Development of a multi-sensor data science system used for signature development on solvent extraction processes conducted within Beartooth facility

This project will develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, and light, and traditional sources such as flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. The goal is to characterize stages within a solvent extraction process can increase target metals recovery, indicate process faults, account for special nuclear material, and inform near real-time decision making.