Title:

Data-Driven Decision Making for Improved Economics of Nuclear Power

Speaker:

Dr. Jamie Coble

Affiliation:

Associate Professor at UTK

When:

Thursday, October 19, 2023 at 11:00:00 AM   Add to Calendar

Where:

Boggs Building, Room 3-47

Host:

Chris Wang
chris.wang@nre.gatech.edu

Abstract

Nuclear power plants are faced with a challenging economic reality that has led to the premature closure of many plants in the US fleet over the last several years. William Levis, President and Chief Operating Officer, PSEG Power, succinctly describes the current situation in the forward to NEI Delivering the Nuclear Promise Advancing Safety, Reliability and Economic Performance Nuclear energy is carbon-free and large-scale, and our industry has delivered on its promise to generate energy safely and reliably. Yet nuclear energy still is not economically competitive in many electricity markets. That is our industry most significant challenge and the one promise that we have yet to deliver. Controlling the day-to-day operations and maintenance (O and M) costs associated with nuclear power is one of the primary avenues for improving the economic outlook for the nuclear industry. The current approach to O&M relies primarily on license-based periodic inspection and maintenance activities scheduled to preclude in service degradation and failure; however, this approach often leads to unnecessary and costly activities. Current trends in the nuclear industry are moving away from purely time based inspection, maintenance, and replacement toward risk-informed practices, based in part on the greater situational awareness provided by online equipment condition assessment of key components. This seminar will overview research in online equipment condition assessment, fault detection and diagnostics, and failure prognostics for active equipment in nuclear power plants and methods to integrate this knowledge into robust decision making, including maintenance planning and integration with Digital Twins for O and M support.

Biography

Dr. Jamie Baalis Coble is an Associate Professor, Southern Company Faculty Fellow, and Assistant Department Head of Undergraduate Studies and Service in the Nuclear Engineering department at UTK. Dr. Coble 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 nuclear system monitoring and prognostics to incorporate system monitoring and remaining useful life estimates into risk assessment, operations and maintenance planning, optimal control algorithms, and digital twin simulations. Prior to joining the UT faculty, she worked in the Applied Physics group at Pacific Northwest National Laboratory. Dr. Coble is currently pursuing research in prognostics and health management for active components and systems, advanced control strategies for integration of small modular reactors and multi modular reactors with deep renewable penetration, methods to improve decision making in O and M of nuclear power facilities, and process monitoring and accountancy for safeguards of nuclear fuel cycle facilities.

Notes

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