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.

A practical approach for evaluating the strength of knowledge supporting risk assessment models

Zeng Z.;Zio E.;
2020-01-01

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.
2020
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)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0925753519322076-main.pdf

Accesso riservato

: Publisher’s version
Dimensione 3.62 MB
Formato Adobe PDF
3.62 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1160173
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact