The effects of microstructural stability on the compressive response of two cast aluminum alloys up to 300 °C
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Science & Technology Division; Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary Research and Graduate Education
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Science & Technology Division; Indian Inst. of Technology (IIT), Kharagpur (India). Materials Science Center
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Science & Technology Division
Here in this study, the high temperature compressive response of cast aluminum alloys 319 and RR350 is compared in light of their microstructures. The 319 alloy is widely used in thermally critical automotive applications and provides a baseline for comparison with the RR350 alloy, whose microstructural stability at high homologous temperatures was recently reported. Cylindrical compression samples from each alloy were tested at four temperatures up to 300 °C at a constant true strain rate that was varied over four orders of magnitude. Although both alloys are strengthened by metastable precipitates (nominally Al2Cu) in the as-aged condition, their mechanical response diverges at temperatures greater than 250 °C as the strengthening precipitates evolve in the 319 alloy and retain their as-aged morphology in the RR350 alloy. Deformation mechanisms of each alloy are examined using microstructural analysis and empirical activation energy calculations. The stability of the θ' phase in the RR350 alloy leads to effective precipitation hardening at homologous temperatures up to 0.6 and an extensive regime of grain boundary controlled deformation.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- Work for Others (WFO); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)
- Grant/Contract Number:
- AC05-00OR22725; DE‐AC05‐00OR22725
- OSTI ID:
- 1366385
- Alternate ID(s):
- OSTI ID: 1495821
- Journal Information:
- Materials Science and Engineering. A, Structural Materials: Properties, Microstructure and Processing, Vol. 700, Issue C; ISSN 0921-5093
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Machine Learning for Thermal Transport Analysis of Aluminum Alloys with Precipitate Morphology
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journal | January 2019 |
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