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Record W4402128569 · doi:10.1080/1573062x.2024.2397783

Adaptative water quality management in water distribution systems by optimizing control valves and chlorination booster stations

2024· article· en· W4402128569 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueUrban Water Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBooster (rocketry)ChlorineEnvironmental scienceEnvironmental engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

Good water quality in a water distribution system (WDS) can be reached by using flow control valves (FCV) to reduce water residence time (WRT), and chlorine booster stations to maintain acceptable free residual chlorine concentrations (FRCC). The research developed a cost-effective, adaptative approach for managing FCV and chlorine booster stations, while maintaining acceptable pressure and FRCC ranges. The methodology is applied to a real full-scale case study considering three optimization formulations: 1) FCV operation, 2) chlorine booster station operation, and 3) combining them in an adaptive management strategy. Results revealed that chlorine booster stations individually or combined with FCV enhanced water quality significantly at an acceptable cost, while FCV optimization alone or combined with chlorine booster stations reduced WRT by, at most, 3.8%. Chlorine booster stations were thus more effective than FCV in this case study. This formulation can be applied to other WDS to improve water quality cost-effectively.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.635
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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