Published April 2004 | Version v1
Journal article Metadata-only

A Neural Network Model for the Tomographic Analysis of Irradiated Nuclear Fuel Rods

Creators

  • 1. National Institute of Nuclear Physics and Engineering (Romania)

Description

A tomographic method based on a multilayer feed-forward artificial neural network is proposed for the reconstruction of gamma-radioactive fission product distribution in irradiated nuclear fuel rods. The quality of the method is investigated as compared to a conventional technique on experimental results concerning a Canada deuterium uranium reactor (CANDU)-type fuel rod irradiated in a TRIGA reactor

Additional details

Identifiers

URL
http://epubs.ans.org/;

Publishing Information

Journal Title
Nuclear Technology
Journal Volume
146
Journal Issue
1
Journal Page Range
p. 65-71
ISSN
0029-5450
CODEN
NUTYBB

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
38011686
Subject category
S21: SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS;
Descriptors DEI
CANDU TYPE REACTORS; FISSION PRODUCTS; FUEL RODS; IRRADIATION; NEURAL NETWORKS; NUCLEAR FUELS; URANIUM
Descriptors DEC
ACTINIDES; ELEMENTS; ENERGY SOURCES; FUEL ELEMENTS; FUELS; HEAVY WATER MODERATED REACTORS; ISOTOPES; MATERIALS; METALS; POWER REACTORS; PRESSURE TUBE REACTORS; RADIOACTIVE MATERIALS; REACTOR COMPONENTS; REACTOR MATERIALS; REACTORS; THERMAL REACTORS

Optional Information

Copyright
Copyright (c) 2006 American Nuclear Society (ANS), United States, All rights reserved. http://epubs.ans.org/