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Record W2335107427 · doi:10.1115/ihtc14-22983

Two-Dimensional Simulation of Magnetohydrodynamic Two-Phase Flow in Random Porous Media Using the Lattice Boltzmann Method

2010· article· en· W2335107427 on OpenAlexafffund
Mahshid Hadavand, Aydin Nabovati, António C.M. Sousa

Bibliographic record

Venue2010 14th International Heat Transfer Conference, Volume 6 · 2010
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFerrofluidLattice Boltzmann methodsMagnetic fieldMechanicsPorous mediumMagnetMesoscopic physicsMaterials sciencePhysicsCondensed matter physicsPorosity

Abstract

fetched live from OpenAlex

The present work employs the single relaxation time lattice Boltzmann method along with the pseudo potential model for the two-phase flow simulation of a ferrofluid in a random two-dimensional medium under the influence of a spatially variable external magnetic field. The magnetic field is created and controlled by placing a permanent magnet at the outlet end of the channel filled with a porous medium. The magnitude of the magnetic force acting on the ferrofluid is controlled by changing the distance of the magnet from the channel outlet. The spatially variable magnetic field strength was analytically calculated inside the channel using the available relations in the literature. The main goal of the present work is to qualitatively study the applicability of the single relaxation time (SRT) lattice Boltzmann method (LBM) to modelling flow of a ferrofluid and its steering into porous media. Penetration of the ferrofluid into the porous medium, which is initially filled with a fluid with no magnetic properties, was simulated in time. The simulation results for the flow front are presented and the effect of the magnetic field strength on the rate of flow penetration and front advancement was studied qualitatively. The LBM has proved to be a powerful tool for modelling flows, which involve multi-physics in complex geometries, when mesoscopic inter-particle forces and interaction with external complex forces have to be determined.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.309
Teacher spread0.284 · 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
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

Citations0
Published2010
Admission routes2
Has abstractyes

Explore more

Same venue2010 14th International Heat Transfer Conference, Volume 6Same topicLattice Boltzmann Simulation StudiesFrench-language works237,207