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Record W2103014368 · doi:10.1017/jfm.2013.479

The elastocapillary Landau–Levich problem

2013· article· en· W2103014368 on OpenAlex

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.

Bibliographic record

VenueJournal of Fluid Mechanics · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSurface tensionElasticity (physics)Capillary numberPhysicsCapillary actionPower lawMathematical physicsThermodynamicsMechanicsClassical mechanicsMathematics

Abstract

fetched live from OpenAlex

Abstract We study the classical Landau–Levich dip-coating problem for the case in which the interface possesses both elasticity and surface tension. The aim of the study is to develop a complete asymptotic theory of the elastocapillary Landau–Levich problem in the limit of small flow speeds. As such, the paper also extends our previous study on purely elastic Landau–Levich flow (Dixit & Homsy J. Fluid Mech. , vol. 732, 2013, pp. 5–28) to include the effect of surface tension. The elasticity of the interface is described by the Helfrich model and surface tension is modelled in the usual way. We define an elastocapillary number, $\epsilon $ , which represents the relative strength of elasticity to surface tension. Based on the size of $\epsilon $ , we can define three different regimes of interest. In each of these regimes, we carry out asymptotic expansions in the small capillary (or elasticity) numbers, which represents the balance of viscous forces to surface tension (or elasticity). In the weak elasticity regime, the film thickness is a small correction to the classical Landau–Levich law and can be written as $$\begin{eqnarray*}{\tilde {h} }_{\infty , c} = (0. 9458- 0. 0839~\mathscr{E}){l}_{c} C{a}^{2/ 3} , \quad \epsilon \ll 1,\end{eqnarray*}$$ where ${l}_{c} $ is the capillary length, $Ca$ is the capillary number and $\mathscr{E}= \epsilon / C{a}^{2/ 3} $ . In the elastocapillary regime, the film thickness is a function of $\epsilon $ through the power-law relationship $$\begin{eqnarray*}{\tilde {h} }_{\infty , ec} = {\bar {h} }_{\infty , e} L\hspace{0.167em} f(\epsilon )C{a}^{4/ 7} , \quad \epsilon \sim O(1),\end{eqnarray*}$$ where ${\bar {h} }_{\infty , e} $ is a numerical coefficient obtained in our previous study, $L$ is the elastocapillary length, and $f(\epsilon )$ represents the functional dependence of film thickness on the elastocapillary parameter.

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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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.314

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 head0.003
GPT teacher head0.163
Teacher spread0.160 · 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