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Record W2010253430 · doi:10.1002/cjce.5450820201

Turbulence Modulation in Gas‐Particle Flows: A Comparison of Selected Models

2004· article· en· W2010253430 on OpenAlexaffvenue
Marilyn Lightstone, Sarah M. Hodgson

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTurbulenceModulation (music)K-epsilon turbulence modelK-omega turbulence modelMechanicsPhysicsParticle (ecology)Flow (mathematics)Turbulence modelingStatistical physicsGeology

Abstract

fetched live from OpenAlex

Abstract The problem of turbulence modulation, the process whereby the gas‐phase turbulence is modified by the presence of particles, is investigated. Experimental trends are examined and parameters affecting turbulence modulation and the mechanisms by which turbulence modulation occurs are identified. A new model that accounts for the crossing trajectory effect through fluid velocity correlations is presented. This model and the turbulence modulation models of Chen and Wood (1985), Tu and Fletcher (1994), and Mostafa and Mongia (1988) are compared directly to determine inherent differences or similarities of the models. The models are also invoked to simulate a particle‐laden pipe flow and predictions are compared to the experimental results of Tsuji et al. (1984).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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

Citations40
Published2004
Admission routes2
Has abstractyes

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