Application of Kalman filtering technique for evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction
In this paper, for the first time, evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction is performed using experimental data available in IAEA-EXFOR database library and nuclear model-based data generated using Talys 1.9 code by applying a novel method of combining Kalman filterin...
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| Published in: | Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment Vol. 1020 |
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21.12.2021
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| ISSN: | 0168-9002, 1872-9576 |
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| Abstract | In this paper, for the first time, evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction is performed using experimental data available in IAEA-EXFOR database library and nuclear model-based data generated using Talys 1.9 code by applying a novel method of combining Kalman filtering technique with Machine Learning (ML) regression algorithms. The neutron cross section data evaluation has been performed after a detailed study of all the EXFOR papers corresponding to 100Mo (n, 2n) 99Mo reaction and nuclear model based cross section generation by executing T6 random input files using Talys 1.9 code. The evaluated curve generated is then compared with the existing evaluated curve of 100Mo (n, 2n) 99Mo reaction from nuclear data libraries such as ENDF/B-VIII.0, JEFF-3.3, JENDL-4.0, CENDL-3.1 and TENDL 2017 and found to be in good agreement with them. Chi-square and generalized Chi-square tests were employed to assess the proposed evaluation techniques and found them to be good in estimating evaluated mean values and evaluated uncertainties of cross section. |
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| AbstractList | In this paper, for the first time, evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction is performed using experimental data available in IAEA-EXFOR database library and nuclear model-based data generated using Talys 1.9 code by applying a novel method of combining Kalman filtering technique with Machine Learning (ML) regression algorithms. The neutron cross section data evaluation has been performed after a detailed study of all the EXFOR papers corresponding to 100Mo (n, 2n) 99Mo reaction and nuclear model based cross section generation by executing T6 random input files using Talys 1.9 code. The evaluated curve generated is then compared with the existing evaluated curve of 100Mo (n, 2n) 99Mo reaction from nuclear data libraries such as ENDF/B-VIII.0, JEFF-3.3, JENDL-4.0, CENDL-3.1 and TENDL 2017 and found to be in good agreement with them. Chi-square and generalized Chi-square tests were employed to assess the proposed evaluation techniques and found them to be good in estimating evaluated mean values and evaluated uncertainties of cross section. |
| ArticleNumber | 165850 |
| Author | Suryanarayana, Saraswatula Venkata Ram, Sangeetha Prasanna Ganesan, S. Nair, Jayalekshmi |
| Author_xml | – sequence: 1 givenname: Sangeetha Prasanna surname: Ram fullname: Ram, Sangeetha Prasanna email: sangeeta.prasannaram@ves.ac.in organization: V.E.S. Institute of Technology, Department of Instrumentation, Mumbai 400074, India – sequence: 2 givenname: Jayalekshmi orcidid: 0000-0002-7552-2159 surname: Nair fullname: Nair, Jayalekshmi organization: V.E.S. Institute of Technology, Department of Instrumentation, Mumbai 400074, India – sequence: 3 givenname: Saraswatula Venkata surname: Suryanarayana fullname: Suryanarayana, Saraswatula Venkata organization: Former Scientist, Nuclear Physics Division, Bhabha Atomic Research Centre, Mumbai 400085, India – sequence: 4 givenname: S. surname: Ganesan fullname: Ganesan, S. organization: Former Raja Ramanna Fellow, Reactor Design and Development Group, Reactor Physics Design Division, Bhabha Atomic Research Centre, Mumbai 400085, India |
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| Copyright | 2021 Elsevier B.V. |
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| DOI | 10.1016/j.nima.2021.165850 |
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| Title | Application of Kalman filtering technique for evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction |
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