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Record W1990531391 · doi:10.1002/fld.1436

A model of the unsteady response of a backward‐facing compliant step

2007· article· en· W1990531391 on OpenAlexafffund
Andrew G. Gerber, A. Gordon L. Holloway, C. Ng

Bibliographic record

VenueInternational Journal for Numerical Methods in Fluids · 2007
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputational fluid dynamicsFinite element methodContext (archaeology)MechanicsMechanical engineeringFinite volume methodFlow (mathematics)Work (physics)Free surfaceEngineeringComputer scienceStructural engineeringPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract A large number of industrial surface coating and continuous casting operations require a fluid to flow from a reservoir, over a compliant step, onto a moving substrate. The contact line between the compliant step and substrate in such cases generally responds in an unsteady manner, depending on flow conditions, which can have an important influence on the surface quality of the final product. This work describes the development of a computational fluid dynamics (CFD) model for predicting this unsteady response, with a particular emphasis on isolating the natural frequency of the contact line in a backward‐facing step configuration. The compliant step was developed and implemented in the context of a pressure‐based finite‐element/finite‐volume CFD solution, implicit in time, and considers in‐surface forces based on a surface tension coefficient or an elastic membrane. Copyright © 2007 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.381
Teacher spread0.332 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes2
Has abstractyes

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