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Probability Quantification (PQ) predictions of the efficacy ofsafety-critical protective systems is challenging. Yet, the popularity of PQmethodologies (e.g., Probabilistic Risk Assessment (PRA), Quantitative RiskAnalysis (QRA) and Probabilistic Safety Analysis (PSA)) is growing and can nowbe found written into regulatory rules. PQ in predictive modeling is attractivebecause of its grounding in probability theory. But, certain important safetyrelated events are not probability-measurable which is problematic forrisk-analytic methodologies that rely on PQ computations. Herein, we identifywhy the dynamics of available information play an essential role in governingthe fidelity of PQ, and why PQ in the analysis of safety-critical protectivesystems is limited by the un-measurability of certain critical events. Weprovide an historical example that provides a practical context for ourobservations. Finally we discuss the implications of measurability forregulatory decision-making governed by recent nuclear industry legislationadvocating increased use of risk informed, performance-based regulation foradvanced reactor licensing.

A Note on Probability Quantification for Protective System Efficacy  Analysis: Stochastic Dynamics, Information Flow, and Initiating Event Arrival  Times