Izvestia Vysshikh Uchebnykh Zawedeniy. Yadernaya Energetika

The peer-reviewed scientific and technology journal. ISSN: 0204-3327

Comparison of spallation reaction models using MCDA

6/22/2018 2018 - #02 Physics in nuclear power engineering

Andrianov A.A. Korovin Yu.A. Kuptsov I.S. Konobeev A.Yu. Andrianova O.N.

DOI: https://doi.org/10.26583/npe.2018.2.15

UDC: 539.172.128.17

The paper presents an approach to a comparative evaluation of the predictive ability of spallation reaction models based on widely used, well-proven multiple-criteria decision analysis methods (MAVT/MAUT, AHP, TOPSIS, PROMETHEE) and the results of such a comparison for 17 spallation reaction models in the presence of the interaction of high-energy protons with natPb. A multi-criteria approach to a comparative evaluation of high-energy nuclear reaction models as well as evaluated nuclear data obtained by using these models makes it possible to more finely differentiate various models with due account for experts’ opinions, which makes an additional contribution to both the understanding of nuclear reaction mechanisms and preparation of a reliable nuclear data set. The best models can be considered those of the first group including: CEM02, CEM03, Phits/jam, Cascade/ASF, Phits/Bertini. The models Bertini/Dresner, Cascade-4, INCL4/ABLA, INCL4/SMM, geant4/binary, Isabela/SMM, geant4/Bertini may be referred to the second in attractiveness group. The models Isabela/Abla, INCL4/ Gemini, CASCADeX-1.2, Isabel/Gemini, phits/jqmd, which are characterized with a greater uncertainty, may be united into the next in attractiveness group. The study has shown that if the MCDA methods are applied to evaluating the predictive ability of spallation reaction models, despite some differences in model ranking, the results obtained by using different methods turn out to give good fits. The study demonstrates that taking into account the sensitivity analysis results, an additional alternative analysis using experts’ judgments and the whole set of geographical and attributive information, it becomes possible to select the best models.


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spallation nuclear reactions nuclear data multi-criteria analysis uncertainty