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CANDU Station Blackout D-PSA with RAVEN and TRACE Software.

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Title: CANDU Station Blackout D-PSA with RAVEN and TRACE Software.
Authors: Vododokhov, Nikolai1 (AUTHOR) vododokn@mcmaster.ca, Erlandson, Kendall2 (AUTHOR), Novog, David R.1 (AUTHOR)
Source: Nuclear Science & Engineering. Sep2025, Vol. 199 Issue 9, p1492-1511. 20p.
Subjects: Nuclear energy, CANDU reactors, Computer software, Risk assessment, Emergency management, Electric power failures
Geographic Terms: Canada
Abstract: Nuclear energy provides a low-carbon source of electricity that provides consistent and reliable power in a cost-effective manner. However, the accident at Fukushima Daiichi in 2011 demonstrated several important lessons on nuclear power plant severe events and risk mitigation and led to important changes in designs, improvement in emergency planning, and better understanding of external event hazards. Since 2011, the Fukushima accident has also led to new methodologies to characterize risk for low-probability events such as station blackout (SBO). In particular, large external events that lead to loss of Class IV power, and subsequent failures of backup power (Class III power) and or emergency power, and where the outcome may be dependent on human/emergency response functions, require additional methodological development to better quantify the risks and consequences. Dynamic Probabilistic Safety Assessment (D-PSA) is a set of stochastic tools that allows the integration of technology availability (e.g. as in standard Probabilistic Safety Assessment), human action probability, uncertainty in predictive models, and possible deviations in the timing of any automatic or human-initiated actions. It allows the analysis of accident consequences with different mitigation strategies and action timings and can include the evaluation of both safety (e.g. dose) and/or economic consequences. It can also be used as part of a larger risk informed methodology such as the Risk Informed Safety Margin Characterization approach proposed by the U.S. Light Water Reactor Sustainability (LWRS) Program to rank safety system and operator actions in terms of their probable impact on an event. The RAVEN framework developed under the LWRS Program is used as a D-PSA driver along with the TRACE thermal-hydraulic code to quantify risk evolution during transient event sequences. This paper uses the Dynamic Event Tree approach to analyze the critical time to failure for a SBO in a CANada Deuterium Uranium (CANDU) power plant and the impact of system reliabilities and timing on event outcomes. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Nuclear energy provides a low-carbon source of electricity that provides consistent and reliable power in a cost-effective manner. However, the accident at Fukushima Daiichi in 2011 demonstrated several important lessons on nuclear power plant severe events and risk mitigation and led to important changes in designs, improvement in emergency planning, and better understanding of external event hazards. Since 2011, the Fukushima accident has also led to new methodologies to characterize risk for low-probability events such as station blackout (SBO). In particular, large external events that lead to loss of Class IV power, and subsequent failures of backup power (Class III power) and or emergency power, and where the outcome may be dependent on human/emergency response functions, require additional methodological development to better quantify the risks and consequences. Dynamic Probabilistic Safety Assessment (D-PSA) is a set of stochastic tools that allows the integration of technology availability (e.g. as in standard Probabilistic Safety Assessment), human action probability, uncertainty in predictive models, and possible deviations in the timing of any automatic or human-initiated actions. It allows the analysis of accident consequences with different mitigation strategies and action timings and can include the evaluation of both safety (e.g. dose) and/or economic consequences. It can also be used as part of a larger risk informed methodology such as the Risk Informed Safety Margin Characterization approach proposed by the U.S. Light Water Reactor Sustainability (LWRS) Program to rank safety system and operator actions in terms of their probable impact on an event. The RAVEN framework developed under the LWRS Program is used as a D-PSA driver along with the TRACE thermal-hydraulic code to quantify risk evolution during transient event sequences. This paper uses the Dynamic Event Tree approach to analyze the critical time to failure for a SBO in a CANada Deuterium Uranium (CANDU) power plant and the impact of system reliabilities and timing on event outcomes. [ABSTRACT FROM AUTHOR]
ISSN:00295639
DOI:10.1080/00295639.2025.2455353