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Estimation of Nuclear Reactor Vessel Water Level in Severe Accidents Using Cascaded Fuzzy Neural Networks

Authors:
Man Gyun Na
Dong Yeong Kim
Kwae Hwan Yoo
Geon Pil Choi

Keywords: Cascaded fuzzy neural network (CFNN), Fuzzy neural network (FNN), Nuclear reactor vessel water level

Abstract:
The world’s concern about nuclear reactor safety has increased considerably since the Fukushima accident. In case of most severe accidents, the nuclear reactor vessel water level cannot be measured. But, if the cascaded fuzzy neural network (CFNN) is used, under the event of severe accidents it might be possible to estimate the nuclear reactor vessel water level. The cascaded fuzzy neural network model can be used to estimate the nuclear reactor vessel water level value through the process of adding fuzzy neural networks (FNNs) repeatedly. The developed cascaded fuzzy neural network model is sufficiently accurate to be used to estimate the nuclear reactor vessel water level. Therefore, the developed cascaded fuzzy neural network model will be helpful for providing effective information for operators in severe accident situations.

Pages: 113 to 117

Copyright: Copyright (c) IARIA, 2015

Publication date: October 11, 2015

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-437-4

Location: St. Julians, Malta

Dates: from October 11, 2015 to October 16, 2015