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Record W2317938918 · doi:10.1061/41203(425)51

An Unsteady Optimization Algorithm for Water Distribution Systems Including Hydraulics and Water Quality Criteria

2011· article· en· W2317938918 on OpenAlexaff
Gholamreza Naser, Bernhard Jung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsHydraulicsTurbidityMechanicsFlow (mathematics)Pipeline (software)Water flowParticle swarm optimizationTurbulenceMomentum (technical analysis)GridPipeline transportSurgeWater qualityTransient (computer programming)Computer scienceEnvironmental scienceEngineeringAlgorithmMathematicsGeotechnical engineeringPhysicsMeteorologyMechanical engineeringGeologyThermodynamicsGeometry

Abstract

fetched live from OpenAlex

This research aimed in at least a preliminary way to simulate and approximate red water events in a water pipeline system. An abrupt change in flow regime creates an aggressive shear force, sometimes causing the deposited particles at the pipe wall to be re-suspended and carried with the bulk flow. In this study, a one-dimensional (1-D) transient simulation model is proposed, by which the turbidity of water is modeled with a transport equation, which is then coupled with the continuity and momentum equations for flow. Using the Taylor's turbulence model, an implicit/explicit finite difference model (FDM) is superposed with a fixed grid method of characteristics (MOC) to numerically integrate the governing equations for the unknown flow parameters including water turbidity. The research applied Boxall's approach to determine the water turbidity in the system. The study presented the particle swam optimization (PSO) technique to calibrate the parameters in Boxall's approach. Finally, the model's results for a reservoir-pipe-valve system were compared with the available field data reported in the literature by other researchers. The overall agreement of the two sets of results supports the basic validity of the proposed 1-D model.

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: none
Teacher disagreement score0.946
Threshold uncertainty score0.433

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)0.0000.000

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 head0.045
GPT teacher head0.265
Teacher spread0.220 · 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
Published2011
Admission routes1
Has abstractyes

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