Computational Approach for Evaluation of Nuclear Data IincludingCovariance Information

For the stable and self-sufficient functioning of the DEMO fusion reactor, one of the most important parameters that must be demonstrated is the Tritium Breeding Ratio (TBR). The reliable assessment of the TBR with safety margins is a matter of fusion reactor viability. The uncertainty of the TBR in the neutronic simulations includes many different aspects such as the uncertainty due to the simplification of the geometry models used, the uncertainty of the reactor layout and the uncertainty introduced due to neutronic calculations. The last one can be reduced by applying high fidelity Monte Carlo simulations for TBR estimations. Nevertheless, these calculations have inherent statistical errors controlled by the number of neutron histories, straightforward for a quantity such as that of TBR underlying errors due to nuclear data uncertainties. In fact, every evaluated nuclear data file involved in the MCNP calculations can be replaced with the set of the random data files representing the particular deviation of the nuclear model parameters, each of them being correct and valid for applications. To account for the uncertainty of the nuclear model parameters introduced in the evaluated data file, a total Monte Carlo (TMC) method can be used to analyze the uncertainty of TBR owing to the nuclear data used for calculations. To this end, two 3D fully heterogeneous geometry models of the helium cooled pebble bed (HCPB) and water cooled lithium lead (WCLL) European DEMOs were utilized for the calculations of the TBR. The TMC calculations were performed, making use of the TENDL-2017 nuclear data library random files with high enough statistics providing a well-resolved Gaussian distribution of the TBR value. The assessment was done for the estimation of the TBR uncertainty due to the nuclear data for entire material compositions and for separate materials: structural, breeder and neutron multipliers. The overall TBR uncertainty for the nuclear data was estimated to be 3~4% for the HCPB and WCLL DEMOs, respectively.

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“…The N value should be assessed within the TMC sensitivity analyses. This approach is realized in the computer code shell BEKED [23].…”

Section: Generation Of the Random Files Using Covariancesmentioning

confidence: 99%

Statistical Analysis of Tritium Breeding Ratio Deviations in the DEMO Due to Nuclear Data Uncertainties

et al. 2021

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“…The evaluation of cross-sections using experimental data, results of model calculations, and covariance information was performed using the generalized least-squares (GLS) method [11] as implemented in KIT's BEKED code package [12]. Fig.…”

Section: Nuclear Data Evaluations -Tasks and Achievementsmentioning

confidence: 99%

Nuclear data activities of the EUROfusion consortium

Fischer

Avrigeanu

et al. 2020

EPJ Web Conf.

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The activities of the EUROfusion consortiums on the development of high quality nuclear data for fusion applications are presented. The activities, implemented in the Power Plant Physics and Technology (PPPT) programme of EUROfusion, include nuclear data evaluations for neutron and deuteron induced reactions and the production of related data libraries which satisfy the needs for nuclear analyses of the DEMO fusion power plant and the IFMIF-DONES neutron source. The activities are closely linked to the JEFF initiative of the NEA Data Bank. The evaluation work is complemented by extensive benchmark, sensitivity and uncertainty analyses to check the performance of the evaluated cross-section data and libraries against integral experiments.

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“…The co-variances of the cross sections are produced using the Monte Carlo technique of random sampling of model parameters fed as "prior" into the GANDR system [8], and constrained with experimental data via the generalised least-squares method. KIT employs the Universal Monte Carlo (UMC) approach [9] to generate covariance data taking into account both nuclear model and experimental uncertainties as implemented in KIT's BEKED code system [10]. TUW utilizes the Full Bayesian Evaluation Technique (FBET) [11] implemented in the GENEUS system [12] to provide evaluated crosssections with associated uncertainty information.…”

Section: Evaluation Of Neutron Cross-section Data For General Purposementioning

confidence: 99%

Nuclear data for fusion technology – the European approach

Fischer¹,

Avrigeanu

et al. 2017

EPJ Web Conf.

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Abstract. The European approach for the development of nuclear data for fusion technology applications is presented. Related R&D activities are conducted by the Consortium on Nuclear Data Development and Analysis for Fusion to satisfy the nuclear data needs of the major projects including ITER, the Early Neutron Source (ENS) and DEMO. Recent achievements are presented in the area of nuclear data evaluations, benchmarking and validation, nuclear model improvements, and uncertainty assessments.

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Computational Approach for Evaluation of Nuclear Data IincludingCovariance Information

Cited by 12 publications

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Statistical Analysis of Tritium Breeding Ratio Deviations in the DEMO Due to Nuclear Data Uncertainties

Statistical Analysis of Tritium Breeding Ratio Deviations in the DEMO Due to Nuclear Data Uncertainties

Nuclear data activities of the EUROfusion consortium

Nuclear data for fusion technology – the European approach

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