Development of Advanced Core Noise Monitoring System for a Boiling Water Reactor

Abstract

For an efficient nuclear power plant operation, advanced core design is very important. However, advances in design may result in approaching unexplored areas where unforeseen events are increasingly common. The purpose of this paper is to describe a BWR core noise monitoring system for addressing core anomaly problems in future advanced core operation. To monitor in-core status from a limited number of signals, we introduce various new algorithms to compensate for a lack of information. We demonstrate that up-to-date signal processing technologies, such as independent component analysis, nonlinear principal component regression, factor analysis and neural network, are effective tools for core monitoring. Also, the combination of the first principle or design model and the empirical fitting model is applied to estimate unobserved in-core state variables. Several concrete examples, such as stability monitoring, reactivity coefficient estimation, core flow estimation and in-core signal validation, are shown based on long-term monitoring experiences in real BWR plants. Through these examples, we demonstrate that the core noise monitoring system is a general platform for providing a variety of monitoring tools to meet the requirements of an advanced core operation strategy.