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Record W4413025465 · doi:10.1177/10775463251362279

Experimental and numerical investigations on the effect of water-filled barriers on the vortex-induced vibrations of large span bridges

2025· article· en· W4413025465 on OpenAlexaff
Dandan Xia, Lin Li, Kamran Foroutan

Bibliographic record

VenueJournal of Vibration and Control · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of Regina
FundersXiamen UniversityXiamen University of TechnologyNational Natural Science Foundation of China
KeywordsVibrationSpan (engineering)Vortex-induced vibrationStructural engineeringVortexMechanicsMaterials scienceEngineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

Water-filled barriers have been reported to significantly affect the vortex-induced vibrations (VIVs) of large-span bridges. However, few studies have systematically investigated the influence mechanisms of water-filled barriers on bridge decks. In this research, both wind tunnel tests and numerical simulations were conducted to analyze the VIV behavior of the considered bridge model with various arrangements of water-filled barriers on the bridge deck. Six configurations with different water-filled barrier positions on the bridge deck were tested in a wind tunnel, and numerical simulations were conducted to explore the influence mechanisms of water-filled barriers. The results show that with the installation of water-filled barriers, the maximum RMS of the vertical VIV amplitudes are increased by 100% compared with that in Case 1 without water-filled barriers, whereas the torsional VIV amplitudes may slightly decrease. Compared with the most unfavorable case, where the water-filled barriers were positioned near the crash barriers, moving the water-filled barriers further away from the upstream or adopting a sparse arrangement along the bridge deck may reduce the VIV amplitudes. Therefore, it is important to consider both the incoming flow direction and the positioning of water-filled barriers on the deck should be considered in bridge maintenance to avoid the most unfavorable scenarios.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.193

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 head0.004
GPT teacher head0.223
Teacher spread0.218 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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