Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods
- Computational Reactor Physics Group, Massachusetts Institute of Technology (United States)
Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark 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 that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)
- OSTI ID:
- 23042784
- Journal Information:
- Transactions of the American Nuclear Society, Vol. 115; Conference: 2016 ANS Winter Meeting and Nuclear Technology Expo, Las Vegas, NV (United States), 6-10 Nov 2016; Other Information: Country of input: France; 6 refs.; available from American Nuclear Society - ANS, 555 North Kensington Avenue, La Grange Park, IL 60526 (US); ISSN 0003-018X
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
97 MATHEMATICAL METHODS AND COMPUTING
BENCHMARKS
BURNUP
CALCULATION METHODS
COMPUTERIZED SIMULATION
COUNTING RATES
DATA PROCESSING
FISSION
FISSION CHAMBERS
FUEL ASSEMBLIES
INTERPOLATION
NUCLEAR CORES
PWR TYPE REACTORS
REACTION KINETICS
SPACERS
TIME-SERIES ANALYSIS
TRANSIENTS
URANIUM 235
VALIDATION