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Record W3080521761 · doi:10.1063/5.0018416

On the role of surface grooves in the reduction of pressure losses in heated channels

2020· article· en· W3080521761 on OpenAlexafffund
Z. Hossain, J. M. Floryan

Bibliographic record

VenuePhysics of Fluids · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanicsPrandtl numberPressure gradientPhysicsBuoyancyReynolds numberReduction (mathematics)Pressure dropConvectionAdverse pressure gradientGeometryTurbulence

Abstract

fetched live from OpenAlex

Pressure-gradient-driven flows in grooved horizontal channels were investigated. The results show that a significant reduction in pressure losses can be achieved by exposing such channels to spatially distributed heating. The system response strongly depends on the characterization of both patterns and on their relative position, leading to a pattern interaction problem. Mismatch and misplacement of both patterns may result in a significant increase in pressure losses or may have no effect on such losses. The reduction in pressure loss is associated with the formation of convection rolls on the bounding surfaces due to spatially distributed buoyancy along the streamwise direction. The pressure-gradient-reducing effect is active only in small Reynolds number flows. Explicit results are given for fluids with the Prandtl number Pr = 0.71, representing air.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2020
Admission routes2
Has abstractyes

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