Artificial neural network approach for mechanical properties prediction of as-cast A380 aluminum alloy-Reference-Cited by-同舟云学术

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Artificial neural network approach for mechanical properties prediction of as-cast A380 aluminum alloy

Published:2022-06 Issue: Volume:31 Page:103301
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Lan Qiao,Wang Xingchen,Sun Jiangwei,Chang Zhiyu,Deng Qingchen,Sun Qicai,Liu Zehua,Yuan Lingyang,Wang Jiacheng,Wu Yujuan,Liu Baoliang,Peng Liming

Publisher

Elsevier BV

Subject

Materials Chemistry,Mechanics of Materials,General Materials Science

Reference45 articles.

1. Influences of roughness and heat treatment on high-cycle bending fatigue properties of A380 aluminum alloy under stress-controlled cyclic loading;Khisheh;Mater. Chem. Phys.,2021

2. J. Kaufman, E. Rooy, Aluminum alloy castings: properties, processes, and applications, 2004. 〈https://doi.org/10.31399/asm.tb.aacppa.9781627083355〉.

3. Role of Fe/Mn ratio and cooling rate on precipitation of iron intermetallics α-AlFeMnSi and β-AlFeSi in a 356 alloy;Castro-Román;Trans. Indian Inst. Met.,2015

4. Evolution of Fe based intermetallic phases in Al–Si hypoeutectic casting alloys: influence of the Si and Fe concentrations, and solidification rate;Gorny;J. Alloy. Compd.,2013

5. Effect of cooling rate and Fe/Mn weight ratio on volume fractions of α-AlFeSi and β-AlFeSi phases in Al–7.3Si–3.5Cu alloy;Belmares Perales;Met. Mater. Int.,2008

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