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This report describes research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions.

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants