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Record W3119782646 · doi:10.1063/5.0030289

Comparison of turbine blade film cooling efficiency between PSP and TLC techniques in a stationary wind tunnel

2021· article· en· W3119782646 on OpenAlexfundno aff
Xiao-Jian He, Haiwang Li, Guoqin Zhao, Ruquan You

Bibliographic record

VenueAIP Advances · 2021
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesUniversity of Guelph
KeywordsThermal conductionReynolds numberWind tunnelMaterials scienceCoolantPressure-sensitive paintTurbine bladeThermodynamicsMechanicsTurbineComposite materialTurbulencePhysics

Abstract

fetched live from OpenAlex

In general, pressure sensitive paint (PSP) and thermochromic liquid crystal (TLC) are used to indicate film cooling efficiency. However, due to the mechanisms of PSP and TLC being different, their results are not consistent in some cases. Thus, analyzing the divergence between these two measurement methods is essential. In this paper, a comparison of measured film cooling efficiency distribution between PSP and TLC has been made on the same wind tunnel; the effect of heat conduction on film cooling was analyzed qualitatively and quantitatively. Sixteen cases were analyzed in which the mainstream Reynolds number was 35 000, 45 000, and 57 000; the blowing ratio was 0.5, 1.0, 1.5, and 2.0; and the density ratio was 0.91 and 1.44. We found that both PSP and TLC results exihibit an optimum blowing ratio under the condition of small and medium mainstream Reynolds numbers, but the measured film cooling efficiency is slightly different. Differences between PSP and TLC results were caused by the heat conduction of the substantial region. At the same time, a high mainstream Reynolds number and a high blowing ratio would boost heat conduction. Furthermore, in cases of high mainstream Reynolds number and low blowing ratio, the effect of heat conduction decreased obviously. When the blowing ratio is small as 0.5 and N2 acts as a coolant, PSP and TLC results match well, showing that in cases of low blowing ratio and low density ratio, the effect of heat conduction can be ignored.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.340

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 head0.011
GPT teacher head0.278
Teacher spread0.267 · 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 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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