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Modeling Ventilation Phenomenon in Sanitary Sewer Systems: A System Theoretic Approach

2006· article· en· W2038088158 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

VenueJournal of Hydraulic Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSanitary sewerPipingCabin pressurizationEnvironmental engineeringEnvironmental scienceDragSewageCivil engineeringWastewaterCombined sewerEngineeringWaste managementStormwaterSurface runoffMechanical engineering

Abstract

fetched live from OpenAlex

Municipal wastewater collection systems, due to the nature of their functions, carry varying concentrations of odorous gases. The production rate and transport of these gases within and out of sewer systems depend on air flow rate in the system piping. However, municipal sewers are generally designed to only transport sewage flow without giving consideration to the air flow field. As a consequence, the movement of air into, along, and out of collection systems is for the most part uncontrolled. The purpose of this paper therefore is to provide a new design protocol based on system theoretic techniques to be used by municipal engineers and environmentalists involved in odor control and sewer foul air transport studies. The modeling formulation accounts for combined wastewater drag and pressure-induced air flows, and manhole pressurization. The developed framework is applied to both hypothetical and real sewer systems to only illustrate the applicability of the modeling formulation.

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: none
Teacher disagreement score0.772
Threshold uncertainty score0.631

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 studies0.0000.000
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 head0.004
GPT teacher head0.154
Teacher spread0.149 · 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