MétaCan
Menu
Back to cohort
Record W2335495940 · doi:10.1115/gt2012-68081

Film Cooling From Short Holes With Sister Hole Influence

2012· article· en· W2335495940 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVolume 4: Heat Transfer, Parts A and B · 2012
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSisterTurbulenceMechanicsUpstream (networking)Flow (mathematics)Adiabatic processMaterials sciencePhysicsThermodynamicsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper reports a computational analysis on the effect of sister hole control on film cooling from short holes. The proposed method includes surrounding a primary injection hole by two or four smaller sister holes to actively maintain flow adhesion along the surface of the blade. A numerical study 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 carried out to determine the optimum 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. Similar results were found in evaluating both long and short hole geometries with a significantly less coherent flow field arising from the short hole. However, 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.530

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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