RETRACTED ARTICLE: Application of artificial neural networks for analytical modeling of Charpy impact energy of function
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ORIGINAL ARTICLE
Application of artificial neural networks for analytical modeling of Charpy impact energy of functionally graded steels Ali Nazari
Received: 15 August 2011 / Accepted: 22 October 2011 / Published online: 10 November 2011 Ó Springer-Verlag London Limited 2011
Abstract In the present study, the Charpy impact energy of ferritic and austenitic functionally graded steel produced by electroslag remelting has been modeled in crack divider configuration. To produce functionally graded steels, two slices of plain carbon steel and austenitic stainless steels were spot welded and used as electroslag remelting electrode. Functionally graded steel containing graded layers of ferrite and austenite may be fabricated via diffusion of alloying elements during remelting stage. Vickers microhardness profile of the specimen has been obtained experimentally and modeled with artificial neural networks. To build the model for graded ferritic and austenitic steels, training, testing and validation using, respectively, 174 and 120 experimental data were conducted. According to the input parameters, in the neural networks model, the Vickers microhardness of each layer was predicted. A good fit equation that correlates the Vickers microhardness of each layer to its corresponding chemical composition was achieved by the optimized network for both ferritic and austenitic graded steels. Afterward, the Vickers microhardness of each layer in functionally graded steels was related to the yield stress of the corresponding layer and by assuming Holloman relation for stress–strain curve of each layer, the area under each stress–strain curve was acquired. Finally, by applying the rule of mixtures, Charpy impact energy of functionally graded steels in crack divider configuration was found through numerical method. The obtained results from the proposed model are in good agreement with those acquired from the experiments.
A. Nazari (&) Department of Materials Science and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran e-mail: [email protected]
Keywords Chemical concentration profile Microhardness Charpy impact energy Crack divider Artificial neural networks ESR Ferritic FGS Austenitic FGS
1 Introduction FGMs are multiphase systems in which their composition varies gradually in some direction to obtain a unique mechanical, thermal and electrical property that distinguishes them from the conventional composites which in general are of discrete, piecewise nature with sharp interfaces [1–4]. There are not enough studies on the plastic behavior of FGMs. Among these few works, most of the researchers have been modeled their work with the aid of conventional flow theories that are the one of the best tools that has ever proposed. For example, some of them have tried to use J2 flow theory [5–7], but the empirical investigations have not been linked to the obtained results because of the difficulty of FGMs fabrication. Okolednik [8] although has used J integral concept to model several materials with yield s
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