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Record W2618863334 · doi:10.2166/wst.2017.315

Dewatering optimization with in-line and real-time measurement of polymer: results from full-scale treatment plants

2017· article· en· W2618863334 on OpenAlexaff
Banu Örmeci, Richard DiMassimo

Bibliographic record

VenueWater Science & Technology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsAbsorbanceDewateringPolymerTurbidityResidualMaterials scienceChromatographyPulp and paper industryChemistryComposite materialMathematicsEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Full-scale testing was carried out at two wastewater treatment plants to determine whether residual polymer concentration, measured by filtrate and centrate absorbance at 191 nm, can be used to identify the optimum polymer dose and achieve in-line and real-time dewatering optimization. The first plant uses high speed centrifuges and the second plant uses belt filter presses for dewatering. During the testing, the polymer dose incrementally increased to cover the under-dose, optimum dose and over-dose polymer ranges, and the centrate/filtrate absorbance at 191 nm, turbidity and cake solids were measured. The results showed that absorbance measurements at 191 nm exhibited a parabolic shaped curve with increasing polymer dose, where the minimum absorbance corresponded to the optimum polymer dose. The method can directly measure the residual polymer concentration and determine the optimum polymer dose accordingly, and is planned to be used in the development of a dewatering automation system in the future.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.426

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 studies0.0000.001
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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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