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Record W4283584031 · doi:10.11159/ffhmt22.122

Heat Transfer Coefficients in Perforated Fins

2022· article· en· W4283584031 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2022
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyU.S. Department of EnergyNational Science Foundation
KeywordsHeat transferMaterials scienceFinMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Three-dimensional steady state and incompressible flow and heat transfer are simulated over a perforated fin to validate the numerical heat transfer coefficients with experimental data. The validated numerical approach is necessary to investigate the complex flow patterns over perforations, which is difficult and costly to capture through experiments. Perforations with square cross sections are distributed equidistantly along the length of the fin. The simulation is performed for a laminar airflow with Reynolds numbers between 992 and 1722. The Navier-Stokes and energy equations are discretized through the finite volume approach, and the pressure and velocity components are coupled by the SIMPLEC algorithm. Excellent agreements (below 6.1%) are obtained by comparing average numerical and experimental Nusselt numbers. Suggestions for future research to address the current gaps in understanding the thermo-fluid mechanism in perforated fins are provided.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.217
Teacher spread0.197 · 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