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Record W4221016628 · doi:10.1115/1.4054079

Physics Modeling for Conceptual Designs of Proposed Experiments in the Zero Energy Deuterium-2 Critical Facility for Testing Small Modular Reactor-Type Fuels

2022· article· en· W4221016628 on OpenAlexafffundabout
D. G. Watts, F.P. Adams, Eugene Masala, L. Blomeley, Blair P. Bromley

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2022
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsCanadian Nuclear Laboratories
FundersAtomic Energy of Canada Limited
KeywordsNuclear engineeringModular designEnriched uraniumThorium fuel cycleConceptual designNuclear reactor coreOak Ridge National LaboratoryMolten salt reactorUraniumNuclear physicsComputer sciencePhysicsMOX fuelEngineeringMechanical engineeringMolten salt

Abstract

fetched live from OpenAlex

Abstract To enable the deployment of small modular reactors (SMRs) in Canada, Canadian Nuclear Laboratories (CNL) is interested in the applicability of zero energy deuterium-2 (ZED-2) experiments for validation of Monte Carlo reactor physics codes and models for SMR reactor fuels. This applicability is investigated here by considering potential ZED-2 experiments for testing fuel assemblies (FAs) for two different SMR technologies: the pressurized-water reactor (PWR), and the fluoride-salt-cooled high-temperature reactor (FHR). Each proposed set of mixed-lattice substitution experiments uses driver fuel channels containing CANDU flexible low enriched uranium/recovered uranium (CANFLEX-LEU/RU) fuel bundles. Simulation results indicate that a number of critical core configurations are possible, and should provide suitable reactor physics measurement data that can be used for physics design verification, and also for benchmarking and validation of computational reactor physics codes used in the design, operations, and safety analysis of SMRs based on PWR or FHR technologies.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.077
GPT teacher head0.266
Teacher spread0.189 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2022
Admission routes3
Has abstractyes

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