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Record W2065985471 · doi:10.1115/gt2013-95138

Film Cooling From Circular and Elliptical Exit Shaped Holes With Sister Hole Influence

2013· article· en· W2065985471 on OpenAlexafffund
Siavash Khajehhasani, B.A. Jubran

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoolantMechanicsBowingMaterials scienceJet (fluid)VortexAdiabatic processOpticsLift (data mining)Cooling flowPhysicsThermodynamicsAstrophysics

Abstract

fetched live from OpenAlex

In traditional film cooling configuration, coolant is injected through a cylindrical pipe with an inclined angle (0<α<90), which results in an elliptical exit shaped hole (EESH) at the blade surface. The present study makes use of an elliptical injection coolant pipe that leads to a circular exit shaped hole (CESH). The film cooling effectiveness and the associated flow for both cases of circular and elliptical shaped holes are numerically investigated. A comparison between the predicted results and the available experimental results from the literature for blowing ratios of M = 0.5 and 1, clearly indicated a better agreement with the experimental results when the realizable k-ε model was used. Further, the results indicate that the circular exit shaped hole improves the centerline and laterally averaged adiabatic effectiveness, particularly, at a higher bowing ratio of 1. The analysis of the vortex generation downstream of the jet for both exit shaped holes, shows a considerable decrease in the jet lift-off where the coolant flow tends to adhere more to the surface and hence, provides a better film cooling protection for the circular exit shaped hole, in comparison with the common elliptical exit shaped hole. The influence of sister holes on film cooling performance tends to be more effective with circular exit shaped hole than that with elliptical exit shaped hole.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.545

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 science0.0000.000
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 head0.179
Teacher spread0.170 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2013
Admission routes2
Has abstractyes

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