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Record W2606850579 · doi:10.2166/wqrj.2017.023

A computational fluid dynamics analysis of placing UV reactors in series

2015· article· en· W2606850579 on OpenAlexafffund
Patrick C. Young, Yuri Lawryshyn

Bibliographic record

VenueWater Quality Research Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoNational Water Research Institute
KeywordsUltravioletWastewaterReactor designUltraviolet radiationWater disinfectionSeries (stratigraphy)Additive functionChemistryBiological systemNuclear engineeringBiochemical engineeringEnvironmental scienceEnvironmental engineeringMaterials scienceRadiochemistryMathematicsEngineeringOptoelectronicsBiology

Abstract

fetched live from OpenAlex

Ultraviolet (UV) light water treatment reactors are commonly used in both wastewater and drinking water disinfection. UV technology can effectively inactivate a large number of pathogens at low UV doses, however adenovirus requires a substantially higher dose than most pathogens of interest. In order to meet adenovirus inactivation requirements, UV reactors are often placed in series and the total inactivation is calculated as the sum of the reactors' individual UV doses. In this paper, it is shown that this simple summation treatment of UV dose may be acceptable. A parameter called the reactor additivity factor is introduced to properly characterize the interaction between UV reactors in series. Three types of UV reactors are modelled using computational fluid dynamics, and their RAFs are computed. The validity of reactor additivity in practice in wastewater and drinking water systems is discussed.

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)0.007
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.446
Teacher spread0.289 · 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 designObservational
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
Published2015
Admission routes2
Has abstractyes

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