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Record W1989693505 · doi:10.1177/107754603030773

A Family of Efficient Sloshing Liquid Dampers for Suppression of Wind-Induced Instabilities

2003· article· en· W1989693505 on OpenAlexaff
V. J. Modi, Ayhan Akintürk, W. Tse

Bibliographic record

VenueJournal of Vibration and Control · 2003
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSlosh dynamicsDamperDissipationVibrationStructural engineeringVortexParametric statisticsEngineeringResonance (particle physics)Vortex sheddingVibration controlMechanicsPhysicsAcousticsTurbulence

Abstract

fetched live from OpenAlex

Bluff structures in the form of tall buildings, smokestacks, control towers, bridges, etc., are susceptible to vortex resonance and galloping type of instabilities. One approach to vibration control of such systems is through energy dissipation using sloshing liquid dampers. In this paper we focus on enhancing the energy dissipation efficiency of a rectangular liquid damper through the introduction of two-dimensional obstacles as well as floating particles. The investigation has two phases. To begin with, a parametric free vibration study aimed at the optimization of the obstacle geometry is undertaken to arrive at configurations promising increased damping ratio and hence higher energy dissipation. The study is complemented by an extensive wind tunnel test program, which substantiates the effectiveness of this class of damper in suppressing both vortex resonance and galloping type of instabilities. Simplicity of design, ease of implementation, minimal maintenance, reliability as well as high efficiency make such liquid dampers quite attractive for real-life applications.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.230

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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations12
Published2003
Admission routes1
Has abstractyes

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