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Record W2883042497 · doi:10.1002/fld.4673

Multiphase periodic pressure difference boundary condition enhanced by a proportional‐integral‐derivative controller for the lattice Boltzmann method

2018· article· en· W2883042497 on OpenAlexafffund
Sébastien Leclaire, Jonas Lätt, David Vidal, François Bertrand

Bibliographic record

VenueInternational Journal for Numerical Methods in Fluids · 2018
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsBoundary value problemMechanicsLattice Boltzmann methodsMathematicsBoundary (topology)Multiphase flowPressure dropConservation of massMathematical analysisPhysics

Abstract

fetched live from OpenAlex

Summary A new pressure difference boundary condition between a pair of inlet and outlet boundaries in an immiscible multiphase periodic flow is introduced. This boundary condition is globally mass conservative and makes use of a simple proportional‐integral‐derivative controller to accurately control the pressure difference. For a droplet/bubble that crosses the outlet to reenter at the inlet of a periodic slit flow, the stability and accuracy of the boundary condition are numerically studied for a wide range of flow conditions. A visualization of a droplet crossing the outlet boundary provides qualitative evidence that the boundary condition works effectively. More importantly, quantitative results also confirm that the targeted average pressure difference is adequately set and that the total momentum in the pressure drop direction is nearly constant (which is what is expected from a perfect multiphase periodic pressure difference boundary condition). This new type of multiphase boundary condition is expected to open up new avenues to simulate complex interfacial multiphase systems using the lattice Boltzmann method.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.713
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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 science0.0010.000
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 head0.033
GPT teacher head0.419
Teacher spread0.386 · 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
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

Citations4
Published2018
Admission routes2
Has abstractyes

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