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Metallurgical and Materials Transactions A
Erschienen in: Metallurgical and Materials Transactions A 13/2012

01.12.2012

Assistance of Novel Artificial Intelligence in Optimization of Aluminum Matrix Nanocomposite by Genetic Algorithm

verfasst von: Ali Mazahery, Mohsen Ostad Shabani

Erschienen in: Metallurgical and Materials Transactions A | Ausgabe 13/2012

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Abstract

In this article, a genetic algorithm (GA) is used to predict the mechanical properties and to optimize the process conditions of Al nanocomposites. An artificial intelligence method is also implemented as an assisting tool for engineering tasks of GAs. The principle of the survival of the fittest is applied to produce successively superior approximations to a solution. A population of points at each iteration is generated. The population approaches an optimal solution. The next population by computations that involve random choices is selected. The optimal volume percentage of SiC, cooling rate, and temperature gradient are computed to be 2.84 pct, 283 K/s (10 °C/s), 1273 K/m (1000 °C/m), respectively.
Vorheriger Artikel Sintering of Titanium with Yttrium Oxide Additions for the Scavenging of Chlorine Impurities
Nächster Artikel Nanoscale Deformation Behavior of Phase-Reversion Induced Austenitic Stainless Steels: The Interplay Between Grain Size from Nano-Grain Regime to Coarse-Grain Regime

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Metadaten
Titel
Assistance of Novel Artificial Intelligence in Optimization of Aluminum Matrix Nanocomposite by Genetic Algorithm
verfasst von
Ali Mazahery
Mohsen Ostad Shabani
Publikationsdatum
01.12.2012
Verlag
Springer US
Erschienen in
Metallurgical and Materials Transactions A / Ausgabe 13/2012
Print ISSN: 1073-5623
Elektronische ISSN: 1543-1940
DOI
https://doi.org/10.1007/s11661-012-1339-6

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