Investigation of neutron-induced reaction cross section calculations for the fusion reactor structural materials using a
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ORIGINAL PAPER
Investigation of neutron-induced reaction cross section calculations for the fusion reactor structural materials using artificial neural networks VC ¸ apali* Department of Material Science and Nanotechnology, Usak University, 64200 Us¸ ak, Turkey Received: 15 September 2019 / Accepted: 17 March 2020
Abstract: Using artificial neural networks for an estimation of the nuclear reaction cross section data is discussed. Approximately rate of the fitting criteria is determined by the calculated experimental data obtained from using Variable Learning Rate Backpropagation (traingdx) algorithm in artificial neural networks. This method has been applied to obtain the cross section for 14–15 MeV neutron-induced (n,a) and (n,p) reactions in the fusion reactor structural materials. In comparison to the reaction cross section calculation by experimental cross sections reported in EXFOR, TALYS 1.9 and EMPIRE 3.2, the proposed method has better prediction ability when the target output has a large variation between the experimental and the calculated data. This study is substantial for the new method validation development of the nuclear model approaches with the increased prediction power of the neutron-induced reactions for fusion reactor systems. Keywords: Cross section; Artificial neural networks; Fusion structural material; EXFOR
1. Introduction The humanities needs have changed to cheap, clean and inexhaustible energy resources in the twenty-first century, and this quest brought the nuclear energy into the forefront. Using nuclear energy for fine intending aims began with nuclear reactors. Refurbished relevance of nuclear energy has led to developed new designs of new reactor systems on the basis of fusion technology which takes advantage of advances in nuclear technology. These future reactors plight that they improved security, reliability, sustainability and waste minimization. The structural material development is the first pitch to obtain an efficient source of energy in a nuclear reactor. The reactors structural materials would be crucial for the future success of fusion energy reactors, which will cause the structures to unprecedented fluxes of high-energy neutrons along. The advanced reactor materials can achieve improved reactor performance via increased safety margins and design flexibility beside in particular by providing increased strength, corrosion and neutron radiation damage resistance. In many cases, designing high-performance radiation-resistant materials is
based on the density of diffusing nanoscale particles that simultaneously provide good high-temperature strength and neutron radiation damage resistance [1]. High-performance structural materials will be critical for the future success of fusion energy reactors, which will lead the unprecedented fluxes of high-energy neutrons. These high-energy neutrons produced by the deuterium– tritium (D–T) fusion reaction are absorbed by especially combined and produced materials. In order to ensure the continuous operation of the fusion energy
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