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Experimental evaluation of fluid-to-fluid scaling models for deteriorated heat transfer at supercritical pressures (carbon dioxide and Refrigerant 134a)

2025· article· en· W4410974515 on OpenAlexafffundabout
B. Sears, Stavros Tavoularis

Bibliographic record

VenueNuclear Engineering and Design · 2025
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsRefrigerantSupercritical fluidCarbon dioxideMaterials scienceScalingThermodynamicsSupercritical carbon dioxideHeat transferMechanicsWorking fluidHeat exchangerChemistryPhysics

Abstract

fetched live from OpenAlex

Experimental evaluations of fluid-to-fluid scaling methods for deteriorated heat transfer (DHT) in upward vertical flows in tubes at supercritical pressures were performed at the University of Ottawa Supercritical Heat Transfer Loop (SCUOL), using Refrigerant R134a as a medium at conditions that were determined by scaling those in previous carbon dioxide tests in the same loop. Two scaling methods were considered: the Ottawa method, which was based on local scaling, and the Pisa method, which was based on global scaling. Both methods were partially successful in scaling the occurrence or absence of DHT, but only when allowing for the thresholds of DHT onset conditions to span some ranges rather than being sharply defined.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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 designBench or experimental
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

Citations2
Published2025
Admission routes3
Has abstractyes

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