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

TL;DR

This paper examines the limitations of probability quantification in safety-critical protective systems, emphasizing the role of information dynamics and event measurability in risk assessment and regulatory decision-making.

Contribution

It highlights the importance of information flow in probability quantification and discusses the challenges posed by un-measurable safety events in risk analysis.

Findings

Probability quantification is limited by un-measurable critical events.

Information dynamics significantly influence PQ fidelity.

Implications for nuclear safety regulation and risk-informed decision-making.

Abstract

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.