Monitoring Used Nuclear Fuel Reprocessing Facilities through Data Analytics

American Institute of Chemical Engineers - Knoxville-Oak Ridge Section

K Town Tavern

AIChE Knoxville - Oak Ridge Section April 2021 Meeting – Joint with the Society of Women Engineers - Virtual Meeting &amp; In-Person MeetingDate: 	Thursday, April 15, 2021
Location:	K Town Tavern, 320 N Peters Rd, Knoxville, TN 37922



Attending the Zoom Meeting is Free. Please use Eventbrite to register.

5:00 pm	Executive Committee Meeting (All members welcome)
5:30 pm	Social/Networking
6:00 pm	Dinner - $20 for members and free for students (Pay by cash or check onsite, or in advance using Eventbrite. There is no charge for the program or PDH Certificate)
7:00 pm	Program - Dr. Jamie Baalis Coble, Nuclear Engineering Department at the University of Tennessee, Knoxville

Monitoring Used Nuclear Fuel Reprocessing Facilities through Data Analytics

Abstract - Reprocessing of used nuclear fuel (UNF) can address some concerns about long-term fuel storage; however, proliferation concerns currently limit the deployment and use of aqueous reprocessing in the US and abroad. Despite these concerns, aqueous approaches to separations and reprocessing (as opposed to electrochemical reprocessing) remain the most technically viable solution in the near-term. Traditional approaches to material control and accounting at reprocessing facilities rely in large part on laboratory-based destructive assay of samples; this analysis can be very accurate, but is costly and time-intensive. Online monitoring of operating facilities has been proposed as a complement to sampling-based accountancy to provide real-time indications of facility misuse.
The Multi-Isotope Process (MIP) Monitor is one approach to online facility monitoring that combines in-line gamma spectroscopy and multivariate analysis to provide real-time, autonomous process monitoring and diversion detection during facility operation. The MIP Monitor measures the spectra from gamma-emitting isotopes across multiple stages of the reprocessing system. These spectra are measured and evaluated in effectively-real time through multivariate analysis to detect and identify process anomalies that could be due to normal process disturbances, anomalous process control changes, or maleficence. This presentation will describe the MIP Monitor approach and present results of this method for detecting a simulated diversion at the H-Canyon reprocessing facility at Savannah River Site.

Speaker Biography – Dr. Jamie Baalis Coble is an Associate Professor, Assistant Department Head for Undergraduate Studies and Service, and Southern Company Faculty Fellow in the Nuclear Engineering department at the University of Tennessee, Knoxville.
Dr. Coble’s expertise is primarily in statistical data analysis, empirical modeling, and advanced pattern recognition for equipment condition assessment, process and system monitoring, anomaly detection and diagnosis, failure prognosis, and integrated decision making. Her research interests expand on past work in monitoring and prognostics to incorporate remaining useful life estimates into risk assessment, operations and maintenance planning, and optimal control algorithms. Prior to joining the UT faculty, she worked in the Applied Physics group at Pacific Northwest National Laboratory. Her work there focused primarily on data analysis and feature extraction for detecting anomalies and degradation in large passive components, advanced active components, and nuclear fuel reprocessing systems. Dr. Coble is currently pursuing research in prognostics and health management for active components and systems; advanced control strategies for new concepts of operation for nuclear reactors; and data-driven qualification of additively manufactured parts.

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Monitoring Used Nuclear Fuel Reprocessing Facilities through Data Analytics

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Monitoring Used Nuclear Fuel Reprocessing Facilities through Data Analytics

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