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A contact line force model for the simulation of drop impacts on solid surfaces using volume of fluid methods

2023· article· en· W4379260776 on OpenAlexafffund
Adolfo Esteban, Pablo Gómez, Claudio Zanzi, Joaquín López, Markus Bussmann, Julio Hernández

Bibliographic record

VenueComputers & Fluids · 2023
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Toronto
FundersMinisterio de UniversidadesFaculty of Science and Engineering, University of ManchesterUniversidad Politécnica de CartagenaMinisterio de Ciencia e InnovaciónUniversidad Nacional de Educación a DistanciaFederación Española de Enfermedades RarasUniversity of TorontoAalborg UniversitetAgencia Estatal de InvestigaciónMinisterio de Ciencia, Innovación y Universidades
KeywordsVolume of fluid methodMechanicsContact angleWettingDrop (telecommunication)Solid surfaceDrop impactReynolds numberMaterials scienceHysteresisSimulationComputer sciencePhysicsMechanical engineeringEngineeringBreakup

Abstract

fetched live from OpenAlex

Characterizing the contact line dynamics on solid walls is often a crucial problem encountered in the simulation of complex interfacial unsteady flows, such as drop impacts on solid surfaces. In this work, a new model is proposed to reproduce the contact line dynamics in a simple but effective way, based on introducing in the momentum equation a force term proportional to the deviation of the calculated contact angle from the value predicted by a dynamic model that takes into account wettability hysteresis. The model has been implemented in a volume of fluid (VOF) method and is applied to the simulation of drop impacts leading to deposition outcomes, although it could be extended to other interface tracking methods and is also applicable to more complex drop impacts involving fingering and splashing. Numerous tests have been performed to evaluate the accuracy and robustness of the proposed model over a wide range of Reynolds and Weber numbers. The results substantially improve those obtained by imposing only the contact angle as a boundary condition at the contact line, and satisfactorily predict a variety of experimental results from the literature for very different impact and wettability conditions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score0.535

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 head0.051
GPT teacher head0.339
Teacher spread0.288 · 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 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

Citations10
Published2023
Admission routes2
Has abstractyes

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