Boundary dependent physics-informed neural network for solving neutron transport equation
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Publisher
Elsevier BV
Subject
Nuclear Energy and Engineering
Reference42 articles.
1. Nodal synthetic kernel (N-SKN) method for solving neutron transport equation in one-and two-dimensional X-Y geometries;Altac;Ann. Nucl. Energy,2014
2. Using deep learning to explore local physical similarity for global-scale bridging in thermal-hydraulic simulation;Bao;Ann. Nucl. Energy,2020
3. Improving the one-dimensional interfacial area transport equation using a physics-informed machine learning method;Dang;Int. J. Heat Mass Transf.,2023
4. Solutions of Chandrasekhar’s basic problem in radiative transfer via theory of functional connections;De Florio;J. Quant. Spectrosc. Radiat. Transf.,2021
5. Physics-Informed Neural Network Method and Application to Nuclear Reactor Calculations: A Pilot Study;Elhareef;Nucl. Sci. Eng.,2022
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