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Record W4388825807 · doi:10.2495/be460111

A NOVEL BOUNDARY INTEGRAL METHOD FOR SLOW FREE SURFACE FLOWS

2023· article· en· W4388825807 on OpenAlexafffund
LOÏC GOBET, Robert G. Owens

Bibliographic record

VenueWIT transactions on engineering sciences · 2023
Typearticle
Languageen
FieldMathematics
TopicDifferential Equations and Numerical Methods
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDie swellSingularityStokes flowGravitational singularityFree surfaceMathematical analysisReynolds numberBoundary (topology)Singular point of a curveMathematicsBoundary value problemFlow (mathematics)GeometryMechanicsPhysicsMaterials scienceExtrusion

Abstract

fetched live from OpenAlex

The present article introduces a novel boundary integral method (BIM), adapted from an earlier method of Hansen and Kelmanson (1992, 1994) and suitable for the solution of creeping flow boundary value problems where the boundary presents singularities in the stresses.We use the new BIM to solve the problem of the planar extrusion of a Newtonian fluid at zero Reynolds number and, in particular, to determine the shape of the free surface in the immediate neighbourhood of the separation point for a range of capillary numbers.The proposed method incorporates the singular solution near the separation point, thus overcoming one limitation of a classical BIM to the problem (see, for example, Kelmanson (1983)).In a recent article, Owens (2022) also incorporated the singular solution into his BIM formulation.However, since the integration path used in the present BIM passes directly through the separation point this leads to an important improvement on the method of Owens (2022), who was obligated to skirt the singularity due to the non-integrability there of the normal derivative of the vorticity.Results presented for the extrudate swell ratio, the angle of separation and the leading exponent in the asymptotic expression for the stream function are shown to be in convincing agreement with others in the theoretical, numerical and experimental literature.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
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 head0.084
GPT teacher head0.366
Teacher spread0.281 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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