Structural behaviour of water sloshing damper with embossments subject to random excitation
Bibliographic record
Abstract
To improve the serviceability of tall buildings, several types of vibration control systems have been developed. The tuned liquid damper (TLD) has advantages, such as simple adjustment of natural frequency, easy installation, and low maintenance. Since water tanks at the top of tall buildings can be directly modeled as a TLD system, it is more practical than any other vibration control system in Korea. Since most of the tanks in Korea have embossments on the wall, the structural characteristics are different from those of tanks used in other countries. As the damping ratio of the TLD depends on several factors, such as the magnitude and frequency of applied load, the shape of the tank, wall roughness, and so forth, it is difficult to evaluate the control performance of the tank exactly. In this study, the characteristics of the water sloshing damper with embossments (WSDE) are evaluated and the equation for equivalent damping ratio is proposed. To clarify the damping effect of a high-rise building with a damping device subject to random excitation, an experiment of a coupled structural model with a water tank was conducted. The parameters were mass ratio of water to model structure, number of wire screens, and shape factor of the water tank. The peak displacement, acceleration response, and standard deviation of the experimental results are analyzed. The coupled structural model with a water tank shows lower maximum and standard deviation responses than those of the structural model alone.Key words: water sloshing damper with embossment, vibration control, structural test, tall buildings.
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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 | 0.001 | 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".