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Thermal stability, determining the material ability of retaining its properties at required temperatures over extended service time, is becoming the next frontier for aluminum alloys. Its improvement would substantially expand their range of structural applications, especially in automotive and aerospace industries. This report explains the fundamentals of thermal stability; definitions, the properties involved; and the deterioration indicators during thermal/thermomechanical exposures, including an impact of accidental fire, and testing techniques. For individual classes of alloys, efforts aimed at identifying factors stabilizing their microstructure at service temperatures are described. Particular attention is paid to attempts of increasing the current upper service limit of high-temperature grades. In addition to alloying aluminum with a variety of elements to create the thermally stable microstructure, in particular, transition and rare-earth metals, parallel efforts are explored through applying novel routes of alloy processing, such as rapid solidification, powder metallurgy and additive manufacturing, engineering alloys in a liquid state prior to casting, and post-casting treatments. The goal is to overcome the present barriers and to develop novel aluminum alloys with superior properties that are stable across the temperature and time space, required by modern designs.
Keywords:
thermal stability, aluminum alloys, transition metals, rare earths, aerospace, automotive
Thermal stability is the key design feature that determines a suitability of materials for specific applications and has a particular meaning for aluminum alloys. As documented throughout the decades, practically all aluminum alloys are thermally unstable with their properties being affected, to some extent, by service temperature and time. This includes grades essentially used at room temperatures, as is the case with aircraft components that may become warm due to exposure to sun, due to aerodynamic heating, or heat transferred from engines, which can deteriorate their properties over years of service [1]. The key engineering interest is, however, in the high temperature range and increasing the upper service limit of high-temperature grades [2].
At present, extending thermal stability to higher temperatures is the technology and knowledge barrier that prevents the substantial expansion of application scope of aluminum alloys, especially in automotive, marine, and aerospace transportation vehicles, designed for long-term service and strategically using aluminum for its lightweighting advantages. It is believed that the future aluminum alloys with improved high-temperature capabilities could compete, in selected applications, with more expensive titanium- and nickel-based grades. Therefore, along with recent refocusing on the strategic importance of aluminum alloys as lightweight structural materials for all forms of transportation vehicles, a substantial research interest is devoted to an improvement in their performance at high temperatures.
Although the thermal stability of aluminum alloys represents the major theme or at least a partial subject of a large number of research papers, differences in its understanding, critical property selection, and testing procedures make it difficult or impossible to combine individual results to draw a unified quantitative conclusion. The objective of this report is to review all elements of thermal stability from fundamentals to applications that refer to structural materials and aluminum alloys. Through identifying its detailed controlling factors, a better understanding of the relationship between mechanical, structural, and thermophysical properties that are critical for performance of alloys at increased temperatures will emerge. The outcome will help in optimizing the service conditions for existing aluminum alloys and development of novel alloys with superior thermal stability.
There is no universal definition or single criterion describing thermal stability of structural materials. While being typically seen as the “material ability of retaining its properties at required temperatures over extended service time”, in practice, more major parameters influencing thermal stability are involved including, in addition to (i) temperature and (ii) time, also (iii) load conditions and (iv) environmental conditions. Another definition as a “material resistance to permanent property changes caused by heat” is even less accurate as after cooling to room temperature, some portion of properties frequently recovers, whereas in a design, the properties maintained at the service temperature matter. Thermal stability is also defined as a material “property” characterizing changes after long-time exposure to elevated temperatures [3]. In this case, thermal stability is seen as an “intrinsic property” and, therefore, such an approach has further limitations. The related term “dimensional thermal stability” is also used that describes thermal expansion.
When assessing the thermal stability of a material, a future destination of this description is essential. If thermal stability is assessed for the purpose of comparing different alloys, e.g., during alloy development, the temperature and time are sufficient to characterize the alloy behavior. However, when a design input is required, during a material selection for a specific engineering application, detailed service conditions should be assessed. The design input will require an experimental measurement and/or computer simulation of material performance under conditions of its future application, including the load details and service environment nature.
Due to the low melting point of aluminum, 660.5 °C, the thermal stability of its alloys covers the temperature range, which is substantially lower than that of other materials with much higher melting points that, excluding the corrosive factor, can be used to contain molten aluminum alloys, as schematically marked in . In this respect, the term “heat-resistant alloys” also has a relative meaning when applied to aluminum-based grades.
Open in a separate windowThe property variation of aluminum alloys at temperatures from cryogenic to over 400 °C is different than that observed in other materials, such as steel. As for other materials, the intensity of the temperature-related property change of aluminum alloys is influenced by their chemical composition and initial microstructure, controlled, in turn, by the manufacturing route and post-manufacturing treatment. An example for the wrought AA6061 alloy in T6/T651 condition is shown in a,b. At temperatures above 150 °C, the alloy suffers a loss in strength with deterioration increasing over time. Above 200 °C, the weakening is substantial, and is accompanied by some gain in ductility. Most of the strength reduction induced by exposure to elevated temperatures is permanent, so the loss in strength is not recovered when the material is returned to a lower temperature. In case of AA6061, a major portion of the loss in strength is caused by coarsening of the Mg2Si precipitates. As shown in a, aluminum alloys are susceptible to creep and stress relaxation. Creep is a time-dependent, permanent deformation that occurs under sustained load or stress, even at stresses below the yield strength. For the most part, creep is governed by migration of vacant lattice sites, which increases with temperature.
Open in a separate windowIn order to apply a material for a particular design, the certain threshold of properties at service temperature is required. To understand the process of material selection, three hypothetical alloys with different strength vs. temperature/time characteristics are shown schematically in a,b.
Open in a separate windowAlloy A has an initial strength that substantially exceeds the minimum required but experiences a steep reduction at temperatures much lower than that predicted in its design ( a). In contrast, alloy C shows high thermal stability with low reduction in strength, taking place within the entire temperature range. However, its overall low strength makes it not suitable for this application. Thus, from a temperature criterion alone, alloy B meets the design specification.
At a given temperature, the material properties are affected by the exposure time. The influence of time on the properties of aluminum alloys depends on temperature. At high temperatures, a reduction of strength is the dominant observation for all classes of alloys. In contrast, at room or slightly elevated temperatures the opposite behavior may be observed, where the alloy strength may increase at the cost of plasticity, so an alloy may become prone to brittle cracking. The alloy selection depends, therefore, on the kinetics of the strength variation, and for alloy B, the strength reduction at temperatures T2 and T3 makes it not suitable for that design.
As portrayed in a,b, a definition of thermal stability as “strength (property) retention at service temperature/time” can lead to confusion during a material selection. Therefore, the highly thermally stable alloy C does not meet design requirements due to its overall low strength. Thus, the thermal stability criterion that is viable during a material selection has two factors: (i) an alloy should achieve at room temperature the strength required and (ii) the strength should be retained within the temperature and time space to meet the level required at service temperature and to remain stable for the predicted service time.
Thermal stability is often expressed through graphs of the alloy strength vs. maximum service temperature. While being very educational, the above examples show that without specifying detailed conditions (time, load, environment, etc.), such characteristics are very approximate.
The influence of heat on material properties depends not only on temperature but also on temperature changes with time, especially in the case of frequent (periodic) changes, a presence of load applied to a material in structural applications and its nature.
In general considerations of thermal stability, it is assumed that a material is exposed to constant (or near constant) temperature. As thermal stability refers to all temperature ranges that also include room environment the term “high thermal stability” may often be misleading, when temperature is not specified. For example, an aluminum alloy may be described as having very high thermal stability just at 100 °C. Examples of applications of aluminum alloys that require thermal stability at essentially different temperatures are shown in a–c.
Open in a separate windowStability at room and slightly elevated temperatures refers to temperatures typically below 100 °C. Such a scenario occurs for aircraft components that may become warm during service due to exposure to sun, aerodynamic heating, or heat transferred from engines. Temperatures from 70 °C to 85 °C are typically used to simulate the environment to which the wings and fuselage structures of a commercial aircraft are exposed [8].
The medium temperature range, requiring thermal stability, covers temperatures below 200 °C. They include impellers used in generators/compressors, vacuum pump rotors, and turbocharger impellers of various sizes with service range of 150 to 180 °C. An example of alloy used in this environment is the Al−Cu−Mg−Fe−Ni AA2618 alloy [9]. The medium temperature range will also cover alloys in metastable state, cold-deformed, nanocrystalline, and amorphous ones. However, the most challenging aspect of thermal stability is maximizing the upper service limit of high-temperature grades with the ultimate goal for aluminum alloys being to exceed 400 °C.
Thermal stability is uniquely tested in a case of accidental fire, when aluminum alloys may be exposed to temperatures, exceeding those predicted for regular service that exert damaging effect on their properties. There is a concern of fire safety with using aluminum for load-bearing applications such as lightweight structures, light rail, bridge decks, marine crafts, and off-shore platforms, due to potential dangerous reduction in mechanical properties during exposure to heating [10]. Alloys used in these applications are typically not designed for high temperatures. A related concern is regarding the integrity and stability of an aluminum structure following a fire exposure.
Due to thermal exposures, materials expand during heating and contract during cooling. When a material is geometrically constrained, this leads to generation of tensile and compressive stresses. Stresses may also arise within unconstrained materials due to a spatial temperature gradient. As a result of cyclic expansion and contractions the material experiences thermal fatigue. This phenomenon, also called heat checking, is common when a metal surface is repeatedly heated and cooled. Thus, thermal fatigue may occur without mechanical loads. If both thermal and mechanical strain is involved, the degradation mode is termed as thermomechanical fatigue.
As the structural materials are subjected to a load at service temperature, the effect of heat on their performance depends on the load level and its nature, with a special impact being exerted by heavy and cyclic loads, in particular with high-speed load alterations. To describe a material performance under particular service conditions the term durability is often used, understood as the ability of a material to sustain mechanical or thermomechanical loads over a predicted service time. Although the durability meaning may vary, depending on an application, for structural materials it is seen as the critical design consideration.
The ability of retaining the properties by an alloy is strongly affected by reactive environments leading, for example, to oxidation, erosion, molten metal or salt corrosion, or irradiation damage.
For room temperature service, surface corrosion, leading to localized reaction and a material loss, forming pitting and stress risers, is of concern. For service at high temperatures, a process of selective oxidation resulting in localized surface degradation should be considered.
The oxidation of aluminum in air can be described as occurring in four distinct stages [11]. At room and lower temperatures, the amorphous alumina layer covers the metallic surface, protecting it against further oxidation, which results in very slow film thickening up to 550 °C. At this stage, the oxide growth is controlled by outward diffusion of Al ions with a reaction taking place at the oxide−gas interface. The amorphous oxide remains stable, due to the energy of the oxide–metal interface, only up to a critical thickness of ~5 nm, then transforms to γ-alumina, when crystallites are no longer able to form a continuous layer that would cover the aluminum surface. This leads to stage II, above 550 °C, with higher oxidation rate and polycrystalline layer of γ-alumina covering the entire aluminum surface. At the stage III, which starts at 650 °C, very close to melting, the growth of γ-alumina continues at a rate controlled by the inward diffusion of oxygen anions along oxide grain boundaries, acting as fast diffusion paths.
In the case of aluminum alloys, the process of high-temperature oxidation may have a preferential nature, leading to localized oxide patches, formed on specific alloy phases, potentially forming stress risers. The role of aluminum surface reactivity is better understood when compared with another light metal, magnesium. Due to the high affinity of magnesium with oxygen, at high temperatures, its surface degradation and formation of MgO is of higher concern than a reduction in its mechanical properties [12,13]. In this regards, aluminum shows an advantage over magnesium. In contrast to magnesium, there is no concern of ignition or flammability with aluminum and its oxidation rate is substantially slower due to a formation of the protective Al2O3 alumina film. However, for Al−4−5Mg (wt.%), only MgO is formed with a reaction following the linear law up to 500 °C and parabolic law above 550 °C [14,15]. Then, an environment may essentially change the oxidation kinetics. For example, in a presence of traces of sulfur, spallation of otherwise protective alumina occurs, which is the chronic problem in some aerospace applications.
An important environmental factor, necessary to consider during analysis of thermal stability of aluminum, is the influence of radiation. Aluminum alloys are used in applications subjected to irradiation, e.g., as the primary structural material for the reactor reflector vessel of Advanced Neutron Source and for most of the components housed within the vessel [4] or in casks for transportation of nuclear fuels [16]. The deciding factors for the use of an alloy are good combination of low neutron absorption cross section and high thermal conductivity, good resistance to aqueous corrosion, and good performance in high flux reactors. Therefore, changes in mechanical properties expected to occur in alloys under irradiation during their intended lifetimes are of key importance.
The effects of irradiation exposures result in an increase in the metal’s volume, caused by development of voids, bubbles, and low-density phases, termed as swelling. Although generally metals undergo hardening during irradiation, softening is also possible, particularly for cold work-hardened or precipitation-hardened alloys, subjected to irradiation. That softening may take place during irradiation at temperatures below the normal temperature for thermal recovery, as a result of radiation enhanced diffusion processes or cascade dissolution of precipitates.
An example for the AA6061 aluminum alloy target holder from the High Flux Isotope Reactor, originally in a precipitation-hardened condition, after exposure to a maximum fast neutron fluence of 9.2 × 1022 neutrons/cm2 (E > 0.1 MeV) and a thermal fluence of 1.38 × 1023 neutrons/cm2 (E < 0.414 eV) at ~60 °C, is shown in a,b [17]. At temperatures in the range from 25 to 200 °C, significant strength increases were observed that are attributed to the silicon precipitates and to irradiation-induced dislocations. There was a corresponding loss of ductility, particularly severe at 200 °C for slow strain rate testing conditions. The alloy, tested at temperatures between 200 and 500 °C, at which the microstructure was unstable, showed substantial loss in strength, accompanied by a gain in ductility. For the entire temperature range from 25 to 500 °C, however, the strength of irradiated alloy was higher than that for the alloy without irradiation. The same nature of changes was reported for the AA4043 alloy welds.
Open in a separate windowIn another example, a microwave radiation influenced the thermal stability of aluminum nanosize powder. After microwave radiation with a power flux density of 80 W/cm2 and carrier frequency of 9.4 GHz, the chemical activity of aluminum powder increased and the temperature for the beginning of its oxidation decreased by 40 °C, while the thermal effect of oxidation decreased by 13.5% [18].
This phenomenon refers to temperatures typically below 100 °C. Such a scenario applies to aircraft components that may become warm during service due to exposure to sun, aerodynamic heating, or heat transferred from engines. Temperatures from 70 to 85 °C are typically used to simulate the environment to which the wings and fuselage structures of commercial aircraft are exposed [8]. For a supersonic jet, due to air friction at a speed of Mach 2.05, the temperature on the skin of the airplane body is reported as 127 °C [57]. A challenging factor is the long exposure time, as airplane materials are designed for a service time between 30 to 50 years. The aerospace applications have strict regulations, regarding thermal stability.
In today’s aircraft industry, there is a general shift from metallic materials towards composites, but aluminum alloys still represent ~60% by weight of the structural materials used. An exception is the Boeing 787 Dreamliner, which uses only 20% aluminum. Although there are different selection criteria, aluminum alloys are also used in spacecraft structures, including space vehicles and satellites.
The typical alloys used for aircraft structure are Al−Li grades containing lithium to decrease the weight of aluminum, while improving its strength, toughness, corrosion resistance, and forming characteristics. Lithium contents up to 3 wt.% exert a large effect on the modulus of aluminum with a 6% increase for every wt.% Li added. In addition, every wt.% Li added decreases the aluminum density by 3%. Aircraft industry applications include wing leading and trailing edges, fuselage bulkhead webs, and internal framework parts. For example, the Airbus A350 XWB has parts made of steel and titanium, with almost 20% made from Al−Li alloys.
A key question in controlling the thermal stability is how fast the properties evolve, which relates to the kinetics of phase transformations, primarily controlled by diffusion. A room temperature exposure of some aluminum alloys may result in natural aging, i.e., slight movements of solute atoms in the matrix, which modifies the material properties [58]. Aging of Al−Li alloys results in decomposition of solid solution of Li in Al and precipitation of Al3Li [59], which may lead to embrittlement during the long-term operation [60,61].
Historically, the first (1950s and 1960s) and second (1980s) generations of Al−Li alloys tended to suffer from several problems, including poor ductility and fracture toughness, fatigue and fracture resistance, and unreliable corrosion resistance [62]. The second generation alloys AA2090, Al−Li−Cu, and AA8090, 2091 Al−Li−Cu−Mg, when exposed to elevated temperature of ~70 °C undergo aging, causing an increase in strength and reduction in ductility and toughness that may lead to embrittlement. An explanation of embrittlement in the AA8090 alloy, considered the most successful of the second generation, includes a formation of δ AlLi phase at grain boundaries, segregation of Li atoms to grain boundaries, precipitation of small Al3Li particles, and precipitation effects related to G−P zone formation [63]. An example of property change for the second generation Al−Li alloy AA1464, subjected to long-term exposure at 85 °C and strengthening precipitates in third generation alloys, are shown in a,b.
Open in a separate windowThe third generation Al−Li alloys, developed in the 1990s, with significantly reduced lithium content and other improvements, made them more attractive for modern aircraft and aerospace vehicles. For example, the Airbus A380 uses 3rd generation Al−Li alloys AA2099−T83 and AA2196−T8511 for floor beams, AA2196−T8511 for fuselage stringers, and AA2050−T84 for lower wing reinforcement [64]. Thermal stability of the AA2099 Al−Cu−Li T83 alloy, assessed in the temperature range 200 to 305 °C, through both hardness and tensile tests after overaging, showed better performance, compared to aluminum alloys specifically developed for high temperature applications, with the advantage of a considerable lower density [65]. Tests underlined the need to enhance the formation of T1 (Al2CuLi) precipitates when high temperature strength is required. An addition of 0.29 wt.% Ce contributed to coarsening inhibition of Al2CuLi and refinement of Ce-containing intermetallic phase, Al8Cu4Ce, which further improved the thermal stability at the medium−high temperature range (170 to 270 °C) and high-temperature deformation uniformity of this alloy [66].
The Al–Li–Cu–Zr alloy, C458−T861 (Al−1.8Li−2.7Cu−0.3Mg−0.08Zr−0.3Mn−0.6Zn wt.%), destined for use in space vehicles, tested at 83, 135, and 177 °C for up to 1000 h showed good thermal stability of mechanical properties up to 135 °C. However, further increasing the temperature and time led to a reduction in the alloy fracture toughness [67].
The upper strength limit of bulk Al alloys achieved by conventional precipitation strengthening of ~700 MPa may be increased to over 1000 MPa through grain refinement to nanocrystalline level and amorphization. Unfortunately, the nonequilibrium state with a low thermal stability of amorphous and nanostructured aluminum alloys limits their use at increased temperatures.
Al-based amorphous alloys represent an important group of amorphous materials with a high specific strength, combined with outstanding corrosion resistance and good ductility. It is of interest that their high strength at room temperature is accompanied by an ability of softening to viscous liquid states above the glass transition temperature, thus allowing thermoplastic forming to be conducted due to superplasticity [68].
In the 1970s, the alloys covered Al−transition metal binary systems, formed by splat quenching, and in the 1980s, the Al−(Fe, Co)−B alloys, cast by melt spinning. Later, they expanded to alloying with transition metals groups IV−VI with VII and VIII. The next expansion included Al−rare earth binary systems and Al−transition metals−rare earth combinations. The latter systems are the most popular at present due their high glass-forming ability and high strength. There are still technological barriers with manufacturing the Al-based bulk metallic glasses due to their rather low glass-forming ability, requiring very high critical cooling rates that are difficult to achieve in engineering practice at larger cross sections, often larger than just a few micrometers.
During heating, amorphous alloys easily transform to crystalline structures, losing their unique properties. Following crystallization, continued heating results in phase transformations with a generation of stable and metastable phases, until the alloy finally melts. For example, amorphous powders with compositions of Al85Y7Fe8, Al83Y7Fe8Ti2, and Al79Y7Fe8Ni3Ti2Nd1 (at.%) exhibited crystallization temperatures of 342, 446, and 457 °C, respectively, with an increase by 115 °C through microalloying [69].
An interesting feature of the crystallization behavior of amorphous aluminum alloys is that some compositions have a tendency to crystallize into nanometer-sized clusters or grains ( ). The phenomenon can be explored for improving properties of amorphous structures. For example, the mechanical properties of bulk Al84Ni7Co3Dy6 (at.%) alloys, produced by Spark Plasma Sintering of amorphous powder with a diameter of 25 µm at temperatures above 400 °C, are significantly enhanced by in situ crystallization of nanoscale intermetallic compounds during plasma sintering [70]. The Al−Ni−Co−Dy bulk alloys produced by plasma sintering at 400 °C exhibit a maximum strength of 1773 MPa with 5.6% plastic strain. Increasing the sintering temperature to 430 °C led to higher plastic deformability of 7.2% at the expense of the lower maximum strength of 1255 MPa. The solute concentration played a key role in determining the size of the α−Al phase during plasma sintering of the amorphous Al84Ni7Co3Dy6 (at.%) powder.
Open in a separate windowNanocrystalline materials have a high stored energy due to their large grain boundary area and, when subjected to heating, grains have a tendency to grow to minimize their energy by reducing the grain boundary area per unit volume [71]. The poor thermal stability of nanocrystalline materials arises from their high density of grain boundaries, which provides a high driving force for grain coarsening. Overall strategies that are proposed to stabilize the grain size with emphasis on thermodynamic stabilization and kinetic stabilization are discussed in [72].
Therefore, low thermal stability restricts the application expansion of nanocrystalline alloys. To improve their thermal stability, the mobility of grain boundaries should be reduced, for example, through alloying. The precipitation-hardened AA2024 (Al−4.2Cu−1.5Mg−0.6Mn−0.5Si) alloy, with nanocrystalline structure, generated through the single-pass Equal Channel Angular Pressing, preserved its properties at 120 °C for up to 1000 h [73]. As shown in , after long-term heating at 80 and 120 °C, a secondary hardening took place, whereas at 150 °C, softening was accompanied by a slight secondary hardening. In contrast, at 200 °C fast softening occurred. As the major cause of the hardness loss, the increased coarsening rate of the equilibrium phase S (Al2CuMg) accompanied by dislocation annihilation were identified. Moreover, the dislocation-rich structure and Mg clusters, remaining from the S precipitate dissolution, eased the nucleation of Ω precipitates, which were responsible for the secondary hardening. The above transformation sequence differs from that described for the AA2024 commercial sheet [74].
Open in a separate windowAs another example, the nanocrystalline structure of Al−Mg−Sc alloys, generated by Friction Stir Processing, was stabilized by the Al3(Sc,Zr) dispersoid phase up to 450 °C for 16 h [75]. In turn, in cold-worked Al–Fe–Si alloys, developed for electrical engineering purposes, the Mn−Ni−Cr fine dispersion phases were effective recrystallization barriers, preserving the microstructure up to 300 °C [76]. In another example, the nanocrystalline Al−10Fe−5Cr (wt.%) bulk alloy preserved the compressive strength of 450 MPa at 450 °C with such a high thermal stability being attributed to the formation of Fe and Cr containing phases with Al, such as Al6Fe, Al13Fe4, and Al13Cr2, in addition to the supersaturated solid solution of Cr and Fe in Al matrix [77].
The application of High Pressure Torsion to the Al−2.46Cu−1.48Mg−0.89Fe−0.92Ni (wt.%) alloy led to grain refinement to 200 nm, formation of high-angle grain boundaries and dynamic precipitation of Al9FeNi particles, with the strength preserved up to 225 °C [78]. It is of interest that 0.5 h annealing at around 225 °C reduced hardness to the level seen before deformation. Increasing the temperature up to 300 °C resulted in the same hardness of both deformed and non-deformed alloys. Similarly, high pressure torsion led to an improvement of tensile strength of the AA2198−T8 Al–Li alloy, associated mainly with grain refinement and dislocation strengthening [79]. However, aging of that alloy at 175 °C for 12 h caused a reduction in strength, indicating the low thermal stability. In contrast, the ultrafine grain AA8090 Al–Li alloy with an average grain size of 2 μm, obtained by Repetitive Corrugation and Straightening (RCS), was fairly stable during heating up to 300 °C [80].
Additions of Er to Al−Mg alloy powder improved its thermal stability through the combined effects of the solute/impurity drag and second-phase pinning, involving nanosize oxides, nitrides, and oxynitrides that impeded the grain boundary motion [47]. Small additions of the order of 0.1 wt.% Er were not effective and Al−Mg powders showed the abnormal grain growth at 180 °C. In contrast, the 0.5 wt.% Er addition improved thermal stability, maintaining the grain size of approximately 20 nm up to 400 °C. The controlled grain growth at higher temperatures resulted in an average grain size of 55 nm and a maximum observed grain size of ~200 nm after one hour of annealing at 500 °C.
In addition to optimizing the alloy chemical composition, to improve thermal stability, parallel efforts are explored through alloy processing, such as rapid solidification, powder metallurgy, and additive manufacturing, engineering alloys in a liquid state, and post-casting treatments. They represent either modification of conventional or testing novel manufacturing routes or, as in the case of liquid metal engineering, an extra step within the conventional manufacturing sequence. Each technique exerts its unique impact on microstructural constituents, affecting the alloy performance at increased temperatures.
Liquid metal engineering refers to a variety of physical and/or chemical treatments of molten metals aimed at influencing their solidification characteristics [127]. It is generally accepted that exploring the synergy of melt chemistry and physical treatments, achieved through liquid metal engineering, allows creating the optimum conditions for nucleation and growth during solidification, positively affecting the quality of alloys.
The detrimental feature of aluminum alloys modified with transition metals, having much higher melting points than aluminum, is that the intermetallic compounds that control thermal stability are generally coarse and therefore ineffective. Thus, an opportunity to refine the coarse compounds, using liquid metal treatment, offers a number of benefits through reducing the overheating temperature, required during melting, shortening the holding time in a molten state and shortening the holding times during post-casting heat treatment, or in some cases, eliminate a need for heat treatment altogether. A new mixing technology that explores an integration of gas injection into the shear zone with ultrahigh shear mixing, called Gas-enhanced Ultrahigh Shear Mixing (GE−UHS), allows refining the microstructure through affecting the alloy solidification mechanism ( ) [128].
Open in a separate windowAn application of the GE−UHS technology to molten aluminum alloys shows that injecting gas into a shear zone of the rotor/stator apparatus drastically magnified the alloy structural refinement, which substantially exceeded the individual effects, caused by gas flotation and ultrahigh shearing. For an experimental Al−7Si−1Cu−0.5Mg (wt.%) alloy with microquantities (0.1 to 0.5 wt.%) of V−Ti−Zr, in addition to matrix grain size reduction by almost two orders of magnitude, the complex intermetallic compounds (AlSi)x(TiVZr) with D022/D023 tetragonal crystal structure were refined [129]. Those compounds with transition metals are crucial for thermal stability but remain inherently coarse in conventional castings.
For some alloys, liquid metal engineering may be the only option to refine the strategic strengthening compounds. An example is the Al−Ce alloy, where due to negligible solid state solubility of Ce in Al, generation of strengthening precipitates through heat treatment is impossible. The key component of Al−Ce binary alloys, which controls their thermal stability, is the Al−Al11Ce3 eutectic. However, the Al11Ce3 eutectic phase with lamellar morphology provides limited strengthening to the alloy [124].
According to recent experiments, the eutectic morphology can be transformed from lamellar to more effective fiber-like, using an agitation of a molten alloy before solidification with a permanent magnet [130]. Modeling of the lamellar-to-fiber transition within the Jackson–Hunt framework, followed by experiments, using the Al−5 wt.% Ce alloy, led to the fiber structure with improved mechanical properties. The alloy processing through permanent magnet stirring at 630 °C exhibited increased mechanical strength retention and better performance than the other commercial aluminum heat-resistant alloys. Although, there is some ambiguity, regarding the alloy treatment temperature and its location in regards to the alloy liquidus, this example demonstrates that liquid metal engineering offers a new route to influencing the solidification morphology with a considerable advantage over directional solidification and laser additive manufacturing.
Rapid solidification technology is explored for decades with aluminum alloys, showing many advantages over conventional ingot casting. It improves the elevated temperature performance of aluminum alloys through high supersaturations of elements in the matrix. Several experimental materials with transition metals Fe and Cr, produced through this route, have promising creep properties up to 350 °C [131].
The rapid solidification was used to manufacture aluminum alloys for high temperature applications, including systems Al–Fe–Ce, Al–Fe–Cr–(TM), Al–Cr–Zr(Mn), and Al–Fe–V(Mo)–Si [132]. The best examples of green products show strength of 550–600 MPa at room temperature and at least 200–250 MPa at 300 °C. The strength of Al–Fe–Cr–(TM) alloys with a high volume content of quasicrystals is approximately 100 MPa higher at 20 and 300 °C, while their elongation is 50 to 67% lower than typically seen in other aluminum alloys. In particular, in the Al−8.8Fe−3.7Ce (wt.%) alloy, processed through arc melting and rapid solidification and followed by extrusion, led to formation of metastable phases in addition to equilibrium structures Al6Fe, Al10Fe2Ce, and Al20Fe5Ce [133]. The Al20Fe5Ce phase was a decagonal quasicrystal while the Al10Fe2Ce phase was determined to have an orthorhombic crystal structure belonging to space group Cmmm, Cmm2, or C222.
Mechanical alloying is widely used to produce nanostructured aluminum alloys for high-temperature applications, including compositions with transition metals, where having the fine and homogenous microstructure is difficult to obtain after conventional casting. The process is generally implemented through a combination of gas atomization, ball milling, and hot pressing. Examples of alloys include both standard and unique compositions such as Al86Ni7Y4.5Co1La1.5 (at. %) [134], 70.0Al−22 Fe−8.0Ti (wt.%), 69.0Al−22 Fe−8.0Ti (wt.%) with 1.0 nano−Y2O3, and 69.0Al−22 Fe−8.0Ti (wt.%) with 1 wt.% nano−TiO2 [135].
The powder metallurgy with devitrification and consolidation of amorphous/crystalline powders was also used to manufacture Al84Ni7Gd6Co3 (at.%) alloys with a unique hybrid microstructure, composed of isolated nanoscale fcc−Al grains and intermetallic compounds [25]. The high strength at both room and high temperatures is attributed mainly to the composite structure and the effect of confinement between the nanosized Al and intermetallic phases. As a result of the confining effect, the premature brittle fracture of the intermetallics and the nanocrystalline Al could effectively be suppressed, thus offering the possibility to deform plastically and to exhibit intrinsic strength rather than the flaw-controlled strength. An example of properties of the Al84Ni7Gd6Co3 (at.%) alloy are shown in .
Open in a separate windowThe combined mechanical alloying and powder consolidation was also found effective during manufacturing of the Al(Mg)−NiO composites with very fine grain matrix [136]. During processing, transformation of NiO particles into thermodynamically stable Al3Ni and MgAl2O4 compounds in the Al(Mg)−NiO composite extruded at 400 °C is responsible for the flow stress decrease, observed for a wide range of deformation temperatures. Therefore, the effect of preliminary annealing at 600 °C on the flow stress versus deformation temperature characteristics was very limited, because the chemical reaction occurred during the hot extrusion of the composite, i.e., before composite annealing.
Additive manufacturing (3D printing) covers a variety of computer-controlled processes, where a material is deposited layer by layer and solidifies to create a three-dimensional object. Selective laser melting and electron beam melting represent the major technologies of additive manufacturing. The key feature of selective laser melting, where manufacturing is conducted by repeated melting and solidification of a metal powder by laser, is its cooling rate, being much faster than that experienced during conventional casting [137].
In addition to refining structure due to a rapid solidification, multipass laser additive manufacturing can trigger precipitation hardening, thus replacing heat treatment. Conventional processing involves controlled ageing, during which the ordered and coherent Al3Sc precipitates form from a Sc-supersaturated solid solution. In [138], the intrinsic heat treatment that explores the deposition energy was used to trigger in situ precipitation of Al3Sc during laser additive manufacturing. As the intrinsic heat treatment causes precipitates coarsening, thereby reducing their strengthening effect, the alternative solidification conditions were implemented to exploit the intrinsic heat treatment to form the Zr-rich shell around the Al3Sc precipitates.
As shown in , a presence of the Zr shell prevents the precipitate coarsening. This approach is applicable to a wide range of precipitation-hardened alloys, used in laser additive manufacturing.
Open in a separate windowIn general, laser-printed metals do not tend to match the mechanical properties and thermal stability of conventionally manufactured alloys. However, laser additive manufacturing can also produce high-performance and near-net shape parts of aluminum matrix composite with higher specific strength, better wear resistance, and more outstanding physical properties than aluminum alloys, which are widely used in automotive and aerospace fields [139]. It should be kept in mind that a single-pass laser melting creates microstructural effects similar to those achieved during rapid solidification.
Laser melting overcomes a challenge of manufacturing the aluminum matrix nano−composites with a high density of dispersed nanoparticles. The laser printed aluminum nano composites with a thickness of around 300 μm, reinforced with 35 vol.% TiC reached a yield stress of up to 1000 MPa, elongation over 10%, and Young’s modulus of approximately 200 GPa [140].
As shown in , hardness of the composite over wide temperature range exceeds values obtained for other metallic materials listed there. An improvement in the composite performance is attributed to the high density of uniformly dispersed nanoparticles, strong interfacial bonding between particles and matrix, and fine grain sizes of ~330 nm. Similar benefits of selective laser melting were recorded after deposition of AlSi10Mg (wt.%) composites with additions of TiB2 reinforcement [141].
Open in a separate windowTo better exploit the advantages of additive manufacturing and optimize the functionality of the customized components, alloys specifically developed for this manufacturing route are required. At present, the majority of additive manufacturing of aluminum-based alloys involves commercial grades such as AlSi7Mg, AlSi12, and AlSi10Mg (wt.%), designed for conventional casting. An attempt is shown in , where novel Al−Mn−Sc alloys were evaluated by selective laser melting [142]. Due to formation of the primary Al3(Sc,Zr) particles at the molten pool boundaries, the Al−Mn−Sc alloys developed a fine columnar-equiaxed bimodal grain structure with high thermal stability. Additions of transition metal Mn, forming Al6Mn likely through the solute rejection from the solidification front and nucleation at the grain and subgrain boundaries or dislocation walls, contributed to thermal stability improvement.
Open in a separate windowThe combination of processing through selective laser melting and alloying with Fe improved the high-temperature strength and ductility of Al−11.6Si−0.97Cu−0.96Mg−1Ni (wt.%) alloys [144]. According to microstructural observations the improvement was caused by the dispersion of fine rod-shaped Fe−Si−Ni particles, which replaced the cell-like structure of eutectic Si, typical for the conventionally cast state. Selective laser melting was also found effective to fabricate components from the heat-resistant Al–8.5Fe–1.3V–1.7Si (wt.%) aluminum alloy with a microhardness of 246 HV0.1 [145]. The nanosize spheroidal Al12(Fe,V)3Si particles, homogeneously distributed in the Al matrix, were developed in the heat affected zone, while the rectangle-like AlmFe phase with m = 4.0–4.4 and 100–500 nm in size was formed in the border re-melting zone.
In addition to experimental alloys, there are also commercial ones, designed for additive manufacturing. An example is the second-generation aluminum−magnesium−scandium (Al−Mg−Sc) alloy, referred to as Scalmalloy®, developed by Airbus research center as a high-strength lightweight alloy for selective laser melting [146]. The alloy with a specific weight of 2.67 g/cm3 offers tensile strength of 520 MPa with elongation of 13% and the microstructure stable up to 250 ° C.
In case of accidental fire hazards a metal might be exposed to enormously high temperatures. Due to relatively low melting temperature of aluminum alloys as compared to steel, often coexisting in a design, the outcome may be catastrophic for the former ( ). For aluminum, however, much higher heat input is necessary to bring the same mass of metal to a given temperature, compared with steel. This is caused by high thermal conductivity of aluminum, being about four times that of steel and its specific heat twice that of steel, resulting in higher heat transfer away from the source.
Open in a separate windowAluminum is non-sparking in all environments if struck against aluminum, stainless steel, or any other material. The purpose in using non-sparking metals is to prevent ignition of combustible or explosive materials from an impact-generated spark. There is, however, one known exception: when unpainted or uncoated aluminum is struck by or strikes rusty ferrous metals, sparks may result [147]. Therefore, to avoid any possibility of sparking, where it is likely that aluminum may be struck by rusty ferrous metals, protective coatings such as paint are recommended.
Even if pure, non-ferrous aluminum is used, sparks can occur during an aluminothermic reaction, also called a thermic reaction. Such a reaction occurs when an aluminum particle and a metal oxide, such as rust, are ignited by a heat source and chemically burn as a “Class D” fire (i.e., combustible metal).
The solid bulk aluminum alloys exposed in air to temperatures exceeding the liquidus convert to molten state but are not subjected to burning, generating smoke or hazardous fumes. After fire is extinguished the metal remains as a re-solidified pool. Similarly, temperatures leading to semisolid state will result in an integrity lost by a design. The resistance of aluminum to burning is controlled by a number of national standards including ASTM. This is in contrast to fine powders or flakes of aluminum, which are highly flammable and oxidize exothermically. The ignition behavior of aluminum powder is similar to other finely divided materials including iron and titanium, which also readily oxidize exothermically while in the powder form.
When structural collapse does not occur as a result of a fire, there is a need to evaluate the residual properties of overheated material to assess whether the structures should be dismantled, repaired, or directly reused. The influence of fire on mechanical properties depends on temperature and exposure time. The key difference from thermal stability issues discussed in this report is that alloys exposed to fire may not be designed at all for high temperature service. Therefore, even relatively low temperature such as 150 °C may lead to very poor performance during fire and the permanent property deterioration after fire.
There are a number of studies where the heat exposure on aluminum alloys that are not designed for high-temperature service, were evaluated. The objective was to accurately assess the post-fire performances of aluminum alloy structures. The models with predictive equations were developed, combining an influence of hardening factors and temperature on the material stress−strain relationship [148].
An example of research where an existing constitutive model for creep was modified in order to be used for fire-exposed alloys involved AA5083−O/H111 and AA6060−T66 grades [149]. For temperature range of 170 to 380 °C the model predicted properties for the 5xxx series alloys. The same AA5083−H116 and AA6061−T651 marine-grade aluminum alloys were subject of extensive mechanical testing to determine the residual mechanical behavior after fire exposure [150] ( ). The constitutive models were developed as a series of sub-models to predict (i) microstructural evolution, (ii) residual yield strength, and (iii) strain hardening after fire exposure. The properties of AA5000 series following a simulated fire exposure were evaluated in [151]. The 5xxx series alloys with different tempers resulted in residual strengths between 85 and 157 MPa following the fire exposure. Most alloys exhibited structural recovery between 100 to 280 °C followed by recrystallization between 300 to 340 °C. However, the AA5456−H116 alloy, which has the highest magnesium content, maintained 60% of room temperature yield strength. This alloy underwent recovery but did not have a clear recrystallization, preserving strength. Another study [152] found that the mechanical properties of AA6061−T6 were drastically reduced after exposure to temperatures exceeding 300 °C. For AA7075−T73, reduction in properties took place at lower temperature of 200 °C. An additional factor affecting post−fire mechanical properties of these two grades was a cooling rate from a relatively high fire temperature.
Open in a separate windowThermal stability is becoming the next frontier for aluminum alloys; understanding and overcoming limitations in this area would lead to substantial expansion in their structural applications, especially in aerospace and automotive sectors.
As practically all aluminum alloys are thermally unstable, with their properties being affected, to some extent, by service temperature and time, thermal stability is of concern throughout the entire temperature range of their applications. This includes grades essentially used at room temperatures, as is the case with aircraft components that may become warm due to exposure to sun, due to aerodynamic heating or heat transferred from engines, which can deteriorate alloys properties over years of service.
The major challenge in thermal stability of aluminum is, however, in increasing the upper service limit of high-temperature grades. There are efforts to develop new alloys with thermally stable microstructure through alloying aluminum with a variety of elements, in particular, transition, and rare earth metals. In parallel, there are efforts to generate more stable microstructure through novel processing routes, such as rapid solidification, powder metallurgy, mechanical alloying and additive manufacturing, engineering alloys in a liquid state prior to casting, and post-casting treatments.
The ultimate goal is to overcome the present knowledge and manufacturing barriers and develop aluminum alloys with superior properties that remain stable across the temperature and time space, required by modern designs.
This research was funded by the Program of Energy Research and Development (PERD) of Natural Resources Canada.
The author declares no conflicts of interest.
Several models have been developed to predict the residual mechanical constitutive behavior of 5083-H116 and 6061-T651 following a fire exposure. These models include simplistic empirical yield strength models and physically-based constitutive models for residual yield strength.
Summers, et al. (2014) developed empirical models to estimate the residual yield strength of 5083-H116 and 6061-T651 after a fire. Conservative estimates of the residual yield strength after infinite isothermal exposure, i.e., infinite time at a given temperature, are shown in Figure 39 (5083-H116) and Figure 40 (6061-T651). The conservative estimates were determined using the residual yield strength models in Ref. (Summers 2014). The time-temperature dependence of residual yield strength should be considered for shorter duration exposures. Material heating during a fire may be idealized as linear (ramp) heating followed by isothermal heating. Aluminum alloy structural members have been measured to approximate such a heating profile during standard fire resistance tests (Suzuki et al. 2005).
Figure 39Comparison of 5083-H116 residual yield strength predicted using the model described through Eqns. (13) – (15) and experimental data after heating at 5, 25, and 250°C/min.
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Figure 40Comparison of 6061-T651 residual yield strength estimated using Eq. (19) and experimental data after heating at 5, 25, and 250°C/min.
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Thus, empirical models have been developed to estimate residual yield strength after linear heating (experimental data in Ref. (Summers 2014)) and isothermal heating (models in Ref. (Summers 2014)). The linear heating empirical models are valid within the bounds of the heating rates tested, i.e., 5 – 250°C/min. Lower heating rates may be conservatively approximated using the isothermal heating empirical models.
5083-H116 residual yield strength was estimated for linear heating using the following relations:
$$ {T}_c\le 100{}^{\circ}C\kern2.5em {\sigma}_y={\sigma}_{y,AR} $$
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(13)
$$ 100{}^{\circ}C<{T}_c\le 280{}^{\circ}C\kern2.5em {\sigma}_y=\left(-0.24\right)\ {T}_c+a $$
(14)
$$ {T}_c>280{}^{\circ}C\kern2em {\sigma}_y=\frac{\sigma_{y,AR}+{\sigma}_{y,RX}}{2}-\frac{\sigma_{y,AR}-{\sigma}_{y,RX}}{2} \tanh \left[\phi \left({T}_c-{T}_k\right)\right] $$
(15)
where T c is the final exposure temperature (°C), σ y is the estimated residual yield strength (MPa), and a (MPa), ϕ (-), and T k (°C) are heating rate dependent parameters. The as-received (σ y,AR = 277 MPa) and recrystallized (σ y,RX = 120 MPa) yield strengths are taken as that from experiment (Figure 20a). The remaining parameters, given in Table 5, were determined by non-linear least squares regression for each heating rate. The empirical evolution models in Eqs. (13) – (15) are compared against experimental data in Figure 39 with good agreement. Note, the effect of heating rates between 5°C/min and 250°C/min may be estimated using interpolation.
Table 5 Parameters for the 5083-H116 linear heating empirical model in Eqs. ( 13 ) – ( 15 )Full size table
The isothermal exposure empirical models were developed using the 5083-H116 residual yield strength model from Ref. (Summers 2014). The isothermal behavior is separated into two regions dependent on whether the material initiates recrystallization within 10 hours of exposure. This was determined to be 230°C. The relations are as follows
$$ {T}_c\le 230{}^{\circ}C\kern2em {\sigma}_y={\sigma}_{y,AR}{(bt)}^c $$
(16)
$$ {T}_c>230{}^{\circ}C\kern2em {\sigma}_y=\left({\sigma}_{y,AR}-{\sigma}_{y,RX}\right) \exp \left[dt\right]+{\sigma}_{y,RX} $$
(17)
where t is time (s) and b (1/s), c (-), and d (1/s) are temperature-dependent parameters defined as
$$ parameter=\alpha \exp \left(\beta {T}_{iso}\right) $$
(18)
where T iso is the isothermal exposure temperature (°C) and α (units dependent on parameter) and β (1/°C) are fitting parameters, which are given in Table 6 for parameters in Eqs. (16) and (17).
Table 6 5083-H116 isothermal empirical model parameter constants for use in Eq. ( 18 )Full size table
6061-T651 residual yield strength was estimated for linear heating using the following relation
$$ {\sigma}_y=\frac{\sigma_{y,AR}+{\sigma}_{y, min}}{2}-\frac{\sigma_{y,AR}-{\sigma}_{y, min}}{2} \tanh \left[\phi \left({T}_c-{T}_k\right)\right] $$
(19)
where σ y,min (MPa), ϕ, and T k are heating rate dependent parameters. The as-received yield strength (σ y,AR = 325 MPa) is that from experiment (Figure 20b). The remaining parameters, given in Table 7, were determined by non-linear least squares regression for each heating rate. The empirical evolution model in Eq. (19) is compared against experimental data in Figure 40 with good agreement. As with 5083-H116, interpolation may be used to estimate heating rates between the relation bounds.
Table 7 Parameters for the 6061-T651 linear heating empirical model in Eq. ( 19 )Full size table
The empirical isothermal exposure model was developed using the residual yield strength evolution model from Ref. (Summers 2014). The relation is as follows
$$ {\sigma}_y=\left({\sigma}_{y,AR}-e\right) \exp \left[ ft\right]+e $$
(20)
where e (MPa) and f (1/s) are temperature-dependent functions defined using Eq. (18). α and β in Eq. (18) are given for 6061-T651 in Table 8.
Table 8 6061-T651 isothermal empirical model parameter constants for use in Eq. ( 18 )Full size table
A physically-based constitutive model for strain hardened aluminum alloys based on kinetically (time-temperature) dependent microstructural evolution is detailed, including models for residual yield strength and strain hardening behavior. This model was previously implemented by (Summers 2014) for 5083-H116.
The physically-based constitutive models utilize microstructural evolution models to predict the residual mechanical state after elevated temperature exposure. The governing microstructural processes in 5xxx-series aluminum alloys are recovery and recrystallization (Dieter 1976). Reduction in the α-matrix Mg solute concentration also affects residual strength; however, this occurs at much longer time scales than expected in a fire scenario (refer to Ref. (Summers et al. 2014) for further discussion). Recovery is the process by which a previously deformed material lowers its internal energy state at low annealing temperatures (Dieter 1976), resulting in dislocation structure (dislocation cells/subgrains) coarsening (Xing et al. 2006; Furu et al. 1995; Hasegawa and Kocks 1979; Verdier et al. 1998b). In the static case, recovery proceeds as a thermally activated, kinetic process (Furu et al. 1995). Recrystallization is the primary process by which the stored energy of deformation (from material processing) is released in strain hardened aluminum alloys (Doherty et al. 1997). The recrystallization process, including grain nucleation, migration, growth, and impingement, has been studied extensively (Bay and Hansen 1979; Bay and Hansen 1984; Fujita and Tabata 1973; Huang and Humphreys 1999; McQueen and Ryum 1985; Vandermeer and Rath 1990; Jones et al. 1979; Huang and Humphreys 2012), including development of predictive models, e.g., the classical uniform impingement KJMA model (Kolmogorov 1937; Johnson and Mehl 1939; AIME 135:416 and Avrami 1939), and physically representative models, e.g., the linear/uniform impingement microstructural path model of Vandermeer and Juul Jensen (Vandermeer and Juul Jensen 2001; Vandermeer and Juul Jensen 1994). Refer to Summers (Summers 2014) for further details regarding the background and theoretical underpinnings of the various models presented in the subsequent sections.
A microstructure-based residual yield strength model was also developed for 5083-H116. Non-isothermal recovery and recrystallization models were implemented to predict microstructural evolution, and its effect on strength, after prior thermal exposure. The models were developed considering non-isothermal thermal exposures, which approximate the initial transient heating during a fire (see Summers (2014)).
Aluminum alloy as-received and residual yield strength is governed by the relative state and magnitude of the microstructural strengthening contributions. For 5083-H116, this includes (i) the friction stress (σ 0), (ii) the solid solution content (σ ss ), (iii) precipitate contributions (σ p ), (iv) grain contributions (Δσ g ), and (v) subgrain contributions (Δσ sg ). These are linearly superposed to calculate the total yield strength (σ y ) as
$$ {\sigma}_y={\sigma}_0+{\sigma}_{ss}+{\sigma}_p+\Delta {\sigma}_{sg}+\Delta {\sigma}_g $$
(21)
Linear superposition is assumed valid as the individual microstructural features strengthen at different length scales, thus there is negligible interaction. The solid solution strengthening contribution, σ ss , is assumed constant due to the short duration exposures expected during fire (Summers et al. 2014). Precipitate strengthening, σ p , is considered negligible due to a low concentration of intermetallic precipitates as observed during TEM analysis (Summers 2014). The subgrain strengthening contribution, Δσ sg , is reduced by recovery and is annihilated during recrystallization; therefore, recovery and recrystallization models were implemented to predict Δσ sg evolution after prior thermal exposure. The grain strengthening contribution, Δσ g , is solely dependent on recrystallization.
The non-isothermal residual yield strength model is given as
$$ {\sigma}_y={\sigma}_{pure}+H{\left({C}_{Mg}\right)}^n+\left[{X}_{RX}^{3/4}{k}_g{d}_{AR}^{-1/2}+\left(1-{X}_{RX}\right){k}_g{d}_{AR}^{-1/2}\right]+\left(1-{X}_{RX}\right)G\sqrt{b{\theta}_m}{\left(\frac{\delta_{AR}}{X_{RV}^2}\right)}^{-1/2} $$
(22)
The first parameter on the right hand side includes the friction stress and effects of other minor hardening solutes (i.e., Fe and Si). The second parameter is from the solid solution strengthening model. The bracketed parameter group implements grain strengthening with the first and second terms representing grain nucleation and growth, and grain annihilation; respectively. Both processes are a function of the recrystallized fraction, X RX . The fifth term on the right hand side implements subgrain strengthening, including subgrain coarsening as a function of the fraction recovered, X RV , and subgrain annihilation, due to recrystallization, as a function of X RX .
The residual yield strength is predicted using Eq. (22) with the fraction recovered, X RV , and fraction recrystallized, X RX , predicted by non-isothermal recovery and recrystallization models. Refer to Summers et al. (2014) and Summers (2014) for model details. Comparison with experimental data is shown in Figure 41. Model parameters are given in Table 9.
Figure 415083-H116 residual yield strength model predictions (lines) compared against experimental data (symbols).
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Table 9 5083-H116 residual yield strength model parametersFull size table
The experimentally measured residual yield strength after thermal exposure, including its time-temperature (heating rate) dependence, is well represented by the residual yield strength model predictions in Figure 41. The initial yield strength reduction is well predicted by the model, specifically recovery and subgrain strengthening models. The onset of recrystallization is also captured by the model. The yield strength evolution during recrystallization is predicted by the grain and subgrain strengthening models; the kinetics are predicted by the recrystallization model. The predicted yield strength after recrystallization has completed (126 MPa) is also in agreement with experimental data, with predicted contributions of σ pure = 19 MPa, σ ss = 75 MPa, Δσ sg = 0 MPa, and Δσ g = 32 MPa.
Aluminum alloy strain hardening has been supposed to be the competitive evolution of the dislocation structure in terms of dislocation storage and dynamic recovery (dislocation annihilation or rearrangement) (Mecking and Kocks 1981; Estrin and Mecking 1984; Kocks 1976). Verdier and colleagues (Verdier et al. 1998a, b) considered the effects of a cellular dislocation structure (i.e., subgrains in 5083-H116) on strain hardening, including dislocation structure evolution during recovery. Recovery is shown to negligibly affect hardening rate except at stresses near yield (refer to Figure 19a). Recrystallization causes a significant hardening rate reduction at constant stress. The subgrains in 5083-H116 sequentially evolve during recovery (subgrain growth) and recrystallization (subgrain annihilation). Thus, subgrain annihilation is the mechanism which causes the hardening rate reduction during recrystallization. The KME model modified by Verdier et al. (1998a) was thus further adapted by Summers (2014) to include the effects of subgrain annihilation on 5083-H116 plastic deformation. Non-isothermal recovery and recrystallization models were implemented to predict subgrain and grain evolution.
The modified KME constitutive law (Verdier et al. 1998a) is defined as
$$ \frac{d\sigma }{d\varepsilon }={\theta}_0+\frac{P_1}{\sigma }-{P}_2\sigma $$
(23)
where P 1 (MPa2) represents subgrain dislocation storage and P 2 (-) is total dynamic recovery. P 1 and P 2 were modified by Summers (2014) as
$$ {P}_1=\left(1-{X}_{RX}\right){M}^3{\left(\alpha G\right)}^2\frac{b}{2\delta }\ \mathrm{and}\ {P}_2=\frac{\theta_0}{\sigma_{sat,0}}+\left(1-{X}_{RX}\right)\frac{K_{sg}M}{2\delta } $$
(24)
where δ is the predicted instantaneous subgrain size (nm) from the non-isothermal recovery model and σ sat,0 is the theoretical saturation stress reached at infinite strain (σ sat,0 = MαGb/L 0). After recrystallization completes, i.e., X RX = 1, the modified KME constitutive law reduces to the classical KME law, which does not account for dislocation structure effects.
Strain hardening is predicted using Eq. (24) with the predicted fraction recovered, X RV , and fraction recrystallized, X RX , predicted by non-isothermal recovery and recrystallization models. Refer to Summers (2014) for model details. All parameters of the modified KME model are provided in Table 10.
Table 10 Modified KME constitutive law parameters for 5083-H116Full size table
The modified KME model predictions are compared with experimental data (5, 25, and 250°C/min to 320°C) in Figure 42. The temperature chosen (320°C) spans a range of possible material states: fully recrystallized (5°C/min), partially recrystallized (25°C/min), and partially recovered (250°C/min). It is evident the model is capable of predicting strain hardening behavior after prior thermal exposure. The agreement between predictions and experiment is good at the shown conditions, which encompass those possible in 5083-H116. The strain hardening behavior approaches approximately the same saturation stress for all conditions as is expected from experiment.
Figure 425083-H116 strain hardening after prior thermal exposure to 320°C at different heating rates as modeled using a modified KME constitutive law.
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A physically-based constitutive model for precipitation hardened aluminum alloys based on kinetically (time-temperature) dependent microstructural evolution is detailed, including models for residual yield strength and strain hardening behavior. This model was previously implemented by Summers (2014) for 6061-T651.
Numerous models are available in the literature for precipitate evolution, including analytical, internal variable models (Grong and Shercliff 2002; Myhr and Grong 1991a; Myhr and Grong 1991b; Bratland et al. 1997) and numerical class size models (Simar et al. 2007; Gallais et al. 2008; Esmaeili and Lloyd 2005; Deschamps et al. 1999; Myhr and Grong 2000; Myhr et al. 2001; Myhr et al. 2002; Nicolas and Deschamps 2003; Myhr et al. 2004; Khan et al. 2008; Perez et al. 2008; Bardel et al. 2014; Bahrami et al. 2012). The analytical approach fails when complicated diffusion processes are involved due to the interaction of different size precipitates (Grong and Shercliff 2002). This is the case for commercial alloys, e.g., 6061, in an aged (hardened) state, e.g., T4 or T6. A numerical class size model, which implements the complete precipitate size distribution (PSD), is therefore required. PSD evolution at elevated temperatures is commonly modeled using the Kampmann-Wagner numerical (KWN) model (Kampmann and Wagner 1984) is commonly implemented (Simar et al. 2007; Gallais et al. 2008; Esmaeili and Lloyd 2005; Deschamps et al. 1999; Myhr and Grong 2000; Myhr et al. 2001; Myhr et al. 2002; Nicolas and Deschamps 2003; Myhr et al. 2004; Khan et al. 2008; Perez et al. 2008; Bardel et al. 2014; Bahrami et al. 2012) in a finite difference formulation (Myhr and Grong 2000). The KWN model describes the nucleation, growth, and dissolution processes using a diffusion-based methodology assuming spherical precipitates.
The KWN model is an example of the so-called classical nucleation and growth theories (CNGTs) which have been widely implemented for modeling PSD evolution, including growth, nucleation, and dissolution. Myhr et al. (2001) and Deschamps and Bréchet (1998) initially adapted the KWN model to Al alloys by implementing a unique β″/β′ phase, thereby simplifying the complex precipitation sequence. This approach was extended to non-isothermal heat treatments in further work by (Myhr et al. 2004). These initial models have been extensively implemented for Al alloys (Simar et al. 2007; Gallais et al. 2008; Myhr et al. 2002; Myhr et al. 2004; Perez et al. 2008; Bardel et al. 2014; Bahrami et al. 2012) including adaptations for heterogeneous precipitation (Gallais et al. 2008; Myhr et al. 2002), various metastable precipitates (Myhr et al. 2002), ternary/quaternary phases (Gallais et al. 2008), and non-spherical precipitates (Bardel et al. 2014; Bahrami et al. 2012). (Perez et al. 2008) discussed the necessity of modeling PSD evolution using a class size approach rather than a mean radius approximation.
An integrated modeling approach was implemented by Summers (2014) to predict 6061-T651 residual yield strength and strain hardening as a function of PSD evolution. The KWN model implemented by Simar et al. (2007) provides a balance between representative capability and limited complexity. In this model, nucleation, growth, and dissolution processes are assumed to occur as spherical precipitates with an equivalent radius defined based on equivalent precipitate length. The PSD interaction and evolution during growth/dissolution were modeled using an Eulerian multi-class approach described by Perez, et al. (2008). The residual yield strength model uses PSD dependent solid solution and precipitate strengthening models. This section provides a summary of model development, including underlying assumptions as well as a description of basic model features. Refer to Summers (2014) for a detailed model description.
A precipitate-dislocation interaction was developed to predict 6061-T651 residual yield strength. The KWN model is implemented to capture the yield strength evolution after non-isothermal thermal exposure.
6061 residual yield strength is governed by the state of several microstructural strengthening contributions, specifically (i) the friction stress (σ 0), (ii) the solid solution content (Δσ ss ), (iii) precipitate contributions (Δσ p ), (iv) grain contributions (σ g ), and (v) dislocation forest hardening contributions (σ g ). These are linearly superposed to calculate the total yield strength (σ y ) as:
$$ {\sigma}_y={\sigma}_0+\Delta {\sigma}_{ss}+\Delta {\sigma}_p+{\sigma}_g+{\sigma}_d $$
(25)
Linear superposition is assumed valid as the individual microstructural features strengthen the alloy at different length scales, thus negligible interaction is assumed. For 6061, the friction stress of pure aluminum is taken as the commonly accepted 10 MPa. The grain strengthening contribution (σ g ) is assumed negligible compared to that for solutes and precipitates. Dislocation forest hardening is given by the Taylor relation (σ d = MαGbρ -1/2); however, σ d is assumed to be much smaller than Δσ p and is thus ignored. Solid solution, Δσ ss , and precipitate, Δσ p , strengthening evolve due to precipitate nucleation, growth, and dissolution; the KWN model was implemented to account for these processes.
The non-isothermal yield strength model is given as
$$ {\sigma}_y={\sigma}_0+{H}_{M{g}_2Si}{C}_{Mg}^{2/3}+{H}_{Cu}{C}_{Cu}^{2/3}+\frac{M}{b}{\left(2{k}_{\Gamma}G{b}^2\right)}^{-1/2}\sqrt{\frac{3{f}_v}{2\pi }}\frac{{\overline{F}}^{3/2}}{\overline{r}} $$
(26)
where the mean obstacle (precipitate) strength is given by \( \overline{F} \). PSD evolution is implemented in the model as the Mg concentration in the matrix, C Mg , mean precipitate radius, \( \overline{r} \), precipitate volume fraction, f v , and mean precipitate strength, \( \overline{F} \). These parameters are a function of the PSD predicted by the KWN model. Refer to Summers (2014) for KWN model details and parameters. Model parameters are shown in Table 11.
Table 11 6061-T651 residual yield strength model parametersFull size table
The experimental evolution of yield strength after thermal exposure is well represented by model predictions in Figure 43. As expected, thermal exposures below 250°C do not cause a significant reduction in yield strength. Above 300°C, the yield strength decreases until precipitate and Mg aluminum matrix Mg content reaches an equilibrium state. The significant reduction in yield strength (~240 MPa reduction) is governed by significant precipitate growth and dissolution. The residual yield strength also depends on heating rate: the lower the heating rate, the lower the residual yield strength at a given maximum temperature. The effect of heating rate on yield strength is well captured by the model (Figure 43).
Figure 436061-T651 residual yield strength model predictions (lines) compared against experimental data (symbols).
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In the case of precipitation hardened alloys (e.g., 6061-T651), several models have been proposed to predict strain hardening behavior as a function of microstructure. Thermal exposure above ~250°C results in a transition from precipitate shearing by dislocations to Orowan looping (storage of a bypassing dislocation by pinning, bowing, and unpinning) due to precipitate growth. Several authors (Estrin 1996; Cheng et al. 2003; Poole and Lloyd 2004) considered the additional dislocation storage of Orowan loops through introduction of a term inversely proportional to precipitate spacing in the dislocation glide plane, which is effectively a function of precipitate volume fraction.
As discussed previously, aluminum alloy strain hardening is commonly modeled using the Kocks-Mecking-Estrin (KME) model (Mecking and Kocks 1981; Estrin and Mecking 1984; Hancock 1976; Kocks and Mecking 2003). Estrin (1996) generalized the KME model to include effects present in solute and precipitate hardened Al alloys. A new term was introduced to the KME formalism to account for Orowan loop storage around non-shearable precipitates. A similar modification was proposed by Barlat et al. (2002). Simar et al. (2007) adapted such an approach to model strain hardening of 6005A-T6 after thermal exposures such as those experienced during welding. A generalized form of the KME law is presented, focusing on the effects of Orowan loop storage stability on dislocation storage and dynamic recovery rates.
For 6061-T651, the KME relation in the Palm-Voce formalism is given as (Simar et al. 2007)
$$ \frac{d\sigma }{d\varepsilon }=\theta -\beta \left(\sigma -{\sigma}_y\right) $$
(27)
where θ (MPa) and β (-) are apparent values for the dislocation storage rate and dynamic recovery used for commercial alloys, e.g., 6061-T651. θ and β are modified to include various microstructural effects as follows
Orowan loop storage efficiency: φ is defined to include the effects of precipitate radius (i.e., the transition in precipitate-dislocation interaction from the age-hardened state to loss of coherency) on the dislocation storage rate, θ. The (1/r) term in Eq. (28) is multiplied by φ.
Dynamic precipitation: θ dp is defined to include the effects of dynamic precipitation on the dislocation storage rate. The extent of dynamic precipitation during plastic deformation is dependent on the relative concentration of Mg in the Al matrix. θ is modified by linearly superposing θ 0 (i.e., the theoretical dislocation storage rate) and θ dp in Eq. (28).
Orowan loop storage: β is defined as a function of the probability of self-annihilating or encountering a stored dislocation (Orowan loop) during a given time interval. The mean number of precipitates encountered before two dislocations meet was determined using an assumed Poisson distribution.
Yield strength effect on β: β 0 is defined as related to the material’s yield strength with a theoretical minimum obtained for a material in super saturated solid solution with natural or artificial aging.
The expressions for θ and β in Eq. (27) are thus defined as
$$ \frac{\theta }{G}=\frac{\theta_0+{\theta}_{dp}}{2G}+\sqrt{{\left(\frac{\theta_0}{2G}\right)}^2+{\alpha}^2{M}^3\beta \varphi \left(\frac{b}{\overline{r}}\right)\sqrt{\frac{3{f}_v}{2\pi }}} $$
(28)
$$ \beta ={\beta}_0 \exp \left(-\sqrt{\frac{3}{2\pi }}\frac{\sqrt{f_v}{L}_0\varphi }{\overline{r}}\right)+\frac{2{y}_p}{b}\left(1- \exp \left(-\sqrt{\frac{3}{2\pi }}\frac{\sqrt{f_v}{L}_0\varphi }{\overline{r}}\right)\right) $$
(29)
The mean precipitate radius, \( \overline{r} \), and volume fraction, f v , are calculated using the PSD predicted by the KWN model (refer to Summers et al. (2014) for further details).
The generalized KME model dislocation storage rate, θ, and dynamic recovery rate, β, are detailed in Eqs. (28) and (29), respectively. Model parameters were identified through analysis using tensile mechanical tests of specimens previously heated at 20°C/min. The identification procedure is described in detail by Summers et al. (2014). All parameters of the KME model in the generalized relations for θ (Eq. (28)) and β (Eq. (29)) are provided in Table 12.
Table 12 Modified KME model parameters for 6061-T651Full size table
The modified KME model predictions are compared with experimental data (material heated at 5, 25, and 250°C/min to 350°C) in Figure 44. The temperature (350°C) was chosen as it coincides with significant PSD evolution. The tested heating rates span a large range of possible PSDs at this temperature. As is shown, the model shows good agreement with the experimental data. Note, somewhat competing effects of θ and β occur for 5°C/min (θ ≈ 3600 MPa, β ≈ 34) and 25°C/min (θ ≈ 3350 MPa, β ≈ 31). This results in a nearly identical prediction of strain hardening; however, the predicted strain hardening at both heating rates remains reasonable. Overall, the evolution in strain hardening behavior at different heating rates is well represented by the model.
Figure 446061-T651 strain hardening after prior thermal exposure to 350°C at different heating rates as modeled using a modified KME constitutive law.
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The residual constitutive behavior characterized and modeled in the previous sections was extended to structural sections and prior heating regimens which better represent that in a structural environment. The commercial finite element analysis package, Abaqus, was used to model the residual mechanical behavior of these sections.
A series of small-scale thermostructural experiments was performed on 6061-T6 extruded square hollow sections. Sample geometries were 38.1 mm wide by 304.8 mm long with a 3.2 mm wall thickness. Similar to previous residual behavior experiments, these were conducted by thermally exposing the specimens, cooling to ambient conditions, then mechanically tested. Thermal exposures consisted of single-sided heating using a steel radiative plate followed immediately by water quenching. Two heat flux exposures were used – 50 and 70 kW/m2. These exposures were selected as they resulted in steady-state exposed surface temperatures of about 350 and 400°C, respectively. Three exposure times were used – 300, 600, and 1200 s. Note, samples reached thermal equilibrium after about 600 s. The full-field temperatures of the sample side were measured during heating of each sample using a FLIR SC655 thermal infrared camera (640 × 480 pixels, 7.5 – 14 μm wavelength).
After thermal exposure and water quenching, the square hollow sections were mechanically tested in four-point flexure. 10 mm diameter stainless steel rollers were used with an outer and inner roller spacing of 259 and 75 mm, respectively. All samples were oriented such that the inner span rollers applied load to the unexposed surface. This orientation was selected to simulate thermal exposure of the ceiling in compartment with loading from above.
The thermostructural experiments were modeled using the FEA package, Abaqus. Similar to the experiments, modeling was performed sequentially: a thermal model followed by a mechanical model. The thermal model includes the 6061 square hollow section and the steel radiant heater plate. The measured full-field temperatures of the steel plate heater were prescribed and the resultant full-specimen thermal response was predicted from the radiation exchange between the radiant heater and sample. Convective losses from the exterior surfaces were modeled based on isothermal vertical surfaces at 325°C. The convective heat transfer coefficient was calculated as 9 W/m2-K using standard empirical correlations (Incropera et al. 2007).
Mechanical loading was modeled using a quasi-static displacement model sequentially coupled to the thermal model. The 10 mm rollers were included in the model. Mesh densities varied along the sample length with fine meshes at loading and support points. A simple hard contact model was used between the rollers (assumed a rigid body) and the sample. No tangential frictional forces were considered as forces were relatively low and a graphite-based lubricant was used in testing. Mechanical loading was modeled to a simulated cross-head displacement of 20 mm or when the model no longer converged. The reduced residual mechanical properties of the 6061 sample were input as that from Summers, et al. (2014) for linear heating rates of 5 and 25°C/min.
A comparison of the measured full-field temperatures and those predicted by the thermal model is shown in Figure 45 for a 50 kW/m2 heat flux. The thermal model captures the thermal gradient from the exposed to unexposed surface. For this exposure, the measured and predicted temperatures at all locations are generally within 10°C. For all tests, the left side is cooler due to non-uniformities in the radiant heater plate temperature. Comparison of the measured and predicted temperatures for the 70 kW/m2 exposure is shown in Figure 46. The thermal model predicts temperatures within 5% of that measured; however, a larger amount of error exists towards the unexposed surface. This is possibly due to the assumed constant temperature (325°C) convection coefficient while these samples reach temperatures above 450°C on the exposed surface. Transient temperature measurements and predictions are also shown in Figure 47 for a location 3.2 mm from the exposed surface and at the mid-length. The model predicts the transient temperature response within 5% of experiment for both exposures.
Figure 45Measured and predicted maximum exposure temperatures for a 50 kW/m2 exposure of a 6061 square hollow section for (a) 300 s, (b) 600 s, and (c) 1200 s.
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Figure 46Measured and predicted maximum exposure temperatures for a 70 kW/m2 exposure of a 6061 square hollow section for (a) 300 s, (b) 600 s, and (c) 1200 s.
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Figure 47Measured (solid lines) and predicted (dashed lines) transient thermal response 3.2 mm from the exposed surface along the square hollow section mid-length.
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FEA load-displacement predictions are compared against experiment in Figure 48 for the 50 kW/m2 exposure. The mechanical model agrees well with the as-received sample mechanical response; however, the model tends to over-predict sample strength after prior thermal exposure. This may possibly be due to the slight discrepancy in material type used in property definitions (T651 plate) and these experiments (T6 extrusion). Despite this, the peak load is reasonably predicted for each test. The relationship between maximum exposure temperature and peak load is shown in Figure 49. Model predictions are shown for mechanical properties obtained after linear heating at 5 and 25°C/min (Summers, 2014). As expected, experiment shows decreasing peak load with increasing maximum exposure temperature. This is also reflected by model predictions. At 350°C, lower peak loads resulted from the 50 kW/m2 exposure than at 70 kW/m2. This is also as expected due to the time required to reach 350°C at the respective heat fluxes.
Figure 48Measured (solid lines) and predicted (dashed lines) load-displacement response of 6061 square hollow section following prior thermal exposure at 50 kW/m2.
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Figure 49Relationship between peak load and maximum thermal exposure temperature of 6061 square hollow sections after prior thermal exposure at 50 and 70 kW/m2. Model predictions (lines) are shown for mechanical properties after prior heating at 5 and 25°C/min (Summers et al. 2014).
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