Development of dynamic integrated consequence evaluation (DICE) for dynamic event tree approaches: Numerical validation for a loss of coolant accident
Sejin Baek and
Gyunyoung Heo
Reliability Engineering and System Safety, 2023, vol. 238, issue C
Abstract:
Although conventional probabilistic safety assessment (PSA) makes a sufficient contribution to evaluating the safety of nuclear facilities, it suffers some limitations in performing optimal assessments close to the actual behavior by reflecting time dependencies in accident management. However, integrated deterministic and probabilistic safety assessment (IDPSA) literally combines two methodologies to enable synchronized evaluation based on physical behavior, system availability of facilities, and operator's response. Dynamic integrated consequence evaluation (DICE) is one of the IDPSA tools developed for this purpose, which is the first achievement in South Korea and supported by a regulatory authority. Based on dynamic discrete event tree (DDET) methodology, DICE consists of a scheduler that supports the exchange of information between modules, including a physical module that computes thermal-hydraulic simulations, a diagnosis module that specifies branching points for safety systems, and a reliability module that provides system availability. This paper deals with numerical validation comparing the conventional deterministic and probabilistic results for a sample scenario with those of DICE, and discusses an application of DICE to support and extend the scope of conventional PSA through a case study. It is expected that DICE emphasizes the compliance with conventional PSA methodologies while providing magnified perception in investigating unforeseen scenarios.
Keywords: Integrated deterministic-probabilistic safety assessment (IDPSA); Dynamic integrated consequence evaluation (DICE); Dynamic discrete event tree (DDET) (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003393
DOI: 10.1016/j.ress.2023.109425
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