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Record W2765489418 · doi:10.1115/pvp2017-65767

Characterization of Flow-Sound-Structure Coupling in Spring-Loaded Valves

2017· article· en· W2765489418 on OpenAlexaff
Salim El Bouzidi, Marwan Hassan, Samir Ziada

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsUniversity of GuelphMcMaster University
Fundersnot available
KeywordsVibrationPipingBernoulli's principleMechanicsFlow (mathematics)Limit cycleAcousticsModal analysisEngineeringStructural engineeringNonlinear systemPhysicsMechanical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate the vibration mechanism of a spring-loaded valve placed in a “push-to-open” configuration in a piping system. A non-linear theoretical model of the valve vibration is developed to describe the interaction mechanisms between the unsteady flow through the valve, the acoustic field in the piping system, and the oscillation of the valve plate. The aim of this phenomenological model is to better understand the main system parameters causing the valve vibration. The model relies on a one-dimensional unsteady Bernoulli representation of the flow and a single degree of freedom model of the valve plate motion with impact conditions at the valve seat and lift limiter. Impact forces are determined through the means of a pseudo-force method. The model is cast in state-space form and solved using a fourth-order Runge-Kutta stencil. The predicted limit cycle amplitudes follow the same trends as experimental findings over the opening range of the valve. Modal characteristics are also consistent with experimental data.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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 designObservational
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

Citations3
Published2017
Admission routes1
Has abstractyes

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