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  • 1.
    Basso, Simone
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Konovalenko, Alexander
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Yakush, Sergey
    Institute for Problems in Mechanics, Russian Academy of Sciences, Ave. Vernadskogo 101 Bldg 1, Moscow, 119526, Russia.
    Kudinov, Pavel
    Validation of DECOSIM code against experiments on particle spreading by two-phase flows in water pool2016In: Proceedings of the 11th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, Operation and Safety, NUTHOS-11, 2016, article id N11A0531Conference paper (Refereed)
    Abstract [en]

    Validation simulations by DECOSIM code are performed against recent PDS-P experiments on particle spreading in a planar vertical water pool with bottom air injection. The model implemented in the code considers two-fluid formulation (water, air), turbulence effects in liquid phase are taken into account by k-epsilon model with additional generation terms accounting for two-phase effects. Particles are described by Lagrangian model, with turbulent dispersion modeled by random-walk model. Simulations are performed in conditions corresponding to experimental setup, the test section was a plane rectangular tank of variable length (0.9 and 1.5 m) and pool depth (0.5, 0.7, and 0.9 m), the superficial gas injection velocity ranged between 0.12 and 0.69 m/s. Sedimentation of spherical stainless steel (1.5 and 3 mm) and glass (3 mm) particles was calculated and compared with experiments with respect to the mean spreading distance and lateral distributions of mass fraction of particles. Reasonable agreement between the results obtained and experimental measurements is achieved for all pool geometries, gas injection rates, and particle types, confirming adequacy of the modeling approach and suitability of DECOSIM code for severe accident analysis related to debris bed formation. Possible ways to further reduction of uncertainty in model validation are discussed.

  • 2.
    Kudinov, Pavel
    et al.
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Galushin, Sergey
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Grishchenko, Dmitry
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Yakush, Sergey
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Basso, Simone
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Konovalenko, Alexander
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Davydov, Mikhail
    KTH, School of Engineering Sciences (SCI), Physics, Nuclear Power Safety.
    Application of integrated deterministic-probabilistic safety analysis to assessment of severe accident management effectiveness in Nordic BWRs2016In: 17th International Topical Meeting on Nuclear Reactor Thermal Hydraulics, NURETH 2017, Association for Computing Machinery (ACM), 2016Conference paper (Refereed)
    Abstract [en]

    The goal of this work is to assess effectiveness of severe accident management strategy in Nordic type boiling water reactors (BWRs). Corium melt released into a deep pool of water below reactor vessel is expected to be fragmented to form a porous debris bed coolable by natural circulation of coolant. However, there is a risk that energetic steam explosion or non-coolable debris can threaten containment integrity. Both stochastic accident scenario (aleatory) and modeling (epistemic) uncertainties contribute to the risk assessment. Namely, the effects of melt release characteristics (jet diameter, melt composition, superheat), water pool conditions (i.e. depth and subcooling) at the time of the release, and modeling assumptions have to be quantified in a consistent manner. In order to address the uncertainty, we develop a Risk Oriented Accident Analysis framework (ROAAM+) where all stages of the accident progression are simulated using a set of models coupled through initial and boundary conditions. The analysis starts from plant damage states determined in PSA Level-1 and follows time dependent accident scenarios of core degradation, vessel failure, melt release, steam explosion and debris bed formation and coolability. In order to achieve computational efficiency sufficient for extensive sensitivity, uncertainty, and risk analysis the surrogate modeling approach is used. In the development of simplified but computationally efficient surrogate models (SM), we employ databases of solutions obtained by detailed but computationally expensive full models (FM). The process includes iterative refining of the framework, full and surrogate models in order to achieve completeness, consistency, and transparency in the review of the analysis results. In the paper we present results of the analysis aimed at quantification of uncertainty in the conditional containment failure probability. Specifically, we carry out sensitivity analysis using standalone and coupled models in order to identify the most influential scenario and modeling parameters for each sub-model. We assess the impact of the parameters on the prediction of the “load”, “capacity” and also failure probability. Then we quantify the effect of the most influential parameters on the failure probability. The results are presented using the failure domain approach and second order probability analysis, considering the uncertainty in distributions of the input parameters.

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