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|a dc
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|a Kumar, Shikhar
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|a Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
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|a Kumar, Shikhar
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|a Liang, Jingang
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|a Forget, Benoit Robert Yves
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|a Smith, Kord S.
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|a Liang, Jingang
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|a Forget, Benoit Robert Yves
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|a Smith, Kord S.
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|a Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods
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|b American Nuclear Society,
|c 2017-06-12T16:49:26Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/109793
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|a 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
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|a United States. Department of Energy (Nuclear Energy University Program Grant)
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|a en_US
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|a Article
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|t www.ans.org/meetings/file/682
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|t ANS Winter Meeting & Expo. PHYSOR 2016. Unifying Theory and Experiments in the 21st Century
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