Estimation of Source Term Uncertainty in a Severe Accident With Correlated Variables

2014 ◽  
Author(s):  
Xiaoyu Zheng ◽  
Hiroto Itoh ◽  
Hitoshi Tamaki ◽  
Yu Maruyama
Keyword(s):  
Uncertainty Analysis ◽  
Nuclear Power ◽  
Source Term ◽  
Correlation Coefficients ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Severe Accident ◽  
Source Terms

The quantitative evaluation of the fission product release to the environment during a severe accident is of great importance. In the present analysis, integral severe accident code MELCOR 1.8.5 has been applied to estimating uncertainty of source term for the accident at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) as an example and to discussing important models or parameters influential to the source term. Forty-two parameters associated with models for the transportation of radioactive materials were chosen and narrowed down to 18 through a set of screening analysis. These 18 parameters in addition to 9 parameters relevant to in-vessel melt progression obtained by the preceding uncertainty study were input to the subsequent sensitivity analysis by Morris method. This one-factor-at-a-time approach can preliminarily identify inputs which have important effects on an output, and 17 important parameters were selected from the total of 27 parameters through this approach. The selected parameters have been integrated into uncertainty analysis by means of Latin Hypercube Sampling technique and Iman-Conover method, taking into account correlation between parameters. Cumulative distribution functions of representative source terms were obtained through the present uncertainty analysis assuming the failure of suppression chamber. Correlation coefficients between the outputs and uncertain input parameters have been calculated to identify parameters of great influences on source terms, which include parameters related to models on core components failure, models of aerosol dynamic process and pool scrubbing.

Influence of In-Vessel Melt Progression on Uncertainty of Source Term During a Severe Accident

2014 ◽  
Author(s):  
Hiroto Itoh ◽  
Xiaoyu Zheng ◽  
Hitoshi Tamaki ◽  
Yu Maruyama
Keyword(s):  
Uncertainty Analysis ◽  
Nuclear Power ◽  
Source Term ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Severe Accident ◽  
Source Terms ◽  
Radioactive Materials ◽  
Uncertainty Analyses ◽  
Reactor Pressure

The influence of the in-vessel melt progression on the uncertainty of source terms was examined in the uncertainty analysis with integral severe accident analysis code MELCOR (Ver. 1.8.5), taking the accident at Unit 2 of the Fukushima Daiichi nuclear power plant as an example. The 32 parameters selected from the rough screening analysis were sampled by Latin hypercube sampling technique in accordance with the uncertainty distributions specified for each parameter. The uncertainty distributions of the outputs, including the source terms of the representative radioactive materials (Cs, CsI, Te and Ba), the total mass of in-vessel H2 generation and the total debris mass released from the reactor pressure vessel to the drywell, were obtained through the uncertainty analysis with an assumption of the failure of drywell. Based on various types of correlation coefficient for each parameter, 9 significant uncertain parameters potentially dominating the source terms were identified. These 9 parameters were transferred to the subsequent sensitivity and uncertainty analyses, in which the influence of the transportation of radioactive materials was taken into account.

Uncertainty studies on hydrogen source term with MAAP5 code

Kerntechnik ◽  
2021 ◽  
Vol 86 (2) ◽  
pp. 152-163
Author(s):  
T.-C. Wang ◽  
M. Lee
Keyword(s):  
Hydrogen Production ◽  
Nuclear Power ◽  
Hydrogen Generation ◽  
Pearson Correlation ◽  
Latin Hypercube Sampling ◽  
Severe Accident ◽  
Model Parameters ◽  
Power Company ◽  
Sensitivity Studies ◽  
The Impact

Abstract In the present study, a methodology is developed to quantify the uncertainties of special model parameters of the integral severe accident analysis code MAAP5. Here, the in-vessel hydrogen production during a core melt accident for Lungmen Nuclear Power Station of Taiwan Power Company, an advanced boiling water reactor, is analyzed. Sensitivity studies are performed to identify those parameters with an impact on the output parameter. For this, multiple calculations of MAAP5 are performed with input combinations generated from Latin Hypercube Sampling (LHS). The results are analyzed to determine the 95th percentile with 95% confidence level value of the amount of in-vessel hydrogen production. The calculations show that the default model options for IOXIDE and FGBYPA are recommended. The Pearson Correlation Coefficient (PCC) was used to determine the impact of model parameters on the target output parameters and showed that the three parameters TCLMAX, FCO, FOXBJ are highly influencing the in-vessel hydrogen generation. Suggestions of values of these three parameters are given.

scholarly journals Higher-order dissipation in the theory of homogeneous isotropic turbulence

2016 ◽  
Vol 803 ◽  
pp. 250-274 ◽  
Author(s):  
Norbert Peters ◽  
Jonas Boschung ◽  
Michael Gauding ◽  
Jens Henrik Goebbert ◽  
Reginald J. Hill ◽  
...  
Keyword(s):  
Source Term ◽  
Isotropic Turbulence ◽  
Stokes Equations ◽  
Higher Order ◽  
Distribution Functions ◽  
Order Structure ◽  
Source Terms ◽  
Homogeneous Isotropic Turbulence ◽  
Higher Order Moments ◽  
Even Order

The two-point theory of homogeneous isotropic turbulence is extended to source terms appearing in the equations for higher-order structure functions. For this, transport equations for these source terms are derived. We focus on the trace of the resulting equations, which is of particular interest because it is invariant and therefore independent of the coordinate system. In the trace of the even-order source term equation, we discover the higher-order moments of the dissipation distribution, and the individual even-order source term equations contain the higher-order moments of the longitudinal, transverse and mixed dissipation distribution functions. This shows for the first time that dissipation fluctuations, on which most of the phenomenological intermittency models are based, are contained in the Navier–Stokes equations. Noticeably, we also find the volume-averaged dissipation $\unicode[STIX]{x1D700}_{r}$ used by Kolmogorov (J. Fluid Mech., vol. 13, 1962, pp. 82–85) in the resulting system of equations, because it is related to dissipation correlations.

scholarly journals Uncertainty and Sensitivity Analysis of the In-Vessel Hydrogen Generation for Gen-III PWR and Phebus FPT-1 with MELCOR 2.2

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4884
Author(s):  
Piotr Darnowski ◽  
Piotr Mazgaj ◽  
Mateusz Włostowski
Keyword(s):  
Sensitivity Analysis ◽  
Hydrogen Generation ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Latin Hypercube Sampling ◽  
Severe Accident ◽  
Sensitivity Analyses ◽  
Pressurized Water ◽  
Water Reactor ◽  
Best Estimate

In this study, uncertainty and sensitivity analyses were performed with MELCOR 2.2.18 to study the hydrogen generation (figure-of-merit (FoM)) during the in-vessel phase of a severe accident in a light water reactor. The focus of this work was laid on a large generation-III pressurized water reactor (PWR) and a double-ended hot leg (HL) large break loss of coolant accident (LB-LOCA) without a safety injection (SI). The FPT-1 Phebus integral experiment emulating LOCA was studied, where the experiment outcomes were applied for the plant scale modelling. The best estimate calculations were supplemented with an uncertainty analysis (UA) based on 400 input-decks and Latin hypercube sampling (LHS). Additionally, the sensitivity analysis (SA) utilizing the linear regression and linear and rank correlation coefficients was performed. The study was prepared with a new open-source MELCOR sensitivity and uncertainty tool (MelSUA), which was supplemented with this work. The FPT-1 best-estimate model results were within the 10% experimental uncertainty band for the final FoM. It was shown that the hydrogen generation uncertainties in PWR were similar to the FPT-1, with the 95% percentile being covered inside a ~50% band and the 50% percentile inside a ~25% band around the FoM median. Two different power profiles for PWR were compared, indicating its impact on the uncertainty but also on the sensitivity results. Despite a similar setup, different uncertainty parameters impacted FoM, showing the difference between scales but also a significant impact of boundary conditions on the sensitivity analysis.

Applicability of Common RANS Models for the Calculation of Transient Forced to Natural Convection

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Austen D. Fradeneck ◽  
Mark L. Kimber
Keyword(s):  
Natural Convection ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Latin Hypercube Sampling ◽  
Distribution Functions ◽  
Flow Reversal ◽  
Cumulative Distribution ◽  
Quality Data ◽  
System Response ◽  
Heated Plate

Abstract The applicability of several Reynolds averaged Navier–Stokes (RANS) turbulence models in calculating the transient evolution of a buoyancy-induced flow reversal along a vertical heated plate is analyzed through the use of validation quality experimental data from the Rotatable Buoyancy Tunnel (RoBuT) facility. This benchmark attempts to capture the transient evolution from downward forced convection to upward natural convection by removing power to the blower and allowing the buoyancy force emanating from the heated plate to gradually dominate as the primary driving force. Boundary conditions and system response quantities for the numerical model are supplied from the experiment every 0.2 s during the 18.2 s transient. ASME standards are used to quantify the numerical uncertainties while the input uncertainties are handled using a Latin hypercube sampling (LHS) method based on the steady-state conditions (t=0 s). Qualitative comparisons between numerical and experimental results at several downstream locations are supported using a validation metric based on the statistical disparity between the respective empirical and cumulative distribution functions (CDFs). The results from this study show that the standard linear eddy-viscosity models have difficulty in reproducing the complex features of the flow reversal in comparison with the more intricate turbulence models such as Reynolds stress models (RSM) and low-Reynolds number variants. This study also briefly highlights the difficulties of capturing validation quality data for three-dimensional multiphysics flow, while also providing insight for the design of future experimental efforts.

Reliable Reservoir Characterization and History Matching Using a Pattern Recognition Based Distance

2016 ◽  
Author(s):  
Jiyoon Lee ◽  
Jonggeun Choe
Keyword(s):  
Pattern Recognition ◽  
History Matching ◽  
Reservoir Characterization ◽  
Correlation Coefficients ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Uncertainty Range ◽  
Box Plots ◽  
Permeability Distribution ◽  
The Difference

A distance is defined as a measure of dissimilarity between two reservoir models. There have been many distances proposed for fast modeling. However, some distances cause distortion or loss in original permeability distribution of models. To avoid such problems, this study proposes a pattern recognition based distance. The distance is defined by the difference of correlation coefficients between ensemble models. From multi-dimensional scaling, initial 400 ensembles are presented on 2D plane using the distance. Then 10 groups are made by K-medoids clustering. After comparing oil production from each centroid and that of the reference field, 100 models are selected around the best centroid. We validate the clustering by comparing the uncertainty range of 100, 50, and 20 ensemble members sampled from the initial 400 models in box plots and cumulative distribution functions. For a history matching and reservoir characterization, ensemble smoother is applied to the 100 models selected. The proposed method takes only 25% time for simulation showing reliable results compared with the initial 400 models.

IRSN R&D Actions on FP Behaviour for RCS, Containment and FCVS in Severe Accident Conditions

2016 ◽  
Author(s):  
Laurent Cantrel ◽  
Thierry Albiol ◽  
Loïc Bosland ◽  
Juliette Colombani ◽  
Frédéric Cousin ◽  
...  
Keyword(s):  
Porous Materials ◽  
Nuclear Power ◽  
Source Term ◽  
Cooling System ◽  
Fission Products ◽  
Simulation Software ◽  
Severe Accident ◽  
Status Report ◽  
Diagnosis And Prognosis ◽  
Accident Conditions

This paper deals with near past, ongoing and planned R&D works on fission products (FPs) behaviour in Reactor Cooling System (RCS), containment building and in Filtered Containment Venting Systems (FCVS) for severe accident (SA) conditions. For the last topic, in link with the Fukushima post-accident management and possible improvement of mitigation actions for such SA, the FCVS topic is again on the agenda (see Status Report on Filtered Containment Venting, OECD/NEA/CSNI, Report NEA/CSNI/R(2014)7, 2014.) with a large interest at the international scale. All the researches are collaborative works; the overall objective is to develop confident models to be implemented in ASTEC SA simulation software. After being initiated in the International Source Term Program (ISTP), researches devoted to the understanding of iodine transport through the RCS are still ongoing in the frame of a bilateral agreement between IRSN and EDF with promising results. In 2017, a synthesis report of the last 10 years of researches, which have combined experimental and fundamental works based on the use of theoretical chemistry tools, will be issued. For containment, the last advances are linked to the Source Term Evaluation and Mitigation (STEM) OECD/NEA project operated by IRSN. The objective of the STEM project was to improve the evaluation of Source Term (ST) for a SA on a nuclear power plant and to reduce uncertainties on specific phenomena dealing with the chemistry of two major fission products: iodine and ruthenium. More precisely, the STEM project provided additional knowledge and improvements for calculation tools in order to allow a more robust diagnosis and prognosis of radioactive releases in a SA. STEM data will be completed by a follow-up, called STEM2, to further the knowledge concerning some remaining issues and be closer to reactor conditions. Two additional programmes deal with FCVS issues: the MItigation of outside Releases in the Environment (MIRE) (2013–2019) French National Research Agency (NRA) programme and the Passive and Active Systems on Severe Accident source term Mitigation (PASSAM) (2013–2016) European project. For FCVS works, the efficiencies for trapping iodine with various FCVS, covering scrubbers and dry filters, are examined to get a clear view of their abilities in SA conditions. Another part, performed in collaboration with French universities (Lorraine and Lille 1), is focused on the enhancement of the performance of these filters with specific porous materials able to trap volatile iodine. For that, influence of zeolites materials parameters (nature of the counter-ions, structure, Si/Al ratio …) will be tested. New kind of porous materials constituted by Metal organic Frameworks (MOF) will also be looked at because they can constitute a promising way of trapping.

Assessing local and spatial uncertainty with HER method

2021 ◽  
Author(s):  
Stephanie Thiesen ◽  
Uwe Ehret
Keyword(s):  
Uncertainty Analysis ◽  
Spatial Configuration ◽  
Order Relation ◽  
Uncertainty Estimation ◽  
Indicator Kriging ◽  
Distribution Functions ◽  
Spatial Uncertainty ◽  
Cumulative Distribution ◽  
Trade Offs ◽  
Entropy Reduction

<p>Uncertainty analysis is a critical subject for many environmental studies. We have previously combined statistical learning and Information Theory in a geostatistical framework for overcoming parameterization with functions and uncertainty trade-offs present in many traditional interpolators (Thiesen et al. 2020). The so-called Histogram via entropy reduction (HER) relaxes normality assumptions, avoiding the risk of adding information not available in the data. The authors showed that, by construction, the method provides a proper framework for uncertainty estimation which accounts for both spatial configuration and data values, while allowing one to introduce or infer properties of the field through the aggregation method. In this study, we explore HER method in the light of uncertainty analysis. In general, uncertainty at any particular unsampled location (local uncertainty) is frequently assessed by nonlinear interpolators such as indicator and multi-gaussian kriging. HER has shown to be a unique approach for dealing with uncertainty estimation in a fine resolution without the need of modeling multiple indicator semivariograms, order-relation violations, interpolation/extrapolation of conditional cumulative distribution functions, or stronger hypotheses of data distribution. In this work, this nonparametric geostatistical framework is adapted to address local and spatial uncertainty in the context of risk mapping. We investigate HER for handling estimations of threshold-exceeding probabilities to map the risk of soil contamination by lead in the well-known dataset of the region of Swiss Jura. Finally, HER method is extended to assess spatial uncertainty (uncertainty when several locations are considered together) through sequential simulation. Its results are compared to indicator kriging and benchmark models available in the literature generated for this particular dataset.</p><p>Thiesen S, Vieira DM, Mälicke M, Loritz R, Wellmann JF, Ehret U (2020) Histogram via entropy reduction (HER): an information-theoretic alternative for geostatistics. Hydrol Earth Syst Sci 24:4523–4540. https://doi.org/https://doi.org/10.5194/hess-24-4523-2020</p>

Scientists Debate Nuclear Source Terms

1985 ◽  
Vol 28 (6) ◽  
pp. 17-23
Author(s):  
John Graham
Keyword(s):  
Nuclear Power ◽  
Source Term ◽  
Large Body ◽  
Radioactive Material ◽  
Source Terms ◽  
American Nuclear Society ◽  
Life Threatening ◽  
Accident Scenarios ◽  
American Physical ◽  
Term Data

The nuclear source term, defined as the quantity, timing, and characteristic of the release of radioactive material to the environment following a core-melt accident, was thoroughly debated in 1985. This debate, summarized here, turns on the Nuclear Regulatory Commission's (NRC) source term for radioactive iodine, which is postulated as potentially the most life-threatening radionuclide that might escape in a nuclear power-plant accident. A generic radioiodine source term has been used by NRC as the surrogate for all others; thus, it has become one of the bases on which nuclear-safety regulations are founded. Following the Three Mile Island (TMI) accident, from which only traces of radioiodine escaped, scientists began arguing that nuclear regulations based on source-term calculations are erroneous and should be modified. The American Nuclear Society (ANS) and industry researchers have concluded that warranted reductions in the NRC source terms could range from a factor of ten to several factors of ten in most accident scenarios. The American Physical Society (APS), after agreeing with a large body of the conclusions from the other research groups, has told NRC that its source-term data base is still inadequate because of the existence of a number of uncertainties it found therein. Although APS presented no such conclusion, its findings made clear to NRC that an early reduction of all source terms is not warranted. The anti-nuclear lobby agrees with APS. The NRC has taken a cautious, conservative approach to the revision of its regulations based on new source-term data, although it too concedes that its old methodologies and conclusions must be revised and ultimately superceded.

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