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Record W4285491828 · doi:10.2166/9781780409030

CFD Modelling for Wastewater Treatment Processes

2022· book· en· W4285491828 on OpenAlex
Julien Laurent, Randal Samstag, Ingmar Nopens, Edward Wicklein, Rainier Hreiz, Damien J. Batstone, Anna M. Karpinska Portela, Usman Rehman, Tewodros Meless Teshome, Alonso Griborio, Maria Elena Valle-Medina, Ed Wicklein, Christopher T. DeGroot, Stephen Saunders, David Fernandes del Pozo, Yang Min, Olivier Potier

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.

Bibliographic record

VenueIWA Publishing eBooks · 2022
Typebook
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsIBI Group (Canada)Western University
Fundersnot available
KeywordsComputational fluid dynamicsProcess (computing)Scale (ratio)Fluid mechanicsResource (disambiguation)EngineeringComputer scienceMechanicsAerospace engineering

Abstract

fetched live from OpenAlex

Abstract This Scientific and Technical Report (STR) provides in-depth fundamentals and guidelines regarding Computational Fluid Dynamics (CFD) simulations of Water Resources Recovery Facilities (WRRFs) unit processes (e.g. headworks, aerobic and anaerobic biological reactors, settling tanks, disinfection). Each unit process is described with respect to: Literature review and process descriptionRelevant CFD concepts and modelling approachCase studiesFuture research needs CFD Modelling for Wastewater Treatment Processes also opens the discussion on two fundamental topics: experimental validation of CFD simulations, and the complementarity between CFD and Chemical Reaction Engineering approaches. This book is intended for undergraduate and graduate students majoring in fields related to wastewater treatment and/or fluid mechanics, as well as researchers and engineers who conduct research and practices in modelling such unit processes. Water resource recovery modelling is not just about lab-scale processes. Now and in the future it is about improving our understanding of (and designing better) full-scale facilities!

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 categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.223
Teacher spread0.186 · 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