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Record W4391351581 · doi:10.2175/193864718825159068

Dynamic Process Modelling for Aeration Blower Design at the Humber Treatment Plant

2023· article· en· W4391351581 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the Water Environment Federation · 2023
Typearticle
Languageen
FieldMathematics
TopicModeling, Simulation, and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsAerationProcess (computing)Process designProcess engineeringComputer scienceEnvironmental scienceEngineeringWaste managementProcess integration

Abstract

fetched live from OpenAlex

Dynamic Process Modelling for Aeration Blower Design at the Humber Treatment PlantAbstractThe City of Toronto initiated a design and construction project in 2022 to replace the existing secondary treatment aeration blowers at the Humber Treatment Plant. A comprehensive review of historical flow and plant operating data was conducted to derive a design-year hourly diurnal flow and load profile (8,760 discrete data points) for input into a commercial wastewater process simulation tool. The output oxygen demands were used to generate process airflows considering varying wastewater temperatures, standard oxygen transfer efficiency based on net airflow per diffuser and diffuser depth, and dynamic alpha based on aeration basin oxygen uptake rates at each time step in the flow and load profile. Statistical and seasonal analyses were applied to the resulting airflow data sets to determine performance guarantee points at varying inlet air conditions for blower equipment preselectionThe City of Toronto initiated a capital project in 2022 to replace the existing secondary treatment aeration blowers at the Humber Treatment Plant. A comprehensive approach was implemented to develop the process design basis for the new aeration blowers using dynamic wastewater treatment process modelling to derive process airflows for a one-year hourly diurnal flow and load profile. Resulting airflows were used to determine performance guarantee points at varying inlet air conditions.SpeakerRizzuti, DanielPresentation time08:30:0009:00:00Session time08:30:0010:00:00SessionThe Big Bad Blower: Huffing and Puffing Air Through Your Aeration BasinsSession locationRoom S401d - Level 4TopicEnergy Production, Conservation, and Management, Facility Operations and Maintenance, Intermediate Level, Municipal Wastewater Treatment DesignTopicEnergy Production, Conservation, and Management, Facility Operations and Maintenance, Intermediate Level, Municipal Wastewater Treatment DesignAuthor(s)Rizzuti, DanielAuthor(s)D. Rizzuti 1; J. Kraemer 2 ; Pretorius 3; T. Young 4; T. Gretarsson 5; D. Pease 6; T. Shen 7; E. Eini 8; V. Szonda 6; D. Rizzuti 1;Author affiliation(s)GHD Ltd., Waterloo, ON 1; GHD Ltd., Waterloo, ON 2 ; GHD 3; GHD 4; GHD 5; City of Toronto, ON 6; City of Toronto, ON 7; City of Toronto, ON 8; City of Toronto, ON 6; GHD 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159068Volume / Issue Content sourceWEFTECCopyright2023Word count13

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.553

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 studies0.0010.000
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 head0.064
GPT teacher head0.271
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