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Record W2043715947 · doi:10.1063/1.4770310

Simulations of dilute sedimenting suspensions at finite-particle Reynolds numbers

2012· article· en· W2043715947 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysics of Fluids · 2012
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Alberta
FundersWestern Canada Research Grid
KeywordsPhysicsReynolds numberScalingAmplitudeDomain (mathematical analysis)Mathematical physicsQuantum mechanicsMechanicsMathematical analysisGeometry

Abstract

fetched live from OpenAlex

An alternative numerical method for suspension flows with application to sedimenting suspensions at finite-particle Reynolds numbers Rep is presented. The method consists of an extended lattice-Boltzmann scheme for discretizing the locally averaged conservation equations and a Lagrangian particle tracking model for tracking the trajectories of individual particles. The method is able to capture the main features of the sedimenting suspensions with reasonable computational expenses. Experimental observations from the literature have been correctly reproduced. It is numerically demonstrated that, at finite Rep, there exists a range of domain sizes in which particle velocity fluctuation amplitudes ⟨ΔV∥, ⊥⟩ have a strong domain size dependence, and above which the fluctuation amplitudes become weakly dependent. The size range strongly relates with Rep and the particle volume fraction ϕp. Furthermore, a transition in the fluctuation amplitudes is found at Rep around 0.08. The magnitude and length scale dependence of the fluctuation amplitudes at finite Rep are well represented by introducing new fluctuation amplitude scaling functions C1, (∥, ⊥)(Rep, ϕp) and characteristic length scaling function C2(Rep, ϕp) in the correlation derived by Segre et al. from their experiments at low Rep [“Long-range correlations in sedimentation,” Phys. Rev. Lett. 79, 2574–2577 (1997)10.1103/PhysRevLett.79.2574] in the form \documentclass[12pt]{minimal}\begin{document}$\langle \Delta V_{\parallel , \perp } \rangle = \langle V_{\parallel } \rangle C_{1, ( \parallel , \perp )} ( Re_{p},\phi _{p} ) \phi _{p}^{1/3} \lbrace 1 - \text{exp} [ -L / ( C_{2} ( Re_{p}, \phi _{p} ) r_{p} \phi _{p}^{-1/3} )] \rbrace$\end{document}⟨ΔV∥,⊥⟩=⟨V∥⟩C1,(∥,⊥)(Rep,ϕp)ϕp1/3{1−exp[−L/(C2(Rep,ϕp)rpϕp−1/3)]}.

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 score0.191
Threshold uncertainty score0.479

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 head0.030
GPT teacher head0.269
Teacher spread0.239 · 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