Multilayer perceptron neural network applied to the neutron transport equation for the single velocity neurocomputational approach to neutronic calculations

Authors

  • Rennan Franco Institute for Energy and Nuclear Research - São Paulo, Brazil
    • Thadeu Conti Institute for Energy and Nuclear Research - São Paulo, Brazil
      • Savio Ferreira Institute for Energy and Nuclear Research - São Paulo, Brazil

        DOI:

        https://doi.org/10.15392/2319-0612.2024.2541

        Keywords:

        Neurocomputational Methods, Neutron Transport Equation, Physical Analysis, Reactor Analysis

        Abstract

        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.  

        Downloads

        Download data is not yet available.

        Author Biography

        • Rennan Franco, Institute for Energy and Nuclear Research - São Paulo, Brazil

          Institute for Energy and Nuclear Research, 05508-000, City, São Paulo, Brazil

        References

        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

        Downloads

        Published

        2024-12-13

        Issue

        Section

        Articles