K. Kavaklioiglu et Br. Upadhyaya, MONITORING FEEDWATER FLOW-RATE AND COMPONENT THERMAL PERFORMANCE OF PRESSURIZED-WATER REACTORS BY MEANS OF ARTIFICIAL NEURAL NETWORKS, Nuclear technology, 107(1), 1994, pp. 112-123
The fouling of venturi meters, used for steam generator feedwater flow
rate measurement in pressurized water reactors (PWRs), may result in
unnecessary plant power derating. On-line monitoring of these importan
t instrument channels and the thermal efficiencies of the balance-of-p
lant components are addressed. The steam generator feedwater flow rate
and thermal efficiencies of critical components in a PWR are estimate
d by means of artificial neural networks. The physics of these systems
and appropriate plant measurements are combined to establish robust n
eural network models for on-line prediction of feedwater flow rate and
thermal efficiency of feedwater heaters in PWRs. A statistical sensit
ivity analysis technique was developed to establish the performance of
this methodology.