Computational Risk Assessment in the Nuclear Industry

Seminar Speaker: Dr. Curtis Smith, Director, Nuclear Safety and Regulatory Research Division, Idaho National Laboratory (INL)

Bio:

Dr. Curtis Smith is the Director for the INL Nuclear Safety and Regulatory Research Division. Prior to taking a leadership role as Division Director, he led several risk-informed activities including the Risk-Informed Systems Analysis (RISA) Pathway under the DOE Light Water Reactor Sustainability Program and the Nuclear Regulatory Commission’s SAPHIRE risk analysis software development.

Dr. Smith has been at INL for over 33 years and has published almost 300 papers, books, and reports on risk and reliability theory and applications. He holds a Ph.D. in nuclear engineering from MIT and a B.S. and M.S. in nuclear engineering from Idaho State University.

In 2023, Dr. Smith was awarded the INL Laboratory Director Award for Leadership.

Abstract: 

In the United States, research organizations are creating the next-generation reliability- and risk-assessment methods and tools that support risk-informed decision-making by combining physics-based models with probabilistic quantification approaches.  Integrating these two worlds of physics and probability using a simulation framework leads us to predictions based upon an approach called “computational risk assessment” which will serve as the technical basis for the future of reliability, risk, and safety approaches.  The driving factors for this new approach includes: temporal (timing issues), spatial (location issues), mechanistic (physics issues), and topological (complexity issues).  By combining phenomenology directly with stochastic quantification, we are able to perform advanced uncertainty analysis directly on both parameters and models. While these advanced methods and tools can provide increased realism in our engineering safety and risk approaches, their greater benefit is to provide our applications a risk-informed engineering framework for design and operation.  This talk will briefly review the history of risk assessment and risk-informed applications, describe some of the current research and development, and discuss potential future applications and approaches for advanced methods and tools.