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Record W2126860818 · doi:10.1142/s0129183108012571

MULTI-RELAXATION TIME LATTICE BOLTZMANN MODEL FOR MULTIPHASE FLOWS

2008· article· en· W2126860818 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Modern Physics C · 2008
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of Calgary
FundersChapman UniversityUniversity of Calgary
KeywordsLattice Boltzmann methodsStatistical physicsRelaxation (psychology)IsotropyCollisionMechanicsPhysicsStability (learning theory)Kinetic energyOperator (biology)Bhatnagar–Gross–Krook operatorComputer scienceClassical mechanicsHPP modelChemistryOptics

Abstract

fetched live from OpenAlex

Multi-relaxation time (MRT) for Lattice Boltzmann method is gaining renewed attention among researchers in the field. The advantage of such formulation over the widely popular single-time relaxation version, is twofold: better numerical stability and wider span of physical applications, extending to non-isotropic flows. In this work, the numerical advantages of the MRT model versus single-relaxation time (BGK) operator are quantitatively assessed through direct numerical simulations of droplet formation and capillary wave propagation on interphase boundaries. The results show that by proper tuning of the collision operator, and particularly of the higher-order kinetic modes (ghosts), appreciable improvements in stability limits, of the order of 20%, and viscosity limits, of the order of 80%, can be achieved. Moreover, a theoretical analysis accounting for the reasons behind such stability improvement, is also presented.

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.

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 score0.781
Threshold uncertainty score0.673

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 communication0.0000.001
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 head0.045
GPT teacher head0.290
Teacher spread0.245 · 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