Abstract
Once an event in a pressurized water reactor (PWR) occurs and the operator has identified it, the system may then be returned to safe operational status. Usually, monitoring the thermal state of the reactor, e.g., the temperature and pressure of the reactor cooling system (RCS), the operator can realize the margin to the safety limit and the progress of the event. A deterministic approach and a stochastic approach are developed in this study. In deterministic approach, the temperature difference between hot and cold legs is additionally adopted as the third parameters used for identification. And, the steam generator pressure is adopted as the forth parameter in stochastic approach.The event data are generated using the best estimated model RELAP5. In deterministic approach, since the variation ranges of system key parameters at a specific time duration represent the specific character of each initiating event, the identification procedure can easily determine the case by comparing the variation range of on-line data and the event data in data pool. In the stochastic approach, which accounts for measurement noise, the cumulative distribution function (CDF) is constructed and system parameters variables at the cumulative probability from 0.05 to 1.00, with 0.05 increments, are chosen for identification. The random value is added to the simulated data, and then a 95% confidence interval is obtained. To identify an event, eighty data points, i.e., twenty data points for each parameter and four parameters for each event, should match the stored data. Since the identification procedures are simple, the computation is very fast and the results show that the event can be properly identified. These two methods will be beneficial in the context of executing an emergency operating procedure more effectively.