Uncertainty and sensitivity analysis of the LOFT L2-5 test: Results of the BEMUSE programme

Crécy, A. de; Bazin, P.; Glaeser, H.; Skorek, T.; Joucla, J.; Probst, Pierre; Fujioka, Ken; Chung, Bub Dong; Oh, Dong Yeol; Kyncl, M.; Pernica, R.; Macek, Jiří; Meca, R.; Macian, Rafael; D’Auria, F.; Petruzzi, A.; Batet, L.; Pérez, Montserrat; Reventós, F.

doi:10.1016/j.nucengdes.2008.06.004

Cited by 64 publications

(30 citation statements)

References 11 publications

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“…Developments in uncertainty methodology are therefore currently focused on model and material input data uncertainties, and specifically on the propagation of uncertainties through coupled neutronic and thermal-fluid calculations. A recent example of a comprehensive thermal-fluid uncertainty propagation study is Phase 3 of the Organization for Economic Co-operation and Development/Nuclear Energy Agency BEMUSE program (De Crécy 2008), where 11 participants calculated uncertainty and sensitivity data for a large break loss of cooling accident. An even larger international uncertainty and sensitivity quantification effort is also underway as part of the OECD's Uncertainty in Analysis Modeling (UAM) program, where nine consecutive uncertainty estimate phases cover all aspects of a coupled boiling water reactor calculation (Ivanov 2007).…”

Section: Uncertainty Propagation Methodologymentioning

confidence: 99%

PEBBED Uncertainty and Sensitivity Analysis of the CRP-5 PBMR DLOFC Transient Benchmark with the SUSA Code

Strydom¹

2011

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The need for a defensible and systematic uncertainty and sensitivity approach that conforms to the code scaling, applicability, and uncertainty (CSAU) process, and that could be used for a wide variety of software codes, was defined in 2008. The Gesellschaft für Anlagen und Reaktorsicherheit (GRS) company of Germany has developed one type of CSAU approach that is particularly well suited for legacy coupled core analysis codes, and a trial version of their Software for Uncertainty and Sensitivity Analyses (SUSA) was acquired on May 12, 2010. This report summarized the results of the initial investigations performed with SUSA, utilizing a typical High Temperature Reactor benchmark (the International Atomic Energy Agency CRP-5 Pebble Bed Modular Reactor 400 MW Exercise 2) and the PEBBED-THERMIX suite of codes. The following steps were performed as part of the uncertainty and sensitivity analysis:1. Eight PEBBED-THERMIX model input parameters were selected for inclusion in the uncertainty study: total reactor power, inlet gas temperature, decay heat, and the specific heat capability and thermal conductivity of the fuel, pebble bed, and reflector graphite.2. The input parameters variations and probability density functions were specified, and a total of 800 PEBBED-THERMIX model calculations were performed, divided into four sets of 100 and two sets of 200 steady-state and depressurized loss of forced cooling (DLOFC) transient calculations each.3. The steady-state and DLOFC maximum fuel temperature and the daily pebble fuel load rate data were supplied to SUSA as model output parameters of interest. The six data sets were statistically analyzed to determine the 5% and 95% percentile values for each of the three output parameters with a 95% confidence level, and typical statistical indictors were also generated (e.g., Kendall, Pearson, and Spearman coefficients).4. A SUSA sensitivity study was performed to obtain correlation data between the input and output parameters, and to identify the primary contributors to the output data uncertainties.It was found that the uncertainties in the decay heat, pebble bed, and reflector thermal conductivities were responsible for the bulk of the propagated uncertainty in the DLOFC maximum fuel temperature. It was also determined that the two standard deviation (2ı) uncertainty on the maximum fuel temperature was between ±58°C (3.6%) and ±76°C (4.7%) on a mean value of 1604°C. These values mostly depended on the selection of the distributions types, and not on the number of model calculations above the required Wilks' criteria.

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Section: Uncertainty Propagation Methodologymentioning

confidence: 99%

PEBBED Uncertainty and Sensitivity Analysis of the CRP-5 PBMR DLOFC Transient Benchmark with the SUSA Code

Strydom¹

2011

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“…5 that summarizes a study performed by KAERI in the framework of Phase III of the BEMUSE project. 21) A direct MonteCarlo simulation consisting of 3,500 runs was performed for simulating the LBLOCA L2-5 in the LOFT facility and several samples of n ¼ 59 and n ¼ 93 calculations were considered. The following considerations apply: .…”

Section: Propagation Of Code Input Uncertaintiesmentioning

confidence: 99%

“…Assuming such availability of relevant data, which are typically ITF data, and assuming the code correctly simulates the experiments, it follows that the differences between code computations and the selected experimental data are due to errors. If these errors comply with a number of acceptability conditions, 21) then the resulting (error) database is processed and the 'extrapolation' of the error can take place. Relevant conditions for the extrapolation are building up the NPP nodalization with the same criteria as was adopted for the ITF nodalizations and performing a similarity analysis and demonstrating that NPP calculated data are ''consistent'' with the data measured in a qualified ITF experiment.…”

Section: Propagation Of Code Calculation Output Errorsmentioning

confidence: 99%

Role of Best Estimate Plus Uncertainty Methods in Major Nuclear Power Plant Modifications

Andrea¹,

Petruzzi²

2010

Journal of Nuclear Science and Technology

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Current industrial trends to increase power production challenge the initial safety design limits of plants, which were evaluated generally using conservative tools and hypotheses. Advanced numerical tools and methods allow demonstrating that safety margins are still respected. These tools are modern fully validated thermal-hydraulic codes, coupled thermal-hydraulic/neutron-kinetic codes, and methodologies that use realistic hypotheses (rather than conservative ones) and estimate the uncertainty. The paper illustrates modern computational tools and approaches for improving plant operation and control and for supporting design modifications on existing nuclear power plants. A survey performed by Joint Research Centre's Institute for Energy is also presented and summarizes the feedback received by several countries of the European Union on the impact of modern Thermal-Hydraulics and Neutron-Kinetics tools on Operational Limits and Conditions and Operating Instructions and Procedures.

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“…Best Estimate (BE) codes have been introduced more recently to provide more realistic results and avoid over-conservatism [Zio et al 2010] [10 CFR 50.46]; their use requires the identification and quantification of the uncertainties in the code outputs coming from simplifications, approximations, round-off-errors, numerical techniques and uncertainties in the input variable values [Pourgol-Mohammad 2009]. The quantification of the uncertainties in the output can be demanding in terms of computational cost, because it requires a large number of simulations of the BE-code [de Crécy et al 2008;Di Maio et al 2014a]. …”

Section: Introductionmentioning

confidence: 99%

Finite mixture models for sensitivity analysis of thermal hydraulic codes for passive safety systems analysis

Maio

Nicola

Zio

et al. 2015

Nuclear Engineering and Design

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Uncertainty and sensitivity analysis of the LOFT L2-5 test: Results of the BEMUSE programme

Cited by 64 publications

References 11 publications

PEBBED Uncertainty and Sensitivity Analysis of the CRP-5 PBMR DLOFC Transient Benchmark with the SUSA Code

PEBBED Uncertainty and Sensitivity Analysis of the CRP-5 PBMR DLOFC Transient Benchmark with the SUSA Code

Role of Best Estimate Plus Uncertainty Methods in Major Nuclear Power Plant Modifications

Finite mixture models for sensitivity analysis of thermal hydraulic codes for passive safety systems analysis

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