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Record W591984257 · doi:10.2166/wpt.2015.038

Current status of the rotating belt filtration (RBF) technology for municipal wastewater treatment

2015· article· en· W591984257 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Practice & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsTrojan Technologies (Canada)
Fundersnot available
KeywordsTotal suspended solidsSuspended solidsEffluentTotal dissolved solidsFiltration (mathematics)WastewaterCloggingMixed liquor suspended solidsSettlingEnvironmental scienceEnvironmental engineeringAerationVolatile suspended solidsWaste managementBiofilterEngineeringChemical oxygen demandActivated sludgeMathematics

Abstract

fetched live from OpenAlex

Rotating belt filtration (RBF) is a technology designed for the removal of suspended solids, and effluent organic matter from wastewater that has been recently undergoing intensive development and testing. Generally, RBF can remove solids to meet Ten State Standards (‘Primary settling of normal domestic wastewater can be expected to remove approximately one-third of the influent BOD5 when operating at an overflow rate of 41 m3/(m2 d) [1,000 gallons per day/square foot]’) and European council directive standards (at least 50% total suspended solids (TSS) and 20% Biological Oxygen Demand (BOD) removal). Recent testing have also shown that, when a polymer is added upstream of the RBF, solids and organics removal is significantly enhanced. Advantages of RBF include reduced space requirement, ability to support small mesh without clogging, reduced civil engineering site work, and modular construction allowing for reduced design work, faster installation, and ease of plant expansion. Additional site-specific advantages may include reduced capital and operation costs, and energy savings (e.g. reduced aeration costs following the addition of primary solids removal by RBF against the baseline case where primary solids removal is not practiced). As a matter of fact, when RBF is operated as a pretreatment to remove 50% of the incoming TSS prior to the biological aerated tank, a significant decrease in power consumption ranging from 22 to 28% can be expected if compared to the case where no primary treatment is used. This paper focuses on the current status of development of the technology and provides a literature review of recent experimental studies focused on testing RBF.

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.

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)0.001
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 score0.267
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.041
GPT teacher head0.315
Teacher spread0.274 · 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