10 research outputs found

    Sensisivity and Uncertainty analysis for the Tritium Breeding Ratio of a DEMO Fusion reactor with a Helium cooled pebble bed blanket

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    An uncertainty analysis was performed for the tritium breeding ratio (TBR) of a fusion power plant of the European DEMO type using the MCSEN patch to the MCNP Monte Carlo code. The breeding blanket was of the type Helium Cooled Pebble Bed (HCPB), currently under development in the European Power Plant Physics and Technology (PPPT) programme for a fusion power demonstration reactor (DEMO). A suitable 3D model of the DEMO reactor with HCPB blanket modules, as routinely used for blanket design calculations, was employed. The nuclear cross-section data were taken from the JEFF-3.2 data library. For the uncertainty analysis, the isotopes H-1, Li-6, Li-7, Be-9, O-16, Si-28, Si-29, Si-30, Cr-52, Fe-54, Fe-56, Ni-58, W-182, W-183, W-184 and W-186 were considered. The covariance data were taken from JEFF-3.2 where available. Otherwise a combination of FENDL-2.1 for Li-7, EFF-3 for Be-9 and JENDL-3.2 for O-16 were compared with data from TENDL-2014. Another comparison was performed with covariance data from JEFF-3.3T1. The analyses show an overall uncertainty of ± 3.2% for the TBR when using JEFF-3.2 covariance data with the mentioned additions. When using TENDL-2014 covariance data as replacement, the uncertainty increases to ± 8.6%. For JEFF-3.3T1 the uncertainty result is ± 5.6%. The uncertainty is dominated by O-16, Li-6 and Li-7 cross-sections

    Nuclear data for fusion technology – the European approach

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    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

    Sensitivity and uncertainty analysis for the tritium breeding ratio of a DEMO fusion reactor with a helium cooled pebble bed blanket

    Get PDF
    An uncertainty analysis was performed for the tritium breeding ratio (TBR) of a fusion power plant of the European DEMO type using the MCSEN patch to the MCNP Monte Carlo code. The breeding blanket was of the type Helium Cooled Pebble Bed (HCPB), currently under development in the European Power Plant Physics and Technology (PPPT) programme for a fusion power demonstration reactor (DEMO). A suitable 3D model of the DEMO reactor with HCPB blanket modules, as routinely used for blanket design calculations, was employed. The nuclear cross-section data were taken from the JEFF-3.2 data library. For the uncertainty analysis, the isotopes H-1, Li-6, Li-7, Be-9, O-16, Si-28, Si-29, Si-30, Cr-52, Fe-54, Fe-56, Ni-58, W-182, W-183, W-184 and W-186 were considered. The covariance data were taken from JEFF-3.2 where available. Otherwise a combination of FENDL-2.1 for Li-7, EFF-3 for Be-9 and JENDL-3.2 for O-16 were compared with data from TENDL-2014. Another comparison was performed with covariance data from JEFF-3.3T1. The analyses show an overall uncertainty of ± 3.2% for the TBR when using JEFF-3.2 covariance data with the mentioned additions. When using TENDL-2014 covariance data as replacement, the uncertainty increases to ± 8.6%. For JEFF-3.3T1 the uncertainty result is ± 5.6%. The uncertainty is dominated by O-16, Li-6 and Li-7 cross-sections

    Sensitivity and uncertainty analysis for the tritium breeding ratio of a DEMO fusion reactor with a helium cooled pebble bed blanket

    No full text
    An uncertainty analysis was performed for the tritium breeding ratio (TBR) of a fusion power plant of the European DEMO type using the MCSEN patch to the MCNP Monte Carlo code. The breeding blanket was of the type Helium Cooled Pebble Bed (HCPB), currently under development in the European Power Plant Physics and Technology (PPPT) programme for a fusion power demonstration reactor (DEMO). A suitable 3D model of the DEMO reactor with HCPB blanket modules, as routinely used for blanket design calculations, was employed. The nuclear cross-section data were taken from the JEFF-3.2 data library. For the uncertainty analysis, the isotopes H-1, Li-6, Li-7, Be-9, O-16, Si-28, Si-29, Si-30, Cr-52, Fe-54, Fe-56, Ni-58, W-182, W-183, W-184 and W-186 were considered. The covariance data were taken from JEFF-3.2 where available. Otherwise a combination of FENDL-2.1 for Li-7, EFF-3 for Be-9 and JENDL-3.2 for O-16 were compared with data from TENDL-2014. Another comparison was performed with covariance data from JEFF-3.3T1. The analyses show an overall uncertainty of ± 3.2% for the TBR when using JEFF-3.2 covariance data with the mentioned additions. When using TENDL-2014 covariance data as replacement, the uncertainty increases to ± 8.6%. For JEFF-3.3T1 the uncertainty result is ± 5.6%. The uncertainty is dominated by O-16, Li-6 and Li-7 cross-sections

    Nuclear data for fusion technology – the European approach

    No full text
    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

    Nuclear data for fusion technology – the European approach

    No full text
    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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