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Record W4412912552 · doi:10.1063/5.0278472

Settling of U-shaped rods at low Reynolds numbers

2025· article· en· W4412912552 on OpenAlexafffund
A. Hamidi, Mark Gordon, Liisa M. Jantunen, Ronald Hanson

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsEnvironment and Climate Change CanadaYork University
FundersNorthern Contaminants ProgramGovernment of Canada
KeywordsPhysicsSettlingReynolds numberMechanicsRodClassical mechanicsTurbulenceThermodynamics

Abstract

fetched live from OpenAlex

The low Reynolds number settling of U-shaped and straight rods in a quiescent fluid was experimentally investigated in this study. It was shown that the U-shaped rods adopt an oblique orientation and horizontal drift at Reynolds numbers above a critical value and middle arm length ratios below a critical value. Due to the non-zero inclination angle of a U-shaped rod, it consistently settles faster than a straight rod with the same diameter and aspect ratio. The vertical component of the U-shaped rod terminal velocity reaches a maximum at an intermediate value of aspect ratio and middle arm length ratio or remains nearly constant as these geometric parameters change, indicating a trade-off between the length and orientation of the side arms. Furthermore, the horizontal velocity ratio of a U-shaped rod is strongly correlated with the inclination angle, either increasing or remaining constant with an increase in aspect ratio, depending on the Reynolds number. Finally, a new model for the vertical component of a U-shaped rod terminal velocity was developed using the experimental results of this study.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.419

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 head0.007
GPT teacher head0.242
Teacher spread0.236 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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