Curtis Smith

Bio

Dr. Curtis Smith is the KEPCO Professor of the Practice of Nuclear Science and Engineering. Prior to joining MIT, he was the Director for the Idaho National Laboratory’s Nuclear Safety and Regulatory Research Division. While at INL, 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 published over 300 papers, books, and reports on risk and reliability theory and applications. He holds a PhD in nuclear engineering from MIT and a B.S. and M.S. in nuclear engineering from Idaho State University.

Recent Awards

• 2022 Idaho National Laboratory Director Leadership award (2022)
• Idaho State University's Professional Achievement Award from the College of Science and Engineering (2023)
• Awarded level of Fellow of the American Nuclear Society (2023)

Research

Risk and reliability methods, teaching, and tools development for applied engineering applications within the nuclear and aerospace industries. Risk-informed decision making, Bayesian analysis, simulation of complex systems, human reliability modeling, nuclear systems analysis, and aerospace risk analysis

Publications

1. IAEA, Design Basis Reconstitution for Long Term Operation of Nuclear Power Plants, IAEA-TECDOC-2018, February 2023.
2. Garga, V. , G. Vinod, M. Prasad, J. Chattopadhyay, C. Smith, V. Kant, “Human reliability analysis studies from simulator experiments using Bayesian inference,” Reliability Engineering and System Safety, Volume 229, January 2023.
3. Smith, C., R. Christian, K. Vedros, P. Finck, R. Iotti, ARC-100 Conceptual Design Phase Level 1 PSA Early Draft, INL/RPT-22-69566, October 2022.
4. Smith, C., K. Vedros, K. Martinez, and D. Kuipers, “A Risk-Informed Community Framework for the Assessment of Chemical Hazards,” Journal of Critical Infrastructure Policy, Spring/Summer 2022.
5. Smith, C., A. Al Rashdan, V. Agarwal, “Using the ‘New Math’: Artificial Intelligence and Machine Learning Applications for the Nuclear Power Industry,” Nuclear News, June 2022.
6. Smith, C., D. Mandelli, K. Le Blanc, “Risk-informed Methods and Applications” in Nuclear and Energy Engineering, Elsevier, ISBN 9780323911528, September 2022.
7. Smith, C., A. Miller, S. Hess, F. Ferrante, “Helping to Solve the Plant Safety Puzzle: An Overview of Probabilistic Risk Assessment,” Nuclear News, September 2021.
8. Zhang, S., Z. M, H. Zhang, C. Smith, “Multicriterion benefit evaluation methodology for safety enhancements in nuclear power plants and application for FLEX strategies,” Nuclear Engineering and Design, 376, 2021.
9. Smith, C., K. Shirvan, J. Christensen, K. Vedros, “Making Emergency Planning Zones Smarter: A risk-informed approach for new reactors,” Nuclear News, April 2021.
10. Mandelli, D., C. Wang, C. Parisi, D. Maljovec, A. Alfonsi, C. Smith, “Linking classical PRA models to dynamic PRA,” Annals of Nuclear Energy, Volume 149, December 2020.
11. Mandelli, D., A. Alfonsi, C. Wang, Z. Ma, C. Parisi, T. Aldemir, C. Smith, R. Youngblood, “Mutual Integration of Classical and Dynamic PRA,” Nuclear Technology, Volume 201, Issue 3, pp. 363-375, October 2020.
12. Ma, Z., C. Smith, N. Johnson, “Loss of Offsite Power Recovery Modeling in United States Nuclear Power Plants,” INSIGHT, Volume 23, Issue 2, June 2020.