Axial Shape Index Calculation for the 3-Level Excore Detector

A new method based on the alternating conditional expectation (ACE) algorithm is developed to calculate axial shape index (ASI) for the 3-level excore detector. The ACE algorithm, a type of non-parametric regression algorithms, yields an optimal relationship between a dependent variable and multiple independent variables. In this study, the simple correlation between ASI and excore detector signals is developed using the Younggwang nuclear power plant unit 3 (YGN-3) data without any preprocessing on the relationships between independent variables and dependent variable. The numerical results show that simple correlations exist between the three excore signals and ASI of the core. The accuracy of the new method is much better than those of the current CPC and COLSS algorithms.