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Record W4393164915 · doi:10.1088/1873-7005/ad3779

Drag on circular cylinders with porous outer layers in turbulent cross-flow

2024· article· en· W4393164915 on OpenAlexafffund
Alexandre Cohen, Donovan Blais, Laurent Mydlarski, B. R. Baliga

Bibliographic record

VenueFluid Dynamics Research · 2024
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDragTurbulenceMechanicsMaterials sciencePorosityFlow (mathematics)PhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract The effects of free-stream turbulence intensity and porosity on the drag on cylinders with porous outer layers in cross-flow was investigated experimentally. This work is motivated by the need to better model spotting—a forest fire propagation mechanism in which burning branches and other debris (termed firebrands) are transported away from the main fire by the prevailing wind and ignite new fires. Multiple levels of background turbulence were studied by using no grid, passive grids, and an active grid to generate turbulence intensities of 0.4%, 1.7%, 2.7% and 12.4%. The porous char-layer on the outer surface of firebrands was mimicked by wrapping wire meshes (of 10, 20 and 40 pores per cylinder diameter or PPD) around the cylinders, each to three different layer-thickness fractions ( 1 / 16 , 1 / 8 and 1 / 4 ) of the cylinder’s outer diameter. The drag on one smooth cylinder and nine cylinders with porous outer layers was measured for Reynolds numbers in the range 7000–17 000, at the aforementioned four turbulence intensities. The results showed that (i) the free-stream turbulence intensity and PPD of the wire meshes affect the Reynolds number dependence of the drag coefficient; (ii) the drag coefficient increases with free-stream turbulence intensity when it is relatively low (0.4%–2.7%), then decreases at high intensities (12.4%), and this decrease is more pronounced as the PPD increases; (iii) the drag coefficient increases with the thickness of the porous layer, and asymptotes to an effectively constant value after a critical thickness of about 1 / 8 of the cylinder’s diameter; and iv) the drag coefficient exhibits a non-monotonic dependence on the PPD of the wire mesh. These results demonstrate the importance of accounting for free-stream turbulence intensity and the parameters that characterize the porous outer layers of cylinders when modeling the drag on firebrands, or in other applications in which there is cross flow over cylinders with porous outer surfaces.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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