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Record W2139397920 · doi:10.1002/fld.2269

Spectrally accurate method for analysis of stationary flows of second‐order fluids in rough micro‐channels

2010· article· en· W2139397920 on OpenAlex
Alireza Mohammadi, J. M. Floryan, P. N. Kaloni

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

VenueInternational Journal for Numerical Methods in Fluids · 2010
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpectral methodChebyshev filterDomain (mathematical analysis)Flow (mathematics)Boundary (topology)Fourier transformMathematicsBoundary value problemFrequency domainFourier analysisComputational fluid dynamicsImmersed boundary methodMathematical analysisGeometryAlgorithmMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract A spectral method for the analysis of stationary flows of second‐order fluids in rough micro‐channels is developed. The algorithm employs a fixed computational domain with the boundaries of the flow domain being located inside the computational domain. The physical boundary conditions are enforced using the immersed boundary conditions concept. The algorithm relies on the Fourier expansions in the flow direction and the Chebyshev expansions in the transverse direction. Various tests confirm spectral accuracy of the algorithm. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.362
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.045
GPT teacher head0.434
Teacher spread0.389 · 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