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Record W4323667522 · doi:10.1080/1573062x.2023.2183136

Stormwater treatment using an ultrafiltration membrane and pulsatile fluid flow

2023· article· en· W4323667522 on OpenAlexaboutno aff
Saida Kaykhaii, Inga Herrmann, Annelie Hedström, Kerstin Nordqvist, Maria Viklander

Bibliographic record

VenueUrban Water Journal · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersVetenskapsrådetVINNOVA
KeywordsUltrafiltration (renal)Environmental scienceStormwaterTurbidityMembraneEnvironmental engineeringSuspended solidsSedimentationTotal suspended solidsMembrane foulingProductivityChemistryChromatographySewage treatmentFoulingChemical oxygen demandSedimentWastewaterGeologySurface runoff

Abstract

fetched live from OpenAlex

A polymeric ultrafiltration (UF) membrane was used for stormwater treatment, with the focus on evaluating the increase in the membrane process productivity by adding pulsatile fluid flow to UF membrane treatment. Sedimentation and sieving were used as pre-treatment. The result showed that increasing the pulse frequency from 0 to 4 Hz increased productivity from −6.6 to 82 LMH. UF membrane removed suspended solids, oil and turbidity below detection limit. The UF membrane also separated total coliforms, E. coli and P. aeruginosa below detection limit. Total organic carbon (TOC) was reduced by between 81%, in average. In addition, the UF membrane was able to reduce BOD7 and COD to below 7 mg/L in the permeate. According to the US EPA, WHO, and national regulations in Canada, Japan, and South Korea, treated stormwater can be used for flushing toilets and streets irrigation and agricultural use.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.032
GPT teacher head0.237
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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

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