Journal
ANNALS OF NUCLEAR ENERGY
Volume 149, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.anucene.2020.107832
Keywords
Nuclear data uncertainties; Random sampling; Sensitivity analysis; Linear regression; Fast-reactor benchmark
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Funding
- German Federal Ministry for Economic Affairs and Energy
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The paper presents solutions for the neutron transport sub-exercises regarding pin cells, fuel assemblies, and supercells of the OECD/NEA UAM-SFR Benchmark. For this, the GRS XSUSA methodology is applied with a recently introduced approach performing linear regression analysis on the output samples, denoted as XSUSA(LR). The main purpose for this is to calculate sensitivity profiles and the main contributions to the total output uncertainties via the first-order uncertainty propagation formula, i.e. by multiplying the corresponding total/partial nuclear data covariance matrices with the total/partial sensitivity vectors. Confidence intervals were estimated by applying Jackknife resampling. Implicit effects are considered. All output uncertainties are compared to the corresponding values calculated with deterministic linear perturbation theory using TSUNAMI from SCALE 6.2.3. Various optimizations were applied with respect to nuclear data and problem geometry. The output uncertainties are significant - around 1.5% for multiplication factors and 5% for Doppler and sodium void reactivity effects. (C) 2020 Elsevier Ltd. All rights reserved.
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