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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 4/2015

01.05.2015 | Original Article

Refined microstructure of compo cast nanocomposites: the performance of combined neuro-computing, fuzzy logic and particle swarm techniques

verfasst von: Mohsen Ostad Shabani, Mohammad Reza Rahimipour, Ali Asghar Tofigh, Parviz Davami

Erschienen in: Neural Computing and Applications | Ausgabe 4/2015

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Abstract

Aluminum metal matrix composites (MMCs) reinforced with nanoceramics are ideal materials for the manufacture of lightweight automotive and other commercial parts. Adaptive neuro-fuzzy inference system combined with particle swarm optimization method is implemented in this research study in order to optimize the parameters in processing of aluminum MMCs. In order to solve the problems associated with poor wettability, agglomeration and gravity segregation of nanoparticles in the melt, a mixture of alumina and aluminum particles was used as the reinforcement instead of raw nanoalumina. Microstructural characterization shows dendritic microstructure for the sand cast and non-dendritic microstructure for the compo cast samples. The fine equiaxed structure of compo cast nanocomposite arises from copious nucleation triggered by a pressure.
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Nächster Artikel Squirrel-cage induction generator system using hybrid wavelet fuzzy neural network control for wind power applications

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Metadaten
Titel
Refined microstructure of compo cast nanocomposites: the performance of combined neuro-computing, fuzzy logic and particle swarm techniques
verfasst von
Mohsen Ostad Shabani
Mohammad Reza Rahimipour
Ali Asghar Tofigh
Parviz Davami
Publikationsdatum
01.05.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 4/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1724-8

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