It is very important to monitor and predict departure from nucleate boiling ratio (DNBR) to prevent the fuel cladding melting and the boiling crisis. In this work, the DNBR is predicted by fuzzy neural networks using lots of measured signals of the reactor coolant system. The fuzzy neural networks are trained using a training data set and are verified with another test data set. The fuzzy neural networks are applied to the first cycle of the Yonggwang three nuclear power plant. The estimation accuracy of the …
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