NPRE 596 Graduate Seminar
Tuesday, December 11, 2018
2:00 - 4:00 pm - Annual Holiday Party - 220 Talbot Lab, Student Lounge
4:00 - 4:50 pm - Graduate Seminar - 103 Talbot Laboratory
Postdoctoral Research Associate
Department of Nuclear, Plasma, and Radiological Engineering
University of Illinois at Urbana-Champaign
Integrated Probabilistic Risk Assessment (I-PRA) Methodology and Computational Platform for Fire PRA of Nuclear Power Plants
Abstract: In resolving emergent safety concerns of Nuclear Power Plants (NPPs), such as the ones created in the aftermath of the Fukushima-Daiichi accident, the existing classical Probabilistic Risk Assessments (PRAs) of NPPs were found to have limitations in generating the required realism for plant risk estimations. Socio-Technical Risk Analysis (SoTeRiA) Laboratory (http://soteria.npre.illinois.edu/) at University of Illinois Urbana-Champaign has developed an Integrated PRA (I-PRA) methodological framework that explicitly incorporates the underlying science of accident causation into plant risk scenarios and provides a feasible solution for adding realism to the plant risk estimations. I-PRA provides a unified, multi-level probabilistic integration, starting with the underlying physical and social failure mechanisms, connecting them to the component-level failures, and the system-level risk scenarios in the plant PRA model. While the I-PRA framework is applicable for various safety challenges of concern of NPPs, this presentation provides an overview of the I-PRA methodology and computational platform developed for assessing the plant risk induced by internal fires of NPPs. The Fire I-PRA framework integrates a Computational Fluid Dynamics (CFD)-based fire model with classical PRA through a probabilistic interface, equipped with advanced uncertainty quantification, dependency modeling, and Bayesian updating. In Fire I-PRA, the interactions between physics of fire progression and manual fire suppression are explicitly modeled based on the key timings associated with the fire brigade human performance. The Fire I-PRA has been applied to a realistic fire scenario at an NPP, showing that this new methodology reduces the core damage frequency estimate by 50% compared to the current Fire PRA methodology (NUREG/CR-6850). Improving the realism of PRA can provide NPPs with more design alternatives that can satisfy the risk acceptance criteria.
Bio: Tatsuya Sakurahara is a postdoctoral research associate in the SoTeRiA Laboratory, Department of Nuclear, Plasma, and Radiological Engineering (NPRE) at the University of Illinois Urbana-Champaign (UIUC). In May 2018, he earned his Ph.D. in nuclear engineering, under the supervision of Professor Zahra Mohaghegh, from NPRE. He has a master’s degree in nuclear engineering and management from the University of Tokyo, Japan. His Ph.D. research focused on developing an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework for Fire PRA of NPPs. For I-PRA, he also developed advanced techniques for importance measure analysis, simulation-informed common cause failure modeling, and the Probabilistic Validation methodology for uncertainty analysis. His current research includes: an integrated component reliability and availability analysis methodology (supported by the U.S. DOE NEUP Project, “Systematic Enterprise Risk Management by Integrating the RISMC Toolkit and Cost-Benefit Analysis”) and physics-based pipe failure rate prediction for advanced reactors (supported by the IAEA Coordinated Research Project “Methodology for Assessing Pipe Failure Rates in Advanced Water Cooled Reactors”). He is a recipient of the 2016-2017 Teaching Excellence Award from the Illinois Student Government for his TA work in NPRE 461 (Probabilistic Risk Assessment) and NPRE 498/598 (Advanced Risk Analysis).