Title:

Prognostic Health Management for Optimizing Operations and Maintenance

Speaker:

Dr. Pradeep Ramuhalli

Affiliation:

Distinguished R&D Staff Member and the group lead for the Modern Nuclear Instrumentation and Control (I&C) group at Oak Ridge National Laboratory (ORNL) in the Nuclear Energy and Fuel Cycle Division.

When:

Thursday, April 7, 2022 at 11:00:00 AM   Add to Calendar

Where:

Boggs Building, Room 3-47

Host:

Fan Zhang
dbrown360@gatech.edu
4043855502

Abstract

Instrumentation and control (I&C) technologies are expected to be vital to achieving improvements in operations and maintenance (O&M) practices to reduce the overall economics of nuclear power. Broadly defined to include sensing, data analysis, control, and decision making, I&C technologies can drive digital innovation in the nuclear energy infrastructure through the deployment of large-scale sensor networks for monitoring power plant operations. The resulting measurement capabilities can serve to automate several routine functions that are currently performed manually, resulting in cost-effective operation. At the same time, the deployment of continuous monitoring technologies can enable the detection and prediction of degradation in critical components, providing an opportunity for maintaining long-term, reliable, cost-effective operations using predictive O&M actions. This presentation will discuss approaches to component and asset health monitoring, with the objective of enabling predictive operations and maintenance actions. Research challenges and potential solutions will be discussed, along with a framework for operations and maintenance decision-making, for supporting digitalization of the nuclear energy infrastructure.

Biography

Dr. Pradeep Ramuhalli is a Distinguished R&D Staff Member and the group lead for the Modern Nuclear Instrumentation and Control (I&C) group at Oak Ridge National Laboratory (ORNL) in the Nuclear Energy and Fuel Cycle Division. He was previously at Pacific Northwest National Laboratory and before that was on a faculty member at Michigan State University. Dr. Ramuhalli’s research is in systems resilience and reliability, and is at the intersection of sensing, data science and decision science. His current research is focused on developing sensors and algorithms for continuous online monitoring and diagnosis of system health; and physics-informed machine learning algorithms for virtual sensing and prognostic assessment of system and component health. He has authored or co-authored 4 book chapters, over 175 technical publications in peer-reviewed journals and conferences, over 90 technical research reports, and has given over 100 invited talks. Dr. Ramuhalli is a senior member of IEEE and a member of ANS.

Notes

https://bluejeans.com/433668448/1395