Citation

Bani-Mustafa T, Zeng Z, Zio E, Vasseur D. Safety Sci. 2020; 124: e104596.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.ssci.2019.104596

PMID

unavailable

Abstract

In this paper, we develop a new quantitative method to assess the Strength of Knowledge (SoK) of a risk assessment. A hierarchical framework is first developed to conceptually represent the SoK in terms of three attributes (assumptions, data, phenomenological understanding), which are further broken down in sub-attributes and "leaf" attributes to facilitate their assessment in practice. The hierarchical framework, is, then, quantified in a top-down, bottom-up fashion for assessing the SoK. In the top-down phase, a reduced-order risk model is constructed to limit the complexity and number of basic elements considered in the SoK assessment. In the bottom-up phase, the SoK of each basic element in the reduced-order risk model is assessed based on predefined scoring guidelines and, then, aggregated using a weighted average of "leaf" attributes, where the weights are determined based on the Analytical Hierarchical Process (AHP). The strength of knowledge of the basic events is in turn, aggregated using a weighted average to obtain the SoK for the whole risk assessment model. The developed methods are applied to a real-world case study, where the SoK of the Probabilistic Risk Assessment (PRA) models of a Nuclear Power Plants (NPP) is assessed for two hazards groups, i.e., external flooding and internal events.

Language: en

Keywords

Event Tree (ET); Multi-Hazards Risk Aggregation (MHRA); Nuclear Power Plant (NPP); Probabilistic Risk Assessment (PRA); Risk-Informed Decision Making (RIDM); Strength of Knowledge (SoK)