ABSTRACT

Safe, reliable, affordable energy is intricately connected to broad advances in health, science, prosperity, and our national defense. Engineering risk assessment is an essential tool used in designing the regulations, codes, and standards that enhance energy system safety and resilience without imposing unreasonable regulatory burden. Advancing the science behind risk-informed regulation is essential as systems become more complex and new challenges emerge. This Faculty Early Career Development (CAREER) project investigates how principles from two domains of reliability engineering can be systematically integrated to advance this science. This research that Probabilistic Risk Assessment (PRA) and Prognostics and Health Management (PHM) have complementary characteristics that can offset their individual weaknesses. The research will establish and validate a conceptual framework along with mathematical and computational methods to systematically integrate PRA and PHM methods, data, and models. Direct engagement with interdisciplinary stakeholders from nuclear power plant and hydrogen transportation infrastructure applications will facilitate both validation and adoption of the new methods. The results will provide new knowledge about the range of data and models that can be used in regulatory design and decision making. Integrated educational initiatives include design of the first public museum exhibit on energy system risk assessment, enhanced reliability engineering coursework, and diversity and inclusion initiatives for women and underrepresented minorities in engineering.

The overarching goal of this project is to establish a strong foundation of integrated research and educational activities centered on energy system risk assessment. The research focuses on transforming risk-informed regulation for energy systems through systematic integration of concepts, data and methods drawn from PRA and PHM and rigorous validation using both energy system case studies and expert stakeholder engagement. The educational activities enhance K-12 and public education through a new museum exhibit on energy system risk assessment that will be displayed in the nation?s only nuclear history and science museum and that will also be made available to a broad network of affiliated museums. Graduate coursework in reliability engineering will be enhanced through development of new active learning exercises based on this research. The research draws upon engineering techniques of PRA, which provides a comprehensive quantitative approach for synthesizing data, scenarios, and probability models to assess risk under uncertainty for complex engineering systems; and PHM, which provides powerful algorithms for using sensor data and failure models to understand and predict health of components. To date, there has been little work at the intersection of PRA and PHM. Unlike previous approaches which seek to make PRA more dynamic or to extend PHM to more complicated components within their current architectures, this research seeks to deconstruct PRA and PHM and engineer a new approach which leverages the benefits of both approaches. The research starts by defining the conceptual framework and then defining mathematical and computational structures. The candidate structures will be compared and validated using energy system case studies and stakeholder-based validation. Nuclear power plants and hydrogen fueling stations are used as testbeds to ensure that the results are generalizable beyond a single energy system or regulatory process. The research has broader societal impact by creating new knowledge and methods that will impact the design of regulations for nuclear power plants, hydrogen infrastructure, pipelines, and other energy systems and critical infrastructures. The integrated educational activities broaden K-12, graduate student, and public understanding of the science behind energy system safety. Broader participation of women and underrepresented minorities in engineering will be encouraged via the enhancement of graduate student recruitment and mentoring activities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Please report errors in award information by writing to: awardsearch@nsf.gov.