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Record W4249544772 · doi:10.32920/ryerson.14647299

Numerical Analysis of Film Cooling Performance of Micro Holes and Compound Angle Sister Holes

2021· preprint· en· W4249544772 on OpenAlexaff
Sana Milud Muftah Abd Alsalam

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTurbulenceFreestreamReynolds-averaged Navier–Stokes equationsCoolantMechanicsMaterials scienceReynolds stressComputational fluid dynamicsJet (fluid)Cooling flowReynolds numberTurbulence kinetic energyVortexPhysicsThermodynamics

Abstract

fetched live from OpenAlex

In the present research, micro holes and compound angle sister holes have been numerically investigated as two different techniques to enhance the cylindrical hole cooling performance, which suffers from a low cooling performance at high blowing ratio. The numerical analysis is performed over a flat plate model to assess the film effectiveness and the associated flow field at low and high blowing ratios. The performance assessment of the discrete round micro hole with a 200 µm diameter reveals that the micro hole yields the best cooling performance at low blowing ratios, and there is nearly 30% increase in the overall film cooling effectiveness compared to that of the round macro hole. The flow field results demonstrate the presence of a Counter-Rotating Vortex Pair (CRVP) at a smaller size and less strength, thus, contributed to better spanwise spreading of the coolant jet and lateral film cooling effectiveness. Micro holes present an improvement in the lateral film cooling effectiveness at high freestream turbulence intensity and high blowing ratios. Computational evaluation of the CFD prediction capability of the sister holes cooling effectiveness using five RANS turbulence models has been carried out as well as an assessment of the effects of the near-wall modeling on the predicted lateral effectiveness. The turbulence models used are realizable k-epsilon, standard k-epsilon, RNG k-epsilon, Reynolds stress model, and Spalart-Allmaras model. It is generally found that realizable k-ε combined with the enhanced wall treatment provides the best prediction of the numerical results in comparison to the experimental measurements at a low blowing ratio while an underprediction of the lateral performance is found at a high blowing ratio from all examined turbulence models. The compound angle upstream sister holes (CAUSH) have been proposed as a novel and simple design of the cooling hole whereas the numerical results have shown a notable increase in both centerline and lateral effectiveness for all tested compound angles at all blowing ratios. The anti-counter rotating vortices pair (ACRVP) structure generated from the compound angle upstream sister holes has actively controlled the flow field and maintained the coolant jet fully attached to the plate surface while restraining the coolant lift-off at high blowing ratios. Finally, the influence of the compound angle sister holes streamwise location on the thermal and flow field performance has also been analyzed, whereas three locations: upstream, midstream, and downstream are examined. It is found that the midstream and downstream locations offered a considerable increase in the cooling effectiveness, which is very much dependent on the blowing ratio and the area downstream of the cooling holes. In addition, the optimum centerline effectiveness is obtained by the downstream location, while the best lateral effectiveness is attained through the midstream location.

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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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.224
Teacher spread0.208 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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