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Record W2034992251 · doi:10.1063/1.1835968

Linear stability of a Berman flow in a channel partially filled with a porous medium

2004· article· en· W2034992251 on OpenAlexafffund
Chuntao Deng, D. Mark Martinez

Bibliographic record

VenuePhysics of Fluids · 2004
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPorous mediumPhysicsMechanicsInstabilitySimilarity solutionSuctionCompressibilityDarcy's lawWork (physics)Flow (mathematics)Darcy numberThermodynamicsHeat transferPorosityBoundary layerMaterials science

Abstract

fetched live from OpenAlex

The temporal stability of similarity solutions for an incompressible fluid moving in a channel partially filled with a porous medium is analyzed. A constant wall suction acting on the bottom surface of the porous medium drives the fluid; the upper wall of the channel is impermeable. This work extends the work of King and Cox [“Asymptotic analysis of the steady-state and time-dependent Berman problem,” J. Eng. Math. 39, 87 (2001)] to a wider class of similarity solutions where coupled flow, both above and through a porous medium, is considered. In this work, a similarity transform is proposed which satisfies both the Navier–Stokes equation in the clear fluid portion of the domain and the Brinkman extended Darcy law relationship in the porous medium. The boundary conditions between the clear fluid and porous regions are those outlined by Ochoa-Tapia and Whitaker [“Momentum transfer at the boundary between a porous medium and a homogeneous fluid I: theoretical development,” Int. J. Heat Mass Transfer 38, 2635 (1995)]. The solutions of the steady flow are approximated analytically, in the limit of small wall suction, and numerically. Multiple steady-state solutions were found. The temporal stability of the solutions indicates turning-point bifurcations and instability only occurred with reverse flows.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.522

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations21
Published2004
Admission routes2
Has abstractyes

Explore more

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