Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods
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Forget_Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods.pdf
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Author(s)
Kumar, Shikhar
Liang, Jingang
Forget, Benoit Robert Yves
Smith, Kord S.
Date Issued
May 2016
Journal
ANS Winter Meeting & Expo. PHYSOR 2016. Unifying Theory and Experiments in the 21st Century
Publisher
American Nuclear Society
Citation
Kumar, Shikhar, Jingang Liang, Benoit Forget and Kord Smith. "Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods." PHYSOR 2016. Unifying Theory and Experiments in the 21st Century (May 1-5, 2016)
Version
Author's final manuscript
Abstract
Introduction - Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark [1] is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month.
These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown [2] that axially integrated radial maps of reaction rates were in close
agreement between provided detector data and calculated data
MIT Department
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
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DOI of Published Version
www.ans.org/meetings/file/682
