Multimode vibration control of stay cables using optimized negative stiffness damper
Why this work is in the frame
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Bibliographic record
Abstract
Due to their low inherent damping and high lateral flexibility, stay cables are prone to large amplitude vibrations governed by either a single or multiple cable modes. Among the practical measures, the installation of transverse passive dampers near the cable-deck anchorage is a popular choice. Compared to conventional positive stiffness and zero stiffness dampers, negative stiffness damper (NSD) manifests superior performance in mitigating cable vibrations, especially in the case of long cables. In this study, a novel design approach is proposed to optimize NSD for multimode cable vibration control. Two design scenarios are considered. In the former, the damper size is optimized for a predetermined negative damper stiffness; whereas in the latter, the size and negative stiffness of the NSD are both optimized to achieve a required damping ratio for the dominant modes. The applicability of the proposed NSD optimum design approach is validated using 15 sample real stay cables. A numerical example is presented, of which a NSD is designed based on the proposed approach to optimize wind-induced multimode vibration control of a 460-m stay cable, and the performance is compared with that of a linear-quadratic regulator (LQR) control. Results show that the selected NSD can effectively suppress the dominant modes and has a controlling effect comparable with an active control using LQR. In addition, it is found that when there exist more than two dominant modes in vibration, designing NSD for the lowest and the highest dominant modes would also adequately control the mid-range modes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it