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Record W2076384373 · doi:10.2166/wst.2006.877

Optimal performance of an immersed membrane bioreactor equipped with a draft tube for domestic wastewater reclamation

2006· article· en· W2076384373 on OpenAlexaboutno aff
Fei Yang, Amos Bick, S. Shandalov, Gideon Oron

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMembrane foulingDraft tubeFoulingAerationMembrane bioreactorMembraneEnvironmental engineeringWastewaterEnvironmental scienceBioreactorHollow fiber membraneChemistryWaste managementPulp and paper industryEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

One of the options to prevent membrane fouling is to implement air lifting that can improve the cake removal from the membrane surface. This study presents the results of tests that were carried out at the Institutes for Desert Research, Kiryat Sde-Boker, Israel, and focused on the influence of hydrodynamic conditions on fouling in a pilot-scale immersed membrane bioreactor (IMBR) using a hollow fiber membrane module of ZW-10 (Zenon Environmental, Canada) under ambient conditions. In this system, the cross-flow velocities across the membrane surface were induced by one conical and four cylindrical draft-tubes. The relationship between the crossflow velocity and the aeration intensity, the influence of the crossflow on fouling rate under various hydrodynamic conditions were investigated and optimal operating conditions were obtained. Optimal operating conditions were reached during the long-term experiment period (70 days) for the treatment of domestic wastewater. The system was stable without external chemical cleaning. The results showed that the permeate was of high quality, and the removal of COD and BOD was 94.0% and 98.8%, respectively. The crossflow near the membrane surface reveals a major contribution for minimizing membrane fouling, and could offer guidelines for future design of similar systems.

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 categoriesScience and technology studies
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 score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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.

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

Citations9
Published2006
Admission routes1
Has abstractyes

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