RETRACTED ARTICLE: Artificial neural networks for prediction Charpy impact energy of Al6061/SiC p -laminated nanocomposi
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ORIGINAL ARTICLE
Artificial neural networks for prediction Charpy impact energy of Al6061/SiCp-laminated nanocomposites Ali Nazari • Vahid Reza Abdinejad
Received: 16 March 2012 / Accepted: 22 May 2012 Ó Springer-Verlag London Limited 2012
Abstract In this work, Charpy impact energy of Al6061SiCp nanocomposites produced by mechanical alloying has been modeled by artificial neural networks in both crack divider and crack arrester configurations. Al6061 powders were mixed by 2, 3, and 5 vol % of SiC nanoparticles and ball-milled for 45 min. Afterward, the produced powders were hot-pressed in aluminum cans and then were extruded to produce a dense bulk. Charpy impact specimens were prepared from the produced samples in layered form with different adhesives and thickness of the layers. To build the model, training, validating, and testing was performed using 171 pair input-target data. The used data in the multilayer feed-forward neural networks models were arranged in a format of six input parameters including the thickness of layers, the number of layers, the adhesive type, the crack tip configuration, the content of SiC nanoparticles, and the test trial number. The output parameter was Charpy impact energy of the nanocomposites. The training, validating, and testing results in the neural network models have shown a strong potential for predicting Charpy impact energy of Al6061/SiCp nanocomposites in the considered range of input-target values. Keywords Al/SiCp nanocomposite Impact behavior Powder metallurgy Mechanical alloying Adhesive type Artificial neural networks
A. Nazari (&) V. R. Abdinejad Department of Materials Science and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran e-mail: [email protected]
1 Introduction Aluminum-based metal matrix composites with small amount of nanometer-range (\0.1 lm) discontinuous hard phases as reinforcement have attracted considerable research interest during recent years due to the potential for the development of novel composites with unique mechanical and physical properties [1]. The primary challenge when producing nanocomposites by introducing pre-fabricated nanoparticles into the matrix is homogeneous dispersion of the reinforcement particles in the matrix. One perspective to achieve this is via a powder metallurgy route involving high-energy milling [2]. In powder metallurgy method, after mixing the matrix and reinforcement, canning is used to densify the primary powder which results in protection of the powder from the environment as well as the following degassing and extrosion. Afterward, hot extrosion is used to access the highest possible density and mechanical properties [3]. Production of Aluminum metal matrix nanocomposites with nano SiC reinforcements by mechanical alloying is of interest of several researchers. Khadem et al. [4] investigated structural and morphological aspects of Al-5 vol %SiC nanocomposite powder produced by mechanical alloying. It was obtained that the increased milling time would result in the smaller pa
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