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Record W4230889362 · doi:10.1080/00295450.2020.1784669

Transient System Thermal-Hydraulic Assessment of Advanced Uranium- and Thorium-Based Fuel Bundle Concepts for Potential Use in Pressure Tube Heavy Water Reactors—II: Full-Core Analyses

2020· article· en· W4230889362 on OpenAlexaff
S. Wang, T. Beuthe, Xianmin Huang, Armando Nava Domínguez, Blair P. Bromley, Ashlea V. Colton

Bibliographic record

VenueNuclear Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsThermal hydraulicsNuclear engineeringUraniumBundleThoriumTransient (computer programming)Environmental scienceTube (container)Heavy waterMaterials scienceWaste managementNuclear physicsPhysicsEngineeringMechanicsHeat transferComputer scienceDeuteriumMetallurgy

Abstract

fetched live from OpenAlex

The use of advanced uranium-based and thorium-based fuel bundles in pressure tube heavy water reactors (PT-HWRs) has the potential to improve the utilization of uranium resources while also providing improvements in performance and safety characteristics of PT-HWRs. Earlier lattice physics and reactor core physics studies have demonstrated the feasibility of using such advanced fuels; however, thermal-hydraulic (T-H) studies are required to confirm that these advanced fuels will have adequate T-H safety margins. Preliminary system T-H transient simulations have been carried out for a 700-MW(electric)–class PT-HWR in a postulated loss-of-coolant accident (LOCA) using the CATHENA code. One purpose of this work was to demonstrate that such simulations of a PT-HWR filled entirely with advanced fuels could be set up and executed successfully in a CATHENA transient simulation model. The other purpose was to evaluate the peak sheath and peak fuel centerline temperatures during a LOCA to perform an analysis that compares the relative performance of each of the proposed advanced fuels. System T-H simulations with CATHENA were performed to model a postulated LOCA event with a 20% inlet header break in a typical 700-MW(electric)–class PT-HWR using two types of advanced uranium-based and thorium-based fuel bundles in modified 37-element and 35-element geometries. Calculations were also performed for a PT-HWR using conventional natural uranium fuel in 37-element fuel bundles for comparison. In the event of a LOCA, there is a drop in the primary circuit pressure. It is assumed that there is a 2-s delay between the signal of the low primary pressure and the tripping of the reactor. When the reactor trips, the shutdown rods are inserted. The reactor trip is followed by the activation of the emergency core cooling system, which occurs 30 s after the LOCA starts, with a trip signal on the boiler crash cooling. Simulation results for the LOCA demonstrated that the peak fuel centerline temperatures (ranging from 1822°C to 2183°C) were several hundred degrees below the expected melting point of UO2 (~2865°C). Simulations also demonstrated that the peak sheath temperatures for the advanced fuel concepts ranged from 1177°C to 1204°C, which are lower than that with conventional NU fuel in 37-element fuel bundles. Thus, the system T-H analysis of the relative results provides confidence in the proposed advanced uranium-based and thorium-based fuel concepts for potential use in PT-HWRs.

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)0.000
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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