Development of Core Monitoring System for a Nuclear Power Plant using Artificial Neural Network Technique

•Core Monitoring System (CMS) for estimation of core safety parameters for Chasnupp-1.•CMS development – design based on Artificial Neural Network Technique (ANNT).•ANNT training using In-core flux measured data of previous five C-1 fuel cycles.•Real time verification and validation of CMS during fuel cycle-11 of C-1.•CMS operating features, advantages and qualification. Core Monitoring System (CMS) has been developed to estimate Power Peaking Factors and other reactor physics safety parameters in normal power mode for core surveillance of Chashma Nuclear Power Plant Unit-1 (C-1). The CMS is based on the combination of Artificial Neural Network Technique (ANNT) and INCOPW processing code. The CMS methodology utilizes four inputs i.e. Power level, T4 control bank position, Effective Full Power Days (EFPDs) and individual burnup of 30 Fuel Assemblies. Seventy reactor operation states with different power density distributions are selected from five fuel cycles of C-1 for ANNT training. The CMS takes input parameters in real time and calculates output parameters. The CMS has been validated online at C-1 during cycle-11. The results indicate that CMS can be used for real time core monitoring of Chashma reactors. It would be beneficial for Chashma reactors to increase time interval between in-core flux maps from 30 to 90 EFPDs.