@article{ref1,
title="A practical approach for evaluating the strength of knowledge supporting risk assessment models",
journal="Safety science",
year="2020",
author="Bani-Mustafa, Tasneem and Zeng, Zhiguo and Zio, Enrico and Vasseur, Dominique",
volume="124",
number="",
pages="e104596-e104596",
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 &quot;leaf&quot; 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 &quot;leaf&quot; 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.<p /> <p>Language: en</p>",
language="en",
issn="0925-7535",
doi="10.1016/j.ssci.2019.104596",
url="http://dx.doi.org/10.1016/j.ssci.2019.104596"
}