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INL researchers use LEDs to shed light on next-gen reactors
At Idaho National Laboratory, researchers have built a bridge between computer models and the lab’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor.
Tony Crawford, an INL researcher and MARVEL’s reactivity control system lead, designed a phone booth–sized surrogate nuclear reactor called ViBRANT, or Visual Benign Reactor as Analog for Nuclear Testing, which uses light instead of neutrons to show a “nuclear” reaction.
Ark O. Ifeanyi, Daniel Dos Santos, Abhinav Saxena, Jamie Coble
Nuclear Technology | Volume 210 | Number 12 | December 2024 | Pages 2387-2403
Research Article | doi.org/10.1080/00295450.2024.2323260
Articles are hosted by Taylor and Francis Online.
Control rods and elements manage the power distribution in nuclear reactors through the motion of banks of rods distributed throughout the core. These positional changes are achieved through the actuation of fine motion control rod drive (FMCRD) mechanisms. In the BWRX-300 design by GE-Hitachi, this mechanism is electrically driven by a servomotor that allows for high-precision control of power outputs. Under operational transients, such as load-following, accurate and precise operation of these servomotors is necessary over long periods of time, so they are key maintenance targets to maintain availability and operational flexibility. Swiftly and precisely identifying faults in the drive mechanisms will support predictive maintenance and reduced costs. This paper used three different types of simulated faults to test the fault detectability of principal component analysis (PCA) when considering the simulated operations of banks of control rods and their associated servomotors. These faults were stator short-circuit faults, ball screw jam faults, and ball screw wear faults. Torque and position were monitored in the simulation. The position signal was insufficient to detect mechanical faults. Torque signals for each servomotor in the bank of rods undergoing multiple position demand changes were projected to a reduced dimensional space via PCA. Q and T2 statistics were employed for anomaly detection. Using this approach, all faults were detected, and the anomalies were isolated to the faulty FMCRD mechanism.