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Record W1964109845 · doi:10.1061/40792(173)137

Modeling and Evaluating Temperature Dynamics in Wastewater Treatment Plants

2005· article· en· W1964109845 on OpenAlexaboutno aff
Scott A. Wells, Dmitriy Bashkatov, Jacek Mąkinia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentEnvironmental scienceDew pointSewage treatmentWastewaterAerationWind speedEnvironmental engineeringDewAir temperatureSecondary treatmentMeteorologyWaste managementEngineeringGeography

Abstract

fetched live from OpenAlex

With new government regulations governing the discharge of heated effluents into receiving waters, there is much interest in providing a model of temperature dynamics in wastewater treatment plants (WWTP). This type of model would allow operators to evaluate alternatives for reducing effluent temperatures, such as covering secondary clarifiers. This type of tool would also be of use to demonstrate the difficulty in some installations of affecting effluent temperatures. A model of temperature in a WWTP was developed and tested at a facility in Vancouver, Washington during both summer and winter conditions. Temperatures were taken at 6 control points throughout the treatment plant and used as a basis for model calibration and evaluation. Meteorological data such as air temperature, dew point temperature, wind speed and direction and solar radiation were obtained from nearby weather station. The impacts of the discharge on the Columbia River were also discussed. Also, the basic model was tested in an aeration model using detailed temperature data from a Washington County, Oregon, USA wastewater treatment facility.

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 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 score0.487
Threshold uncertainty score0.272

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 head0.042
GPT teacher head0.293
Teacher spread0.251 · 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 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
Published2005
Admission routes1
Has abstractyes

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