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Record W2036985034 · doi:10.1139/s06-005

Residence time distribution analysis of an intermittently operating truck fill facility to determine effective contact time

2006· article· en· W2036985034 on OpenAlexvenueno aff
Clark Svrcek, R. Guest, Daniel Smith

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2006
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsnot available
FundersU.S. Environmental Protection Agency
KeywordsTruckResidence time distributionResidence time (fluid dynamics)Environmental scienceResidenceScheduleTransport engineeringEnvironmental engineeringFlow (mathematics)Waste managementEngineeringComputer scienceAutomotive engineeringMathematics

Abstract

fetched live from OpenAlex

Two tracer studies were performed on a First Nations water treatment plant (WTP) reservoir in order to determine the reactor mixing pattern as well as the effective contact time, or t 10 , value. A unique characteristic of the reservoir in question was that the major outlet from the tank was a truck fill station that operated intermittently throughout the day as water haul trucks filled up for delivery. Almost three times the flowrate was removed as was added, and coupled with the undersized reservoir resulted in major short-circuiting in the unbaffled contact chamber. The reservoir showed an almost ideal completely mixed flow regime, and the lowest t 10 value determined from 2 days of testing was 14 min, much lower than what was required for chlorine Ct compliance. The residence time distribution curves also showed a unique step shape that resulted from the intermittent operation of the truck fill. With the introduction of a lagged time factor a generalized approach for analysis of existing truck fills and the design of new facilities was developed using easily quantifiable variables. An alternative approach for the design of new truck fill facilities was also provided and is somewhat more conservative than the lagged time factor method but allows for a more flexible water delivery schedule. Given the prevalence of truck fill stations in northern communities and the upcoming need for infrastructure upgrades to comply with new standards and guidelines this approach will help ensure the continued protection of public health through the potable water system. Key words: truck fill, residence time distribution, Ct concept, tracer study, water treatment facility design, public health.

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 score0.300
Threshold uncertainty score0.336

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 head0.002
GPT teacher head0.168
Teacher spread0.166 · 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
Published2006
Admission routes1
Has abstractyes

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