Abstract

Abstract The modern idea of risk-informed decision-making (RIDM) is here critically examined for all existing, advanced and, generation-IV nuclear reactor systems. Motivated by the predictive difficulties of probabilistic risk assessment (PRA) in regard to occurred accidents, it is evident that the real (not hypothetical) consequences of nuclear core damage accidents that must be considered and quantified are the financial losses, infrastructure damages, societal disruptions, and adverse political policies, and not solely the traditional exceedance of regulated radiation release or public exposure limits. With this perspective, a new dynamic analysis is presented for estimating the probability of core damage due to extended loss of power and cooling in a modern nuclear reactor, giving results different from current standardized PRA/PSA analyses. Using existing data, we approach the multitude of different events in a new way: whatever the initial event in the finite event set {external flood, fire, hurricane, ice storm, typhoon, earthquake, cyber attack…}, the fundamental concerns are the consequent loss and nonrestoration of power, and the inadequate cooling of the core. The present proposed quantitative evaluation uses applicable and fully “exchangeable” severe event data for nuclear and nonnuclear systems, including active and passive emergency back-up systems for a wide range of power losses that lead to widespread damage and societal disruption. While not design-specific, this new independent “order-of-magnitude” estimate for the probability of core damage is some two to two hundred times larger than that shown or reported in recent modern and formal PSA/PRA for licensing submissions using generic failure rate data rather than actual severe event data. This new finding suggests greater uncertainties exist than presently assumed for risk-informed decision-making (RIDM), and points to the need for a major reconsideration and updating of risk assessment and regulatory risk-informed approaches for nuclear plant safety evaluation.

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