2022/03/08 by Martin Wortman, Wortman, Martin, Ernest Kee +3
Decision Sciences · Engineering · #91G70 #FOS: Electrical engineering #Nuclear Engineering Thermal-Hydraulics #Probabilistic and Robust Engineering Design #Risk and Safety Analysis #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2203.04315
openalex publication_date 2022/03/08 · openalex created_date 2022/04/03 · openalex updated_date 2026/07/28
Probability Quantification (PQ) predictions of the efficacy of safety-critical protective systems is challenging. Yet, the popularity of PQ methodologies (e.g., Probabilistic Risk Assessment (PRA), Quantitative Risk Analysis (QRA) and Probabilistic Safety Analysis (PSA)) is growing and can now be found written into regulatory rules. PQ in predictive modeling is attractive because of its grounding in probability theory. But, certain important safety related events are not probability-measurable which is problematic for risk-analytic methodologies that rely on PQ computations. Herein, we identify why the dynamics of available information play an essential role in governing the fidelity of PQ, and why PQ in the analysis of safety-critical protective systems is limited by the un-measurability of certain critical events. We provide an historical example that provides a practical context for our observations. Finally we discuss the implications of measurability for regulatory decision-making governed by recent nuclear industry legislation advocating increased use of risk informed, performance-based regulation for advanced reactor licensing.