Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7779
Title: Using recurrent neural networks for estimation of minor actinides' transmutation in a high power density fusion reactor
Authors: Übeyli, Mustafa
Übeyli, Elif Derya
Keywords: Minor actinides
Recurrent neural networks (RNNs)
Fusion reactor
Issue Date: 2010
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In this paper, recurrent neural networks (RNNs) were presented for the computation of minor actinides' transmutation with reactor's operation period. The results of the RNNs implemented for the computation of the change in the atomic density of minor actinides (Np-237, Am-241, Cm-242, Pu-238, Pu-239) and the results available in the literature obtained by using Scale 4.3 (Ubeyli, 2004) were compared. The results brought out that the proposed RNNs could provide an accurate computation of the atomic densities of minor actinides of the hybrid reactor with respect to operation period of reactor. (C) 2009 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2009.08.005
https://hdl.handle.net/20.500.11851/7779
ISSN: 0957-4174
1873-6793
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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