Tetsuo Tamaoki

Simulation of fast breeder reactor noise based on two-channel core model

Abstract A reactor noise simulator of fast breeder reactor (FBR) was developed for use in the development and testing of early fault detection and diagnostic methods based on noise analysis. The simulator was realized on a simple analog computer, and the simulation model covers the dynamics of reactor core and two control systems. The model in the core simulates two different fuel-channel behaviors; one is a typical channel that represents all normal channels, and the other is a test channel that represents all abnormal channels. This two-channel core model is one of the characteristic features of the technique, and it enables simulation of local core faults. Another feature is that the noise characteristics are quite similar to those of the experimental FBR “JOYO” Mark-I. In this paper we presented the reactor dynamic models and proposed a means of deriving noise source models which resemble actual reactor noise. Several examples are shown which demonstrate how this simulator can be used to model various kinds of anomalies in FBR plants.

On-Line Diagnostic Method with Automated Noise-Signature Learning

In this paper, an advanced diagnostic method is proposed that uses automated pattern recognition for reactor noise. The method enables intensive diagnosis of known anomalies and extensive detection of unknown plant states. It also enables automatic learning of reference noise patterns for an unknown plant state and monitoring of the subsequent state change by regarding the new reference patterns as those for a known plant state. Application results for the method used on artificial noise data produced by a fast breeder reactor noise simulator are presented.

Investigation of failed fuel detection and location using a flux tilting method in a fast breeder reactor

Detection and location of failed fuel in a liquid-metal fast breeder reactor (LMFBR) are very important both for safety and availability. When a fuel failure is detected, it is desirable to identify the failed subassembly quickly to reduce plant shutdown time. The flux tilting method is expected to effectively identify the defective subassembly. The feasibility of the flux tilting method is investigated for an LMFBR with a 100-MW (electric) homogeneous core. A numerical simulation is performed to estimate the viability of the flux tilting method, and a combination of the flux tilting method and the sipping method is found to be very effective in identifying the failed subassembly. In this paper a functional scheme for a computer-aided failed fuel detection and location system is discussed as part of a future on-line support system.