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Record W1801256887 · doi:10.1139/s03-013

Improved sludge dewatering by addition of electro-osmosis to belt filter press

2003· article· en· W1801256887 on OpenAlexvenueno aff
Sunju Hwang

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
Fundersnot available
KeywordsDewateringPulp and paper industryBackwashingOsmosisFilter (signal processing)Water treatmentChemistryFilter cakeEnvironmental scienceWaste managementSewage treatmentFilter pressEnvironmental engineeringMembraneEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Gravity-thickened sludge (GTS) and anaerobically-digested sludge (ADS) from a wastewater treatment plant and sludge from drying bed (DBS) from a water treatment plant were dewatered using the pilot-scale electro-osmotic belt filter press (EBFP). The results indicated that the addition of electro-osmosis greatly improved sludge dewaterability, lowering water content (WC) and heavy metal concentration, and increasing heating value. For instance, EBFP produced 56.0% WC for GTS, 58.4% for ADS, and 69.6% for DBS when current density was 41.1, 42.1, and 17.9 A/m 2 , respectively, and a cationic coagulant was dosed at 0.36% on dried solid, 0.46%, and 0.19%, respectively. Without the addition of electricity, the system achieved only 74.3% WC for GTS, 72.8% for ADS, and 74.7% for DBS. Therefore, EBFP would produce a proper cake WC by simply controlling the current density, depending on the destination of dewatered cake such as land application, compost, or incineration. Key words: belt filter press, cake, electro-osmosis, heating value, heavy metal concentration, water content.

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 score0.008
Threshold uncertainty score0.361

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 studies0.0000.000
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 head0.003
GPT teacher head0.165
Teacher spread0.161 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

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