Machine Learning Prediction of Aluminum Alloy Stress–Strain Curves at Variable Temperatures with Failure Analysis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s11668-023-01833-2.pdf
Reference54 articles.
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2. R.E. Sanders, R. Sanders Jr., Technology innovation in aluminum products. JOM. 53, 21–25 (2001). https://doi.org/10.1007/s11837-001-0115-7
3. H. Agarwal, A.M. Gokhale, S. Graham, M.F. Horstemeyer, Void growth in 6061-aluminum alloy under triaxial stress state. Mater. Sci. Eng. A. 341, 35–42 (2003). https://doi.org/10.1016/s0921-5093(02)00073-4
4. Liu N, Ma L, Liu AJ, Zhang Z, Chen MH, Wu YC (2020) Effect of heat treatment on microstructure and mechanical properties of 6061 aluminum alloy containing Sc. Cailiao Rechuli Xuebao Transactions Mater Heat Treat. https://doi.org/10.13289/j.issn.1009-6264.2020-0072
5. Cai J (2016) Effect of heat treatment on microstructure and mechanical properties of 6061 aluminium alloy. Tezhong Zhuzao Ji Youse Hejin/Special Cast Nonferrous Alloy. https://doi.org/10.15980/j.tzzz.2016.09.027
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