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Record W4255031183 · doi:10.22215/etd/2014-10069

Particulate Deposition Prediction of Diluted Two-Phase Impinging Jet

2014· dissertation· en· W4255031183 on OpenAlexaff
Eid Alatawi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsCarleton University
FundersKing Abdulaziz City for Science and Technology
KeywordsReynolds-averaged Navier–Stokes equationsMechanicsLarge eddy simulationParticle depositionJet (fluid)Reynolds stressDeposition (geology)TurbulenceComputational fluid dynamicsLagrangian particle trackingParticle (ecology)Shear stressFlow (mathematics)Reynolds numberMaterials sciencePhysicsGeology

Abstract

fetched live from OpenAlex

Insights into particle transport and deposition process in impinging jet flow, in light of the available experiments, can be gained using computational fluid dynamics (CFD) numerical simulations. The present thesis focuses mainly on the prediction of aerosol particle transport and deposition in impinging jet flow. An extensive literature survey has indicated that the present work represents the first comprehensive investigation of aerosol particle transport and deposition, using Reynolds averaged Navier Stokes/eddy interaction model (RANS/EIM) along with near-wall corrections, and large eddy simulation (LES) numerical approaches applied to particle-laden impinging jet flow.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.976

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 head0.008
GPT teacher head0.259
Teacher spread0.251 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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