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Record W2341066807 · doi:10.2166/wst.2015.321

Evaluation of flow hydrodynamics in a pilot-scale dissolved air flotation tank: a comparison between CFD and experimental measurements

2015· article· en· W2341066807 on OpenAlexaff
B. Lakghomi, Yuri Lawryshyn, Ron Hofmann

Bibliographic record

VenueWater Science & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputational fluid dynamicsDissolved air flotationBubbleMechanicsFlow (mathematics)Particle (ecology)SCALE-UPResidence time (fluid dynamics)Multiphase flowResidence time distributionWork (physics)Environmental scienceCFD-DEMPhase (matter)ChemistryEngineeringEnvironmental engineeringMechanical engineeringGeotechnical engineeringGeologyPhysics

Abstract

fetched live from OpenAlex

Computational fluid dynamics (CFD) models of dissolved air flotation (DAF) have shown formation of stratified flow (back and forth horizontal flow layers at the top of the separation zone) and its impact on improved DAF efficiency. However, there has been a lack of experimental validation of CFD predictions, especially in the presence of solid particles. In this work, for the first time, both two-phase (air-water) and three-phase (air-water-solid particles) CFD models were evaluated at pilot scale using measurements of residence time distribution, bubble layer position and bubble-particle contact efficiency. The pilot-scale results confirmed the accuracy of the CFD model for both two-phase and three-phase flows, but showed that the accuracy of the three-phase CFD model would partly depend on the estimation of bubble-particle attachment efficiency.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.079
GPT teacher head0.339
Teacher spread0.260 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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