Nordic Boiling Water Reactors (BWRs) employ ex-vessel debris coolability as a severe accident management strategy (SAM). Core melt is released into a deep pool of water where formation of noncoolable debris bed and ex-vessel steam explosion can pose credible threats to containment integrity. Success of the strategy depends on the scenario of melt release from the vessel that determines the melt-coolant interaction phenomena. The melt release conditions are determined by the in-vessel phase of severe accident progression. Specifically, properties of debris relocated into the lower plenum have influence on the vessel failure and melt release mode. In this work we use MELCOR code for prediction of the relocated debris. Over the years, many code modifications have been made to improve prediction of severe accident progression in light-water reactors. The main objective of this work is to evaluate the effect of models and best practices in different versions of MELCOR code on the in-vessel phase of different accident progression scenarios in Nordic BWR. The results of the analysis show that the MELCOR code versions 1.86 and 2.1 generate qualitatively similar results. Significant discrepancy in the timing of the core support failure and relocated debris mass in the MELCOR 2.2 compared to the MELCOR 1.86 and 2.1 has been found for a domain of scenarios with delayed time of depressurization. The discrepancies in the results can be explained by the changes in the modeling of degradation of the core components and changes in the Lipinski dryout model in MELCOR 2.2.

This work is motivated by the problem of restraining temperature escalation inside a porous heat-releasing media submerged in a pool of liquid coolant. When coolant temperature reaches saturation, boiling begins in the bulk of the porous bed, with void generation rate determined by the heating power. Amount of void determines hydrostatic pressure difference that drives natural circulation of two-phase flow through the porous material. At a certain critical value of the heat release rate, the driving head cannot overcome drag of the two phase porous media flow, which results in complete evaporation of coolant in some zone. Temperature of material in the dry zone increases significantly due to deterioration of heat exchange with single phase vapor flow in comparison with boiling flow heat transfer. The paper considers the problem of determining the critical conditions for onset of dryout in a heat-releasing porous bed of an arbitrary shape. The well-known one-dimensional problem for a flat top-flooded bed is revisited, and the functional form of the dryout boundary (expressed as the dryout heat flux, DHF) is derived using non-dimensional parameters. Asymptotic behavior of the solution is analyzed, and, by the method of asymptotic interpolation, a surrogate model is proposed consisting of three single-argument, non-dimensional functions. It is shown that such a model provides acceptable accuracy even in the cases where complete similarity of solutions is not achieved. The results obtained provide important insights into the physics of the problem, reduce the number of free parameters, and enable fast evaluation of dryout conditions without the need of numerical solution of algebraic equations involved in the exact formulation. The ultimate goal of the surrogate model development, i.e. its application to multidimensional configurations, is discussed.

Spargers are multi-hole injection pipes used in Boiling Water Reactors (BWR) and Generation III/III+ Pressurized Water Reactors (PWR) to condense steam in large water pools. During the steam injection, high pool surface temperatures induced by thermal stratification can lead to higher containment pressures compared with completely mixed pool conditions, the former posing a threat for plant safety. The Effective Heat Source (EHS) and Effective Momentum Source (EMS) models were previously developed and validated for the modelling of a steam injection through blowdown pipes. The goal of this paper is to extend the EHS/EMS model capabilities towards steam injection through multi-hole spargers. The models are implemented in ANSYS Fluent 17.0 Computational Fluid Dynamics (CFD) code and calibrated against the spargers experiments performed in the PPOOLEX and PANDA facilities, analysed by the authors in Gallego-Marcos et al. (2018b). CFD modelling guidelines are established for the adequate simulation of the pool behaviour. A new correlation is proposed to model the turbulent production and dissipation caused by buoyancy. Sensitivity studies addressing the effect of different assumptions on the effective momentum magnitude, profile, angle and turbulence are presented. Calibration of the effective momentum showed an inverse proportionality to the sub-cooling. Differences between the effective momentum calibrated for PPOOLEX and PANDA are discussed. Analysis of the calculated flow above the cold stratified layer showed that the erosion of the layer is induced by the action of turbulence rather than mean shear flow.

Computational Fluid Dynamics (CFD) provides means for high-fidelity 3D thermal-hydraulics analysis of Generation IV pool-type nuclear reactors. However, to be used in the decision making process a proof of code adequacy for intended application is required. This paper describes the Verification, Validation and Uncertainty Quantification (VVUQ) of a commercial CFD code Star-CCM + for forced, natural and mixed convection regimes in lead-bismuth eutectic (LBE) coolant pool flows. Code qualification is carried out according to an iterative VVUQ process aiming to reduce user effects. Validation data is produced in TALL-3D experimental facility - a 7 m high LBE loop featuring a 3D pool-type test section. Accurate prediction of mutual interaction between thermal stratification and mixing in the pool and the loop dynamics requires 3D analysis, especially during natural circulation. Solution verification is used to reduce the numerical uncertainty during code validation activities. Sensitivity Analysis (SA) is used to identify the effect of the most influential uncertain input parameters (UIPs) on numerical results. Two new visualization methods are proposed to enhance interpretation of the SA results. Dedicated experiments are performed according to the SA results to reduce the uncertainties in the most important UIPs. Automated calibration method for large CFD models is tested and demonstrated in combination with manual calibration using detailed temperature profile measurements in the pool. Calibration reveals the deficiencies in the modeling of heat losses owing to the presence of thermal bridges and other local effects in thermal insulation that are not explicitly modeled. It is demonstrated that Star-CCM + is able to predict thermal stratification and mixing phenomena in the pool type geometries. The results are supported by an Uncertainty Analysis (UA).

Severe accident management (SAM) in Nordic boiling water reactors (BWR) relies on ex-vessel core debris coolability. In case of core melt and vessel failure, melt is poured into a deep pool of water located under the reactor. The melt is expected to fragment, quench, and form a debris bed, coolable by natural circulation of water. Success of the strategy is contingent upon melt release conditions from the vessel which determine (i) properties and thus coolability of the debris bed, and (ii) potential for energetic steam explosion. Both non-coolable debris bed and steam explosion are credible threats to containment integrity. Melt release conditions are the major source of uncertainty in quantification of the risk of containment failure in Nordic BWRs using ROAAM+ Framework. The melt release conditions, including in-vessel\ex-vessel pressure, lower drywell pool depth and temperature, are affected by aleatory (severe accident scenario) and epistemic (modeling) uncertainties. In this work we use MELCOR code to perform the analysis of the effects of Severe accident scenarios and modelling options in MELCOR on the properties of debris relocated to the lower head, the time and the mode of vessel lower head failure. We identify the most influential uncertain factors and discuss the needs for improvements in the modeling approaches. 

A comprehensive and robust assessment of severe accident management effectiveness in preventing unacceptable releases is a challenge for a today’s real life PSA. This is mainly due to the fact that major uncertainty is determined by the physical phenomena and timing of the events. The static PSA is built on choosing scenario parameters to describe the accident progression sequence and typically uses a limited number of simulations in the underlying deterministic analysis. Risk Oriented Accident Analysis Methodology framework (ROAAM+) is being developed in order to enable consistent and comprehensive treatment of both epistemic and aleatory uncertainties. The framework is based on a set of deterministic models that describe different stages of the accident progression. The results are presented in terms of distributions of conditional containment failure probabilities for given combinations of the scenario parameters. This information is used for enhanced modeling in the PSA-L2. Specifically, it includes improved definitions of the sequences determined by the physical phenomena rather than stochastic failures of the equipment, improved knowledge of timing in sequences and estimation of probabilities determined by the uncertainties in the phenomena. In this work we present an example of application of the dynamic approach in a large scale PSA model and show that the integration of the ROAAM+ results and the PSA model can potentially lead to a considerable change in PSA Level 2 analysis results.