Cross-section sensitivity and uncertainty analysis of the FNG copper benchmark experiment

I. Kodeli, K. Kondo, R. L. Perel, U. Fischer

Research output: Contribution to journalArticlepeer-review

Abstract

A neutronics benchmark experiment on copper assembly was performed end 2014–beginning 2015 at the 14-MeV Frascati neutron generator (FNG) of ENEA Frascati with the objective to provide the experimental database required for the validation of the copper nuclear data relevant for ITER design calculations, including the related uncertainties. The paper presents the pre- and post-analysis of the experiment performed using cross-section sensitivity and uncertainty codes, both deterministic (SUSD3D) and Monte Carlo (MCSEN5). Cumulative reaction rates and neutron flux spectra, their sensitivity to the cross sections, as well as the corresponding uncertainties were estimated for different selected detector positions up to ∼58 cm in the copper assembly. This permitted in the pre-analysis phase to optimize the geometry, the detector positions and the choice of activation reactions, and in the post-analysis phase to interpret the results of the measurements and the calculations, to conclude on the quality of the relevant nuclear cross-section data, and to estimate the uncertainties in the calculated nuclear responses and fluxes. Large uncertainties in the calculated reaction rates and neutron spectra of up to 50%, rarely observed at this level in the benchmark analysis using today's nuclear data, were predicted, particularly high for fast reactions. Observed C/E (dis)agreements with values as low as 0.5 partly confirm these predictions. Benchmark results are therefore expected to contribute to the improvement of both cross section as well as covariance data evaluations.

Original languageEnglish
Pages (from-to)1222-1226
Number of pages5
JournalFusion Engineering and Design
Volume109-111
DOIs
StatePublished - 2016

Keywords

  • Benchmark
  • DT neutron source
  • Neutron cross-sections
  • Neutron yield
  • Sensitivity-uncertainty analysis

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • General Materials Science
  • Nuclear Energy and Engineering
  • Civil and Structural Engineering

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