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Record W2804142046 · doi:10.2166/wst.2005.0033

Experimental abatement data of underflow baffles for removal of floatables in the CSOs of the Greater Montréal (Canada) area

2005· article· en· W2804142046 on OpenAlexaboutno aff
J. Cigana, Martin Couture

Bibliographic record

VenueWater Science & Technology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsArithmetic underflowBaffleClarifierEnvironmental scienceFlow (mathematics)Combined sewerReynolds numberEngineeringEnvironmental engineeringHydrology (agriculture)Geotechnical engineeringMechanicsComputer scienceMechanical engineeringStormwaterPhysicsTurbulenceEcology

Abstract

fetched live from OpenAlex

Underflow baffles have gained in popularity over the years as a viable mean to intercept floatables in Combined Sewer Overflows (CSOs). This choice was mainly justified by the extremely low capital cost (CAPEX) and operational cost (OPEX) of this solution, although the efficiency of underflow baffles has never been clearly proven. The only similar application to underflow baffles are scum boards in grit chambers and clarifier. However, the flow conditions at CSOs vary considerably from those in grit chambers and clarifier. For this reason, review of the behavior of floatables in a rapid flow is paramount. Only then can comprehensive design criteria for underflow baffles and overflow chambers be suggested. Pilot scale tests, performed in a 17 metres long basin at various flowrates, had already shown that a critical horizontal velocity for floatables (Vcr) may develop in the overflow chambers. In this follow up study, the fate of intercepted floatables was investigated. It appears from this latest data that permanent capture of floatables decreases rapidly with an increase in the horizontal velocity of the flow, no matter what the baffle depth. Baffle depth increases capture at lower velocities (0.17 m/s) but become irrelevant at higher velocities (0.61 m/s). This data suggests that capture efficiency of existing underflow baffles in overflow chambers can be, at best, very low whenever the horizontal velocity increases above 0.30 m/s or 1 ft/s.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.002
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 head0.031
GPT teacher head0.235
Teacher spread0.205 · 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 designBench or experimental
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

Citations3
Published2005
Admission routes1
Has abstractyes

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