Data Adequacy (DA) assessment of experimental databases must be performed to control the impact of user effects on the results provided by the Thermal-Hydraulic (T-H) codes employed for the safety assessment of Nuclear Power Plants (NPPs). The activity is typically based on expert judgement, which, however, lacks a rigorous treatment of the uncertainties. With the objective to overcome this limitation, we propose a Multi-Criteria Decision Making (MCDM) approach to consider the Representativeness (R) and Completeness (C) of the databases by an Analytic Hierarchy Process (AHP) combined with Interval Analysis (IA) and Monte Carlo Simulation (MCS) to quantify the uncertainty. The approach for DA is exemplified on the databases made available to the participants of the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the WGAMA of the OECD-NEA, whose ultimate objective is the systematic application of Inverse Uncertainty Quantification (IUQ) methodologies to assess the uncertainties affecting the T-H model of an Intermediate Break Loss Of Coolant Accident (IBLOCA) of a Light Water Reactor (LWR). The outcomes of the application show that the proposed approach allows overcoming some of the limitations of expert-based approaches, reducing the reliance on subjective evaluations through the incorporation of quantitative metrics in the analysis and via the proper quantification of the uncertainty.

Data Adequacy by an Extended Analytic Hierarchy Process for Inverse Uncertainty Quantification in Nuclear Safety Analysis

Di Maio F.;Zio E.
2024-01-01

Abstract

Data Adequacy (DA) assessment of experimental databases must be performed to control the impact of user effects on the results provided by the Thermal-Hydraulic (T-H) codes employed for the safety assessment of Nuclear Power Plants (NPPs). The activity is typically based on expert judgement, which, however, lacks a rigorous treatment of the uncertainties. With the objective to overcome this limitation, we propose a Multi-Criteria Decision Making (MCDM) approach to consider the Representativeness (R) and Completeness (C) of the databases by an Analytic Hierarchy Process (AHP) combined with Interval Analysis (IA) and Monte Carlo Simulation (MCS) to quantify the uncertainty. The approach for DA is exemplified on the databases made available to the participants of the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the WGAMA of the OECD-NEA, whose ultimate objective is the systematic application of Inverse Uncertainty Quantification (IUQ) methodologies to assess the uncertainties affecting the T-H model of an Intermediate Break Loss Of Coolant Accident (IBLOCA) of a Light Water Reactor (LWR). The outcomes of the application show that the proposed approach allows overcoming some of the limitations of expert-based approaches, reducing the reliance on subjective evaluations through the incorporation of quantitative metrics in the analysis and via the proper quantification of the uncertainty.
2024
Analytic Hierarchy Process (AHP)
Best Estimate Plus Uncertainty (BEPU)
Data Adequacy (DA)
Inverse Uncertainty Quantification (IUQ)
Monte Carlo Simulation (MCS)
Multi-Criteria Decision Making (MCDM)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1260603
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