstructure, some of these processes may occur simultaneously and/or interactively. When more than one major power dissipation processes having different characteristics occur simultaneously, the energy of dissipation of one of the processes may become equal to that of another. The regime indicating metallurgical instability during plastic flow can be obtained by the instability condition as given by the Eq. (3).
Figure 4 shows instability maps for Alloy-A and Alloy-B at
ε of 0.6. The regions in the
Fig. 4(a-b): | Instability (shaded) regions for (a) Alloy-A and (b) Alloy-B at ε of 0.6 |
The boundary lines separating the stable and unstable flow regions indicate
ζ = 0, as shown in the instability maps. The flow instabilities arise due
to irreversible changes in the microstructure during plastic flow of the material.
The figures indicate the regions where the contour lines of efficiency of power
dissipation are closely spaced as the regimes of plastic instability. The two
regions where Alloy-A can be considered as safe for hot working are: (i) region
existing at high T (> ~420°C) for
Figure 5 shows the processing maps for Alloy-A and Alloy-B
at a ε value of 0.6, obtained by superimposing the corresponding power
dissipation maps and instability maps of these two alloys. The shaded areas
in figures hence indicate the unstable regions. The Fig. 5(a)
indicates lower values of efficiency of power dissipation for unstable regions
as compared to the adjacent stable regions in case of Alloy-A. The stable regions
of Alloy-A after a ε of 0.6 are observed at: (i) High T (>400°C)
and for 0.02 <
Microstructural evolution: Power dissipation map can provide insight
on various dissipative microstructures during the hot working process. To study
the dissipative microstructures formed during hot deformation, the microstructures
of specimens deformed to a ε of 0.6 under various
Figure 5(b) shows only one regime of flow instability for
Alloy-B. The flow instability regime corresponds to
Fig. 5(a-b): | Processing maps for (a) Alloy-A (b) Alloy-B at ε of 0.6 |
Microscopic studies of the samples deformed at 350°C and
The above studies indicate that the safe regimes for hot working of Alloy-A
are: (i) Very low
CONCLUSIONS
• | The high temperature deformation behavior of Al-Cu-Mg alloy and Al-Cu-Mg alloy containing 0.06 wt.% of Sn was investigated by hot compression tests performed at temperatures ranging from 300 to 500°C and strain rates ranging from 0.001 to 1.0 sec-1. Flow stress of both materials increased with increase in strain rate and decrease in deformation temperature |
• | From the point of design applicability, the Al-Cu-Mg alloy microalloyed with Sn, possesses higher strength, but is relatively difficult to deform as revealed from the higher values of flow stress |
• | Artificial neural network (ANN) modeling was carried out for the first time providing excellent prediction of flow stress at different combinations of strain, strain rate and temperature, during hot deformation of these wrought and microalloyed Al alloys |
• | From the flow stress data predicted by ANN modeling, power dissipation efficiency maps, instability maps and subsequently the processing maps were generated to delineate the process domains for safe metal working. This is the first attempt made to propose the optimum hot processing window providing an intelligent processing and manufacturing system for these wrought 2xxx series Al-Cu-Mg alloys microalloyed with Sn |
• | The power dissipation efficiency maps revealed a maximum efficiency of 60% for the base alloy without Sn content while a comparatively lower value of 40% for the alloy with trace addition of Sn. The instability maps generated for this alloy containing Sn revealed only one instability regime |
• | The safe regimes for hot working of the Al-Cu-Mg alloy without Sn content were observed at (i) very low strain rate (<0.003 sec-1) with temperature <450°C and (ii) high temperature (>400°C) with strain rate >0.02 sec-1. The safe processing zone of the microalloyed material is at low strain rate (<0.01 sec-1) for the entire range of temperatures studied |
• | Considerable flow softening was observed after attaining the peak stress value in both the alloys deforming at low strain rate of 0.001 sec-1. The phenomenon may be interpreted as a consequence of dynamic recovery (DRV) and dynamic recrystallization (DRX) which basically characterized the safe processing zones of both the alloys |
• | Metallurgical instability during hot deformation was observed to be driven by shear band formation and/or intercrystalline cracking for the investigated Al alloys |