Modelling unstable behavior of a natural circulation loop with a neural network

Natural circulation loops represent important elements of many technologically relevant systems. For this reason, their instability represents a major concern, as it consists of oscillations leading to flow reversal. The analysis of these processes was addressed in various theoretical works, mainly based on mathematical approaches to the problem. The models obtained in this way suffers a poor correspondence between simulated and experimental data. To solve this problem, the identification of the system was adopted in this paper, and a neural network model was obtained by means of input-output measurements detected on an experimental natural circulation loop. Moreover, the neural model was used in a predictive scheme, in order to allow long term prediction of the birth of unstable behaviors.