Full-Scale Performance Evaluation of Structure-Dynamic Vibration Absorber Systems
Bibliographic record
Abstract
Modern tall buildings are often susceptible to excessive wind-induced motion, which can cause occupant discomfort and decrease component longevity. Increasing the effective damping of these buildings using a dynamic vibration absorber (DVA) is often the preferred option to decrease motion, especially for serviceability-level performance. A tuned mass damper (TMD) is one form of DVA that consists of a steel or concrete mass that is supported near the top of the building. A tuned sloshing damper (TSD) is another type of DVA that consists of a tank that is partially filled with water and located near the top of the tower. In both cases, when the building moves during a wind event, the motion of the TMD mass or sloshing TSD water lags behind the motion of the structure. A properly designed DVA thereby produces forces that continually oppose the tower’s motion, substantially reducing its response. Although numerous DVAs have been installed worldwide, very little reporting has been published on the full-scale performance of the damping systems. This paper will present the results of measurements conducted on several tall buildings equipped with DVAs. The measured results are compared to theoretical predictions to evaluate performance.
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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 | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".