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Record W2070367525 · doi:10.1115/1.1375165

Effect of Turbulence With Different Vortical Structures on Stagnation Region Heat Transfer

2001· article· en· W2070367525 on OpenAlexaff
Aung N. Oo, C.Y. Ching

Bibliographic record

VenueJournal of Heat Transfer · 2001
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsMcMaster UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsTurbulenceHeat transferMechanicsFreestreamStagnation pointPerpendicularReynolds numberStagnation temperatureMaterials scienceConvective heat transferTurbulence kinetic energyPhysicsGeometryMathematics

Abstract

fetched live from OpenAlex

The effect of freestream turbulence with different vortical structures on the stagnation region heat transfer was experimentally studied. Reynolds numbers, based on leading edge diameter of the heat transfer model with a cylindrical leading edge, ranged from 67,750 to 142,250. Turbulence generating grids of parallel rods were placed at several positions upstream of the heat transfer model in orientations where the rods were perpendicular and parallel to the stagnation line. The turbulence intensity and ratio of integral length scale to leading edge diameter were in the range 3.93 to 11.78 percent and 0.07 to 0.70, respectively. The grids with rods perpendicular to the stagnation line, where the primary vortical structures are expected to be perpendicular to the stagnation line, result in higher heat transfer than those with rods parallel to the stagnation line. The measured heat transfer data and turbulence characteristics are compared with existing correlation models.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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

Citations10
Published2001
Admission routes1
Has abstractyes

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