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Record W2013055394 · doi:10.1017/s0022112005006002

Analytical solution for maximal frictional two-layer exchange flow

2005· article· en· W2013055394 on OpenAlexaff
Gu Li, Gregory A. Lawrence

Bibliographic record

VenueJournal of Fluid Mechanics · 2005
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMechanicsBarotropic fluidFlow (mathematics)Constant (computer programming)Context (archaeology)Nonlinear systemMaterials scienceThermodynamicsPhysicsGeologyComputer science

Abstract

fetched live from OpenAlex

The maximal steady frictional exchange flow through a rectangular channel of constant width is analysed within the context of internal hydraulics. A one-dimensional analytical solution to the fully nonlinear problem of two-layer frictional exchange is developed and shown to compare well with experimental and field data. The analytical solution gives the maximal exchange flow rate and the variation in the height of the density interface along the channel for the case of zero barotropic forcing. In contrast to the assumed constant interface slope of previous theoretical formulations of frictional exchange flows, the resulting density interface is found to be nonlinear and asymmetric. Both interfacial and bottom friction play important roles in determining the exchange flow rate. It is shown that the frictional effects are important even in relatively short channels.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.282
Teacher spread0.251 · 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 designTheoretical or conceptual
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

Citations24
Published2005
Admission routes1
Has abstractyes

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