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Record W1967159150 · doi:10.1115/1.1471526

Stagnation Line Heat Transfer Augmentation Due to Freestream Vortical Structures and Vorticity

2002· article· en· W1967159150 on OpenAlexaff
Aung N. Oo, C.Y. Ching

Bibliographic record

VenueJournal of Heat Transfer · 2002
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFreestreamVorticityMechanicsTurbulenceStagnation pointHeat transferStagnation temperaturePhysicsReynolds numberLeading edgeMaterials scienceVortex

Abstract

fetched live from OpenAlex

Abstract An experimental study has been performed to investigate the effect of freestream vortical structures and vorticity on stagnation region heat transfer. A heat transfer model with a cylindrical leading edge was tested in a wind tunnel at Reynolds numbers ranging from 67,750 to 142,250 based on leading edge diameter of the model. Grids of parallel rods were placed at several locations upstream of the heat transfer model in orientations where the rods were perpendicular and parallel to the stagnation line to generate freestream turbulence with distinct vortical structures. All three components of turbulence intensity, integral length scale and the spanwise and transverse vorticity were measured to characterize the freestream turbulence. The measured heat transfer data and freestream turbulence characteristics were compared with existing empirical models for the stagnation line heat transfer. A new correlation for the stagnation line heat transfer has been developed that includes the spanwise fluctuating vorticity components.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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

Citations6
Published2002
Admission routes1
Has abstractyes

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