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Record W1964205861 · doi:10.1115/fedsm2005-77011

Effect of Particulate Diffusion on the Free Turbulent Flow Based on Two-Fluid

2005· article· en· W1964205861 on OpenAlexaff
R. Fesanghari, Hassan Basirat Tabrizi, Feridun Hamdullahpur

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsCarleton University
Fundersnot available
KeywordsMechanicsTurbulenceTurbulent diffusionDragFinite volume methodParticle (ecology)DiffusionThermal diffusivityMaterials scienceTurbulence modelingMixing (physics)Flow (mathematics)ViscosityThermodynamicsPhysics

Abstract

fetched live from OpenAlex

This paper is concerned with the two-dimensional gas-solid turbulent plane-mixing layer. The solid phase is considered a continuum and a two-fluid model, which is coupled by source terms due to particle drag and diffusion. Finite volume scheme has been employed for the governing equations. The simulation results show that the ratio of particle diffusion coefficient and kinematics viscosity of the carrier gas, have significant influence on the prediction of particles trend. In addition, it is observed that the loading ratio has no significant effect on the gas-solid flow prediction. The results are compared with the existed experimental data’s of others. This kind of modeling will ease the time consuming, stochastic approach of the Eulearian-Lagrangian methods but needs further investigation on the particle diffusivity term.

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: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.464

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 head0.005
GPT teacher head0.215
Teacher spread0.209 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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