MétaCan
Menu
Back to cohort
Record W4321783433 · doi:10.1080/00295639.2022.2160612

Uncertainty Propagation in UAM Time-Dependent Neutronics PWR Studies

2023· article· en· W4321783433 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNuclear Science and Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity Network of Excellence in Nuclear Engineering
KeywordsNeutron transportNuclear dataNuclear engineeringPressurized water reactorLight-water reactorUncertainty analysisEnvironmental scienceNuclear reactor coreNuclear reactorNuclear physicsNeutronPhysicsComputer scienceEngineeringSimulation

Abstract

fetched live from OpenAlex

A subset of pressurized water reactor (PWR) studies from Exercise II-2 of the Uncertainty Analysis in Modeling for Light Water Reactors (UAM-LWR) benchmark study has been performed to quantify the importance of both nuclear data uncertainties and manufacturing uncertainties in an assembly depletion calculation and a mini-core rod movement transient. The depletion study of the 15 × 15 PWR assembly using the SAMPLER and TRITON modules of the SCALE code system revealed a maximum uncertainty in keff of 0.49% for fresh fuel, decreasing to 0.38% at the midpoint of the fuel cycle and rising back to 0.48% at the end of the fuel cycle. Uncertainties and correlations of various homogenized cross sections and other group constant data, such as keff, have been determined, and the effect of randomly applied manufacturing uncertainties was found to be largely negligible relative to nuclear data uncertainties for bulk lattice parameters. However, for local parameters, such as the pin power factors, assembly discontinuity factors, and diffusion coefficients, the effects from manufacturing uncertainties were appreciable and sometimes dominant.Nuclear data uncertainties were found to be the dominant contributors to uncertainty in the isotopic composition of the overall assembly, with the exception of very early in the fuel cycle, where manufacturing uncertainties such as perturbations to the fuel density and pin radius made nonnegligible contributions to total uncertainty. The contribution of manufacturing uncertainties to isotopic uncertainties was nonnegligible at a pin-by-pin level, but still smaller than the contributions from nuclear data uncertainty. Studies of the PWR mini-core rod movement transient using homogenized data from the SCALE models in the PARCS diffusion code showed little difference between the tested modeling approaches and demonstrated that nuclear data uncertainties dominated the manufacturing uncertainties in the global figures of merit considered, such as the equilibrium core boron concentration, the maximum core power factor, and the maximum reactivity insertion. For local effects, such as maximum pin power during the transient, the randomly applied manufacturing uncertainties were dominant. It was found in general that for global system properties, nuclear data uncertainties made significantly larger contributions to total uncertainty, whereas for local parameters the impact of manufacturing uncertainties was at least nonnegligible, and for some parameters, dominant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.214
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it