Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods
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 cor...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
American Nuclear Society
2017
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| Online Access: | http://hdl.handle.net/1721.1/109793 https://orcid.org/0000-0002-8876-4878 https://orcid.org/0000-0003-1459-7672 https://orcid.org/0000-0003-2497-4312 |
| Summary: | 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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