A Neural Network Model for the Tomographic Analysis of Irradiated Nuclear Fuel Rods
DOI: 10.13182/NT04-A3488
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摘要: 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 investigated as compared to conventional technique experimental results concerning Canada deuterium uranium reactor (CANDU)-type rod TRIGA reactor.
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