Experimental Study on the Effect of Attachments on the Vortex-Induced Vibration of a Centrally Slotted Box Deck
Bibliographic record
Abstract
Centrally slotted box decks have been commonly used as components of bridges, especially for long-span bridges. A wind tunnel experiment was conducted to investigate the effect of attachments on the vortex-induced vibration (VIV) of the deck. In this research, the characteristics of VIV responses at different attack wind angles of 5 models considering naked bridge decks, crash barriers, wind barriers, and vehicles on bridges were studied and discussed. The effects of crash barriers, wind barriers and vehicles on the VIV behaviors of the bridge deck were also investigated experimentally. Multiple lock-in wind speed intervals were found to occur for all the models considered, and the vibrating amplitude and frequency show differences in different models. The results of the study showed that, owing to the installation of crash barriers or wind barriers, the vibrating frequency at the second lock-in interval indicated a double natural frequency. However, for the naked bridge deck model, the vibrating frequencies were close to the vertical natural frequency at all lock-in regions. Additionally, the frequency showed an evolutionary characteristic from the first lock-in interval to the second lock-in interval. Generally, the installation of crash barriers and wind barriers caused an increase of 89.8% and 123.7% on maximum vibrating amplitudes respectively. The vehicles had amplification effects on the amplitudes in both lock-in regions, with an increase of 41.5% at the maximum amplitudes. This study provides a guideline for designing bridges consisting of centrally slotted box-type decks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".