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Record W1972697216 · doi:10.1080/09593330.2011.568974

Application of the International Water Association activated sludge models to describe aerobic sludge digestion

2011· article· en· W1972697216 on OpenAlexaff
Maryam Ghorbani, Çiğdem Eskicioğlu

Bibliographic record

VenueEnvironmental Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMixed liquor suspended solidsVolatile suspended solidsActivated sludge modelTotal suspended solidsActivated sludgeChemical oxygen demandEffluentSuspended solidsChemistryAerobic digestionEnvironmental scienceSequencing batch reactorPulp and paper industryAnaerobic digestionEnvironmental engineeringWaste managementWastewaterEngineeringMethane

Abstract

fetched live from OpenAlex

Batch and semi-continuous flow aerobic digesters were used to stabilize thickened waste-activated sludge at different initial conditions and mean solids retention times. Under dynamic conditions, total suspended solids, volatile suspended solids (VSS) and total and particulate chemical oxygen demand (COD and PCOD) were monitored in the batch reactors and effluent from the semi-continuous flow reactors. Activated Sludge Model (ASM) no. 1 and ASM no. 3 were applied to measured data (calibration data set) to evaluate the consistency and performances of models at different flow regimes for digester COD and VSS modelling. The results indicated that both ASM1 and ASM3 predicted digester COD, VSS and PCOD concentrations well (R2, Ra2 > or = 0.93). Parameter estimation concluded that compared to ASM1, ASM3 parameters were more consistent across different batch and semi-continuous flow runs with different operating conditions. Model validation on a data set independent from the calibration data successfully predicted digester COD (R2 = 0.88) and VSS (R2 = 0.94) concentrations by ASM3, while ASM1 overestimated both reactor COD (R2 = 0.74) and VSS concentrations (R2 = 0.79) after 15 days of aerobic batch digestion.

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 score0.063
Threshold uncertainty score0.810

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)0.0010.001

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 head0.186
Teacher spread0.173 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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