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Record W2968818053

Performance Modelling of Etobicoke Exfiltration System (EES)

2018· article· en· W2968818053 on OpenAlexaboutno aff
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Bibliographic record

VenueWDSA / CCWI Joint Conference Proceedings · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsStormwaterSanitary sewerEnvironmental scienceCombined sewerStorm Water Management ModelStormSurface runoffStormwater managementLow-impact developmentHydrology (agriculture)Civil engineeringEnvironmental engineeringEngineeringMeteorology
DOInot available

Abstract

fetched live from OpenAlex

The Etobicoke Exfiltration System (EES), a stormwater conveyance system best management practice, involves small modifications to the conventional storm sewer system design. In an effort to better quantify performance through modelling, this paper presents a methodology that was used to implement EES in the USEPA SWMM modelling framework and the result of applying the methodology on a case study. Key EES components, including the inlets, storage provided by sewer void space of the granular material in the sewer trench and the exfiltration from the trench into the soil, were modelled orifice, storage and pump components. The resulting methodology was applied to model a hypothetical EES retrofit in a 10.50 ha existing residential development serviced with conventional storm sewers and a pond. The results of continuous simulations show that the retrofit results in a significant reduction of runoff volume, water balance that approaches the predevelopment conditions, and drastic changes in flow-duration characteristics. The EES retrofit also results in significant peak flow reductions in response to design storm events, and improved system performance when subjected to precipitation loads modified by climate change.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.049
GPT teacher head0.200
Teacher spread0.152 · 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.

Study designSimulation or modeling
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

Citations0
Published2018
Admission routes1
Has abstractyes

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