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Record W2028968096 · doi:10.1115/gt2010-22060

A Parametric Study on the Effect of Sister Hole Location on Active Film Cooling Flow Control

2010· article· en· W2028968096 on OpenAlexafffund
Marc J. Ely, B.A. Jubran

Bibliographic record

VenueVolume 4: Heat Transfer, Parts A and B · 2010
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSisterFlow (mathematics)MechanicsAdiabatic processUpstream (networking)TurbulenceMaterials scienceThermodynamicsPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

This paper presents an investigation on the effect of sister holes on film cooling. The proposed technique surrounds a primary injection hole by two or four smaller sister holes to actively maintain flow adhesion along the surface of the blade. A numerical evaluation using the realizable k-ε turbulence model led to the determination that the use of sister holes significantly improves adiabatic effectiveness by countering the primary vortical flow structure. Research was performed to determine the optimal hole configuration, arriving at the conclusion that placing sister holes slightly downstream of the primary injection hole improves the near-hole effectiveness, while placing sister holes slightly upstream of the primary hole improves downstream effectiveness. On the whole, the sister hole approach to film cooling was found to offer viable improvements over standard cooling regimes.

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 score0.004

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 communication0.0000.000
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 head0.006
GPT teacher head0.201
Teacher spread0.196 · 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

Citations27
Published2010
Admission routes2
Has abstractyes

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Same venueVolume 4: Heat Transfer, Parts A and BSame topicTurbomachinery Performance and OptimizationFrench-language works237,207