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Record W3187021090 · doi:10.2514/6.2021-2605

Pressure fluctuations under a turbulent boundary layer with transpiration cooling

2021· article· en· W3187021090 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.

Bibliographic record

VenueAIAA AVIATION 2021 FORUM · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTurbulenceBoundary layerMechanicsTranspirationFlow (mathematics)CoolantPressure gradientMaterials scienceThermalWork (physics)PhysicsThermodynamicsChemistry

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-2605.vid Transpiration cooling is an active thermal protective system (TPS) increasingly used in space applications under high thermal loads. A coolant gas is effused through a porous wall into a turbulent boundary layer (TBL) via a pressure gradient. The pressure fluctuations at the wall above the transpiration region result in temporal and spatial modulation of the flow within the porous flow network. This work quantifies the pressure fluctuations at the wall in transpiration cooling through the analysis of a direct numerical simulation (DNS) database. The pressure distributions compare favorably to existing analytical near-wall pressure fluctuation models. It is found that the while the addition of blowing does somewhat impact the shape and magnitude of the resultant spectrum, the Liepmann analytical model still yields a sufficient approximation within the resolved range.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.630

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)0.0010.000

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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