Quantifying Reactor Power Noise - A Case Study on NIST Research Reactor

Published

May 26, 2023

Author(s)

Anil Gurgen, Dagistan Sahin, James R. Whipple

Abstract

Water cooled reactors experience reactivity changes when voids are present in the coolant. The fraction of coolant in the core diminutions in the event of boiling, and the reactivity feedback can either be positive due to reducing neutron absorption in the coolant or can be negative due to reduction in the slowing down of neutrons to thermal energy because of a reduced moderator to fuel ratio. Similarly, mechanical movement of core internals, specifically within the active core volume do cause power fluctuations. Nevertheless, coolant voiding, and mechanical movements are among the main perturbations that induce reactor power oscillations, which can also be defined as the reactor power noise. A real-time noise detection system can track the reactor power measurements, and alarm if the oscillations exceed statistically significant levels. This study presents a method for estimating the noise in reactor power measurements using a real-time signal-to-noise ratio calculation. The effectiveness of the proposed noise calculation methodology is demonstrated using data from the National Bureau of Standards Reactor (NBSR) under both normal operating conditions and fuel failure events. Additionally, this paper describes the detailed design of a noise detection system hardware based on this methodology.

Proceedings Title

Proceedings of the 2023 30th International Conference on Nuclear Engineering

Conference Dates

May 21-26, 2023

Conference Location

Kyoto, JP

Conference Title

30th International Conference on Nuclear Engineering

Pub Type

Conferences

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Keywords

Reactor power noise, noise quantification analysis, signal-to-noise ratio

Citation

Gurgen, A. , Sahin, D. and Whipple, J. (2023), Quantifying Reactor Power Noise - A Case Study on NIST Research Reactor, Proceedings of the 2023 30th International Conference on Nuclear Engineering, Kyoto, JP, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936089 (Accessed April 28, 2024)