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Record W4401633722 · doi:10.11159/jffhmt.2024.024

Terminal Settling Velocity of Cylindrical Rods of Various Shapes

2024· article· en· W4401633722 on OpenAlexfundvenueno aff
Amirhossein Hamidi, Daniel Daramsing, Mark Gordon, Liisa M. Jantunen, Ronald Hanson

Bibliographic record

VenueJournal of Fluid Flow Heat and Mass Transfer · 2024
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
FundersCrown-Indigenous Relations and Northern Affairs CanadaEnvironment and Climate Change CanadaGovernment of Canada
KeywordsSettlingRodTerminal (telecommunication)Terminal velocityMaterials scienceMechanicsPhysicsComputer scienceTelecommunicationsThermodynamicsMedicine

Abstract

fetched live from OpenAlex

In this research, a set of straight, curved, V-shaped, and U-shaped cylindrical rods are dropped in a chamber filled with a quiescent glycerin mixture to approximate the settling of microplastic fibres in the environment.The fall trajectory and terminal velocity of the rods are determined using cameras facing the two perpendicular sides of the chamber.The results show that the terminal velocities of the curved and V-shaped rods are greater than those of the straight rods with the same diameter and aspect ratio.U-shaped rods always exhibit a greater terminal velocity than straight rods with the same dimensions.As the aspect ratio of a U-shaped rod increases, the terminal velocity initially increases, reaches a peak value, and then decreases, reflecting the interplay between the length of the rod arms and the inclination angle.This research shows that fibre shape significantly affects the terminal velocity, which must, therefore, be included in future non-dimensional models to accurately predict the transport of microfibres in the environment.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.314

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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

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