Use of neural networks for modelling the steam generator of a nuclear power plant

This paper describes the development of an artificial neural network which models the dynamic behaviour of the boiler level in the steam generator of a nuclear power plant. Evaluation and validation of the model are performed by predicting boiler level using different sets of actual plant data. The neural network model is shown to be capable of providing accurate predictions of boiler level, and therefore has potential for real-time applications.<>