Mihai A. Diaconeasa
Assistant Professor of Nuclear Engineering
- Burlington Laboratory 1110D
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Dr. Mihai Diaconeasa obtained his B.S. degree from University College Utrecht, the international undergraduate honors college of Utrecht University, the Netherlands, his M.S. in Nuclear Science and Engineering from Massachusetts Institute of Technology (MIT), and Ph.D. in Mechanical Engineering from University of California, Los Angeles (UCLA). After his graduation, Dr. Diaconeasa held the postdoctoral research scholar position at the B. John Garrick Institute for the Risk Sciences from the School of Engineering at UCLA.
Over the past years, Dr. Diaconeasa has developed the methodologies needed to design and implement a suite of computer codes in the probabilistic risk, reliability, and resilience assessment (PRA) fields for nuclear, aerospace, and maritime industries. He served as the associate general chair for the International Conference on Probabilistic Safety Assessment and Management (PSAM-14) hosted by UCLA in 2018 and as the Track Chair/Co-Chair of the American Society of Mechanical Engineers (ASME) Design, Reliability, Safety, and Risk at the International Mechanical Engineering Congress and Exposition (IMECE) since 2020.
Currently, Dr. Diaconeasa is the 3rd Vice Chair of the American Society of Mechanical Engineers (ASME) Safety Engineering and Risk Analysis Division (SERAD) Executive Committee, the Acting Secretary/Treasurer of the American Nuclear Society (ANS) Nuclear Installations Safety Division (NISD) Executive Committee and the Vice-Chair of the ANS Advanced Reactor Working Group (ARWG). Also, he serves as a member of the ANS Standards Committee ANS-30.1 and ANS-30.2 Working Groups under the Research and Advanced Reactors Consensus Committee and is the Working Group Chair of the “Probabilistic Design Methods” Subcommittee, “Plant Systems Design” ASME Standards Committee.
Dr. Diaconeasa leads the design and development of ADS-IDAC, a dynamic probabilistic risk assessment (PRA) methodology and software platform for nuclear power plants and is the co-founder of the OpenPRA Initiative dedicated to designing and developing a wide range of traditional probabilistic risk assessment (PRA) methods and open source software. He has led the development of the Hybrid Causal Logic Analyzer system risk and reliability software used to enhance the design process and assess the commercial off-the-shelf (COTS) parts usage in space systems for extended deep space missions at NASA’s Jet Propulsion Laboratory (JPL) and the Phoenix human reliability analysis (HRA) methodology and software adopted by the Japan’s Nuclear Regulation Authority (JNRA).
University of California, Los Angeles
Nuclear Science and Engineering
Massachusetts Institute of Technology
University College Utrecht, Utrecht University
Dr. Diaconeasa's research focus includes theories, applications, and simulation-based techniques in risk sciences such as traditional and dynamic probabilistic risk assessment, reliability analysis, resilient systems design, probabilistic physics of failure modeling, and Bayesian inference.
- An Open Source, Parallel, and Distributed Web-Based Probabilistic Risk Assessment Platform to Support Real Time Nuclear Power Plant Risk-Informed Operational Decisions
- US Dept. of Energy (DOE)(10/01/21 - 9/30/24)
- Simulation-based reliability methodology development for autonomous controls and adversarial human actions involved in fission battery designs
- US Dept. of Energy (DOE)(12/10/20 - 9/30/22)
- A Quantitative Approach to Assessing Drugs Supply Chain Disruptions Leading to Shortages
- US Food & Drug Administration(9/28/20 - 3/27/22)