Published June 2013
| Version v1
Journal article
Cross section expression based on neural network algorithm
Creators
- 1. National Key Discipline Laboratory of Nuclear Safety and Simulation Technology, Harbin Engineering University, Harbin (China)
- 2. Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing (China)
Description
In order to obtain the cross sections in different operating conditions affected by the thermal parameters and depletion, the neural network algorithm was used for function approximation. Bayesian normalization function and the early termination method were used to train sample cross section. Further more, this method was tested by the two examples. By comparing with FITLINK, the results show that cross section expression based on neural network algorithm is feasible. (authors)
Additional details
Publishing Information
- Journal Title
- Atomic Energy Science and Technology
- Journal Volume
- 47
- Journal Issue
- suppl
- Journal Page Range
- p. 207-210
- ISSN
- 1000-6931
INIS
- Country of Publication
- China
- Country of Input or Organization
- China
- INIS RN
- 48068987
- Subject category
- S22: GENERAL STUDIES OF NUCLEAR REACTORS;
- Descriptors DEI
- ALGORITHMS; COMPARATIVE EVALUATIONS; CROSS SECTIONS; F CODES; FUEL ASSEMBLIES; NEURAL NETWORKS; REACTOR CORES
- Descriptors DEC
- COMPUTER CODES; EVALUATION; MATHEMATICAL LOGIC; REACTOR COMPONENTS
Optional Information
- Notes
- 2 figs., 3 tabs., 5 refs.