Preventing the wind-induced vibration of arches during construction
Bibliographic record
Abstract
Arches are the most prominent architectural feature of tied-arch bridges and offer a dramatic visual impact. Arches rarely exhibit aerodynamic instabilities once tied to the bridge deck; however, during construction they typically have low fundamental frequencies, low inherent structural damping and low mass. This combination makes them especially vulnerable to wind-induced vibrations. The three-dimensionality of the arch shape is best examined through aeroelastic model wind tunnel testing as opposed to sectional model based approaches. In many cases vortex-induced oscillations have been observed for certain discrete stages of arch construction. In some cases, the loads induced by these vortex-induced oscillations can be tolerated by the structure; however, in other cases the responses can be sufficiently large that they must be prevented. Therefore, to prevent vortex-induced oscillations of the arches during construction, different damping strategies have been employed. Two practical methods that have been recently deployed include: (i) an in- line cable damper attached by a cable to the arch and anchored to a firm foundation, and (ii) tuned mass dampers (TMD). In this paper a background on the sources of wind-induced vibrations is presented along with methods to predict the response followed by several mitigation strategies.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".