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Record W4410496029 · doi:10.1063/5.0268281

Coupled phase-field lattice Boltzmann method and discrete element method for gas–liquid–solid multiphase flows

2025· article· en· W4410496029 on OpenAlexaff
Linlin Fei, Kai Luo, Hong Liang, Xitong Zhang, Dominique Derome, Jan Carmeliet

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversité de Sherbrooke
FundersChina Scholarship Council
KeywordsPhysicsLattice Boltzmann methodsMultiphase flowHPP modelMechanicsDiscrete element methodLattice (music)Statistical physicsTwo-phase flowCondensed matter physicsFlow (mathematics)

Abstract

fetched live from OpenAlex

A methodology combining the lattice Boltzmann method (LBM) and discrete element method (DEM) is proposed to simulate gas–liquid–solid multiphase flows and interphase interactions. Specifically, the phase-field LBM is employed to simulate the fluid flow, incorporating the virtual density boundary method. This method effectively enables the realization of wetting phenomena with relatively small spurious velocities, in comparison with the pseudopotential LBM. The DEM is utilized to simulate the motion of multiple solid particles. As for the interaction between fluid and solid, leveraging the features of LBM, the calculation of fluid forces acting on solids can be achieved by going through all fluid nodes surrounding the solid walls, enabling a straightforward and efficient calculation process. The numerical stability and accuracy of the hybrid LBM-DEM are demonstrated via benchmark cases. It is then applied successfully to simulate the upward migration of leaked gas bubbles through a deformable porous medium composed of solid particles.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.364
Teacher spread0.340 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations3
Published2025
Admission routes1
Has abstractyes

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