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Record W4293213652 · doi:10.3390/w14172590

The Crucial Importance of Air Valve Characterization to the Transient Response of Pipeline Systems

2022· article· en· W4293213652 on OpenAlexaff
Elias Tasca, Bryan Karney, Vicente S. Fuertes-Miquel, José Gilberto Dalfré Filho, Edevar Luvizotto

Bibliographic record

VenueWater · 2022
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Toronto
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsInflowOutflowTransient (computer programming)Reliability (semiconductor)Flow (mathematics)Consistency (knowledge bases)Environmental sciencePipeline (software)Upstream (networking)Isentropic processComputer scienceMechanicsSimulationMarine engineeringMeteorologyEngineeringMechanical engineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Air valves are often crucial components in an air management strategy for pressurized water conveyance systems. However, the reliability of characteristic curves of air valves found in product catalogs is quite variable. This paper evaluates the consistency of a selection of product curves to basic air flow principles. Several recurring issues are identified: catalogs that present identical curves for admission and expulsion (they are, in fact, quite distinct); admission curves that are inconsistent with the isentropic inflow model; inflow (admission) curves actually consistent with the shape of the isentropic outflow model; limited validity curves that encompass only part of the subsonic flow regimen; and unclear or unstated specifications regarding the conditions under which the characterization tests were performed or their results displayed. To examine the significance of these representational issues related to air valve capacity on system behaviour, this paper uses a case study involving the simulated transient response arising from a pump trip at the upstream end of a rising water line having a distinct high point fitted with an air valve. It is found that employing inaccurate air valve characteristics in a transient simulation may potentially result in appreciable or even dangerous simulation errors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.180
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2022
Admission routes1
Has abstractyes

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