MétaCan
Menu
Back to cohort
Record W2029789666 · doi:10.2166/wst.2007.607

Interaction between control and design of a SHARON reactor: economic considerations in a plant-wide (BSM2) context

2007· article· en· W2029789666 on OpenAlexaff
Eveline I.P. Volcke, Mark C.M. van Loosdrecht, Peter A. Vanrolleghem

Bibliographic record

VenueWater Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAnammoxEffluentContext (archaeology)WastewaterBenchmark (surveying)Sewage treatmentActivated sludgeEnvironmental engineeringEnvironmental scienceWaste managementProcess engineeringEngineeringNitrogenChemistryDenitrification

Abstract

fetched live from OpenAlex

The combined SHARON-Anammox process is a promising technique for nitrogen removal from wastewater streams with high ammonium concentrations. It is typically applied to sludge digestion reject water, in order to relieve the activated sludge tanks, to which this stream is typically recycled. This contribution assesses the impact of the applied control strategy in the SHARON-reactor, both on the effluent quality of the subsequent Anammox reactor as well as on the plant-wide level by means of an operating cost index. Moreover, it is investigated to which extent the usefulness of a certain control strategy depends on the reactor design (volume). A simulation study is carried out using the plant-wide Benchmark Simulation Model no. 2 (BSM2), extended with the SHARON and Anammox processes. The results reveal a discrepancy between optimizing the reject water treatment performance and minimizing plant-wide operating costs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations17
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueWater Science & TechnologySame topicWastewater Treatment and Nitrogen RemovalFrench-language works237,207