A new approach to monitoring solvent extraction processes for the nuclear industry [version 1; peer review: 2 approved, 2 approved with reservations] - Jay D. Hix; Edna S. Cárdenas; Mitchell R. Greenhalgh; Luis A. Ocampo Giraldo; James T. Johnson; Cody M. Walker (Nuclear Science and Technology Open Research)
As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is building the Beartooth test bed. Beartooth will include a cascade of centrifugal contactors, glove box lines, and solidification and dissolution equipment to aid in the progression of novel separation techniques and to provide hands-on opportunities to early-career separation engineers. Beartooth will incorporate novel monitoring techniques using sensors and machine learning algorithms to inform process operators of separation conditions. This research is examining unconventional monitoring technologies such as incorporating acoustic microphones, vibration sensors, infrared cameras, red-green-blue color sensors, among others into nuclear separation processes. Research is ongoing in the use of machine learning methods to detect faults and alert operators of typical and anomalous events. Results from this research have the potential to impact safeguards-by-design efforts and real-time decision making. This overview will detail preliminary measurement results from acoustic, vibration, and color sensors.