ARMA models in the analysis of temperature noise measurements in a Super-Phenix subassembly mock-up

The noise analysis methods play an important role in the early, reliable detection of local cooling disturbances in a fast reactor subassembly such as sodium boiling or blockage, which are considered among the initiating events of major disruptive core accidents. In this paper we apply the Box and Jenkins auto-regressive moving-average ARMA models to the analysis of several temperature time-series measured by the Commissariat à l'Energie Atomique in the course of the CFNa experiment carried out at the nuclear center of Grenoble. The source of data is a thermocouple placed at the outlet of a Super-Phenix subassembly mock-up. The analysis shows that a simple ARMA (3,2) model adequately accounts for the observed fluctuations. This model provides methods for a continuous, in situ estimate of the thermocouple time constant, for the identification of a suitable boiling and blockage indicator and for the detection in real time of suddenly occurring disturbances.