Feasibility Study oN Continuous Monitoring of Subcriticality by Noise Analysis Methods

Abstract

This paper presents the analysis results of Rossi-alpha, cross-correlation, and Feynman-alpha methods applied to the subcriticality monitoring of nuclear reactors. Two models are designed for the analysis of the three methods: a fast spectrum Godiva model and a thermal spectrum Godiva model. The fast spectrum Godiva geometry consists of a bare spherical core containing the isotopes of H-1, U-235 and U-238. The thermal spectrum Godiva model is a variation of the fast version, which additionally has an H2O reflector outside the core. A Monte Carlo code, McCARD, is used in real time mode to generate virtual detector signals to analyze the feasibility of the three methods. The analysis results indicate that the three methods can be used with high accuracy for the subcriticality monitoring of the virtual thermal reactor. In addition to that, in order to analyze the impact of the random noise contamination on the accuracy of the noise analyses, the McCARD-generated signals are contaminated with arbitrary noise by two difference cases. One is the average of random noise is one-fourth of that of the pure signals, which shows that the three methods can predict the subcriticality with reasonable accuracy. The other is the average of random noise is same with that of the pure signals, which indicates that the accuracy of the three methods degrades significantly, and further study is needed.