An integrated enterprise risk management framework for the estimation of safety risk and financial outcomes for nuclear power plants

Beal, Johnathan

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https://hdl.handle.net/2142/121281 Copy

Description

Title

An integrated enterprise risk management framework for the estimation of safety risk and financial outcomes for nuclear power plants

Author(s)

Beal, Johnathan

Issue Date

2023-07-21

Director of Research (if dissertation) or Advisor (if thesis)

Mohaghegh, Zahra

Committee Member(s)

Sakurahara, Tatsuya

Department of Study

Nuclear, Plasma, & Rad Engr

Discipline

Nuclear, Plasma, Radiolgc Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Probabilistic Risk Assessment
• Maintenance Modeling
• Nuclear Engineering
• Enterprise Risk Management
• Human Reliability Analysis

Abstract

Increased competition and fluctuations in the commercial electric sales market require a renewed focus on cost-saving initiatives to maintain the commercial viability of the Light Water Reactor energy sector. This research theorizes and quantifies the interconnections of safety and financial performance of nuclear power plants (NPPs). In this research, NPP safety refers to system safety, while financial performance refers to the monetary values associated with operation and maintenance (O&M) strategies. Review of the related studies has indicated that a model-based approach is necessary to explicitly analyze the interconnections of safety and financial performance and their underlying factors. This research develops an Integrated Enterprise Risk Management (I-ERM) methodological framework to create a model-based approach for the estimation of the safety and financial performance metrics. The I-ERM methodological framework includes constituting modules that model physical degradation mechanisms and their underlying causal factors, and couple them with maintenance performance models (considering human and organizational influencing factors) in a unified platform. The development of the I-ERM framework requires methodological generation for each of the individual modules, as well as the integration among these modules, including interfaces between models of different nature (e.g., physics-based models, maintenance-based models, component-level models, system-level models). One of the key considerations in these interfaces is how to synchronize multiple modules that have different time scales, and this research establishes a mathematical approach to address the different time scales among individual modules. This research develops a maintenance causal model for maintenance program quality in NPPs to support explicit incorporation of maintenance performance into I-ERM. The development of an explicit maintenance model and its coupling with physics-of-failure models in the I-ERM unified platform adds realism to modeling the influence of maintenance performance on safety and financial outcomes and enables the explicit consideration of the interconnections and dependencies between safety and financial performance. Two case studies are conducted in this research to demonstrate the applicability and value of the I-ERM methodological framework. In the first case study, a hypothetical NPP production and protection system case demonstrates the integration of the explicit maintenance performance model with the safety risk and financial outcomes of plant O&M. In the second case study analysis, a real-world NPP piping case study is used to analyze reliability of a piping component subject to both maintenance and physical degradation due to thermal fatigue. The value of I-ERM platform is that more in-depth causality for physical degradation phenomena (e.g., Stress Corrosion Cracking; SCC) and social contributing factors (e.g., human, organizational, and regulatory performance), associated with the Operations and Maintenance (O&M) of a plant, is incorporated into an integrated assessment of safety risk and financial risk. I-ERM aids NPP decision-making by providing a higher resolution model to identify cost-saving O&M strategies that satisfy safety requirements.

Graduation Semester

2023-08

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/121281

Copyright and License Information

Copyright 2023 Johnathan Beal

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