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Record W1993217142 · doi:10.1017/s0022112010006403

Drag and lift forces on random assemblies of wall-attached spheres in low-Reynolds-number shear flow

2011· article· en· W1993217142 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

VenueJournal of Fluid Mechanics · 2011
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDragSPHERESReynolds numberMechanicsLift (data mining)Lattice Boltzmann methodsDrag coefficientPhysicsDrag equationClassical mechanicsLift-to-drag ratioShear flowMaterials scienceTurbulenceDrag divergence Mach number

Abstract

fetched live from OpenAlex

Direct numerical simulations of the shear flow over assemblies of uniformly sized, solid spheres attached to a flat wall have been performed using the lattice-Boltzmann method. The random sphere assemblies comprised monolayers, double layers and triple layers. The Reynolds number based on the sphere radius and the overall shear rate was much smaller than 1. The results were interpreted in terms of the drag force (the force in the streamwise direction) and lift force (the force in the wall-normal direction) experienced by the spheres as a function of the denseness of the bed and the depth of the spheres in the bed. The average drag and lift forces decay monotonically as a function of the surface coverage of the spheres in the top layer of the bed. The sphere-to-sphere variation of the drag and lift forces is significant due to interactions between spheres via the interstitial fluid flow.

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: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.575

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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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