Multilayer perceptron neural network applied to the neutron transport equation for the single velocity neurocomputational approach to neutronic calculations
DOI:
https://doi.org/10.15392/2319-0612.2024.2541Keywords:
Neurocomputational Methods, Neutron Transport Equation, Physical Analysis, Reactor AnalysisAbstract
The performance of neutronic calculations is a fundamental process for the analysis and design of nuclear reactors. However, due to the intrinsic complexity of these calculations, their solution is nearly impossible, whether through analytical or numerical methods. This work, through the application of a four-layer multilayer perceptron artificial neural network to the neutron transport equation, demonstrates the benefits of using neural computing for electronic calculations.
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Duderstadt JJ, Hamilton LJ. Análise de Reatores Nucleares. 2nd ed. Rio de Janeiro: LTC; 2005.
Bishop CM. Neural networks and their applications. Revista de Instrumentos Científicos. 65(6):1180-1183. 1994. DOI: https://doi.org/10.1063/1.1144830
Honghang Chi, Yahui Wang, Yu Ma. Reduced-order with least square-finite difference method for neutron transport equation. Annals of Nuclear Energy. 191:109914. 2023 DOI: https://doi.org/10.1016/j.anucene.2023.109914
Thulliez L. TOUCANS: A versatile Monte Carlo neutron transport code based on GEANT4. Nuclear Instruments and Methods in Physics Research, Section A. 1051:168-190. 2023. DOI: https://doi.org/10.1016/j.nima.2023.168190
UM-Dearborn. AIS's mysterious "black box" problem explained. [Internet]. Available from: https://umdearborn.edu/news/ais-mysterious-black-box-problem-explained.[cited 2023 Jul 26]
Govers, K., & Verwerft, M. (2017). Experimental data for neutron transport & depletion code validation. In SCALE User Group Meeting, September 26–28, 2017 (pp. 1-27). SCK•CEN. Disponível em: https://www.ornl.gov/sites/default/files/12_Kevin_Govers.pdf
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