Axial Power Distribution Calculation Using a Neural Network in the Nuclear Reactor Core

This paper is concerned with an algorithm based on neural networks to calculate the axial power distribution using excore defector signals in the nuclear reactor core. The fundamental basis of the algorithm is that the detector response can be fairly accurately estimated using computational codes. In other words, the training set, which represents relationship between detector signals and axial power distributions, for the neural network can be obtained through calculations instead of measurements. Application of the new method to the Yonggwang nuclear power plant unit 3 (YGN-3) shows that it is superior to the current algorithm in place.