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The framework is further extension of the approach originally developed and applied by Prof. In order to assess the effectiveness of SAM the Risk Oriented Accident Analysis Methodology framework (ROAAM+) has been developed. Depending on melt release conditions from the vessel and core-melt coolant interactions, containment integrity can be threatened by (i) formation of non-coolable debris bed, or (ii) energetic steam explosion. Nordic Boiling Water Reactor (BWR) design employs ex-vessel debris coolability in a deep pool of water as a severe accident management (SAM) strategy.
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Systematic statistical analysis is carried out to identify the needs for refinement of detailed methods, surrogate models, data and structure of the framework to reduce the uncertainty, and increase confidence and transparency in the risk assessment results. Second, coupled modular framework is developed connecting initial plant damage states with respective containment failure modes. First, fine-resolution but computationally expensive methods are used in order to develop computationally efficient surrogate models. A two-level coarse-fine iterative refinement process is proposed. The focus is on the process of refining the treatment and components of the framework to achieve (i) completeness, (ii) consistency, and (iii) transparency in the review of the analysis and its results. The goal of this work is to develop a risk-oriented accident analysis framework for quantifying conditional threats to containment integrity for a Nordic-type BWR. Success of the strategy is contingent upon melt release conditions from the vessel which determine (i) if corium debris bed is coolable, and (ii) potential for energetic steam explosion. The severe accident management (SAM) strategy involves complex and coupled physical phenomena of melt-coolant-structure interactions sensitive to the transient accident scenarios. In the case of severe accident in Nordic boiling water reactors (BWR), core melt is poured into a deep pool of water located under the reactor. The mode of debris ejection from the vessel has the dominant effect on the likelihood of creep-rupture failure of the vessel lower head and debris ejection rate from the vessel. Results of analysis show that penetration failure is predicted to occur before creep-rupture failure of the vessel lower head, however it does not preclude eventual creep-rupture failure of the vessel lower head. We demonstrate the effect of MELCOR code uncertain modelling parameters and modelling options on the resultant uncertainty in vessel failure mode and melt release conditions. The timing and mode of vessel failure and melt release conditions are predicted by MELCOR code. In this work we focus on uncertainty analysis of vessel failure mode and melt release conditions in unmitigated station blackout accident in Nordic BWR. Effectiveness of this strategy depends on melt release conditions from the vessel which is the major source of uncertainty in risk quantification of containment failure in Nordic BWRs in ROAAM+ Framework. Nordic Boiling Water Reactors (BWRs) employ containment pressure relief and filtered venting and ex-vessel debris coolability in the deep pool located under the reactor pressure vessel as a severe accident management (SAM) strategy. This work presents an example of application of the dynamic approach in a large-scale PSA model and demonstrate the integration of the ROAAM+ results in the PSA model. This information is used for enhanced modeling in the PSA-L2 for improved definition of sequences, where information from the ROAAM is used to refine PSA model resolution regarding risk important accident scenario parameters, that can be modelled within the PSA. The framework is comprised of a set of deterministic models that simulate different stages of the accident progression, and a probabilistic platform that performs quantification of the uncertainty in conditional containment failure probability. The Risk Oriented Accident Analysis Methodology (ROAAM+) has been developed to enable consistent and comprehensive treatment of both epistemic and aleatory sources of uncertainty in risk quantification.
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Typically, the static PSA models are built on a predetermined set of scenario parameters to describe the accident progression sequence and use a limited number of simulations in the underlying deterministic analysis to evaluate the consequences. A comprehensive and robust assessment of phenomenological uncertainties is a challenge for the current real-life PSA L2 applications, since such uncertainty is majorly driven by physical phenomena and timing of events.