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Record W2225718742

Effects of Turbulent Models and Baffle Position on the Hydrodynamics of Settling Tanks

2006· article· en· W2225718742 on OpenAlexaboutno aff
Ali Tamayol, B Firouzabadi

Bibliographic record

VenueScientia Iranica · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsBaffleSettlingTurbulenceMechanicsInletCurvatureFlow (mathematics)CompressibilityGeologyPosition (finance)Computer simulationPhysicsMathematicsThermodynamicsGeometryGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

In this paper, the numerical results of hydrodynamic modeling of primary settling tanks are presented. The flow field is assumed to be incompressible and non-buoyant. The effects of two different types of turbulence model, standard k-varepsilon and RNG, are compared with each other. The effects of an inlet baffle on the hydrodynamics of settling tanks are also studied. Results are obtained for the primary settling tank of the city of Sarnia, Ontario, Canada. The effects of the existence and position of another interior baffle in the settling tanks are also studied. Results in the different parts are compared with experimental and numerical data and showed good agreement. Comparison between two models of turbulence shows that the numerical results of the flow field, especially the streamline curvature, are not the same, in spite of having nearly equal results in the streamwise velocity component.

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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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