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Record W1987667635 · doi:10.2166/wst.2007.370

Modeling of anaerobic treatment of wastewater in ponds

2007· article· en· W1987667635 on OpenAlexaff
B.K. Rajbhandari, Ajit P. Annachhatre, J.L. Vasel

Bibliographic record

VenueWater Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMethanogenesisSedimentSettlingOrganic matterParticulatesWastewaterEnvironmental scienceAnaerobic digestionAnaerobic exerciseAnaerobic respirationEnvironmental chemistryEnvironmental engineeringChemistryGeologyMethaneBiology

Abstract

fetched live from OpenAlex

A mathematical model to simulate the performance of anaerobic ponds was developed incorporating both settling of particulate components and the biological anaerobic digestion process. The biological activity includes solubilization of particulate organic matter; methanogenesis and the sulphate reduction process. The model considers that an anaerobic pond comprises a series of equal size columns. Each column has three compartments viz. liquid layer, active sediment layer and inert sediment layer. The existence of organic matter and sulphate removal mechanisms both in the bulk as well as sediment layer of the ponds and the exchange of the soluble components between the layers has been included in the model. The model was transferred to a computer program using VisSim Basic software. The model was verified by comparing simulated results with full-scale as well as with laboratory-scale anaerobic pond performance data. A good agreement between the simulated and the observed pond performance was achieved.

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 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 score0.015
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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