Monitoring of Tall Buildings to Assist the Design of Supplementary Damping Systems
Bibliographic record
Abstract
Unlike visco-elastic and hydraulic damping systems, which are effective over a broad band of frequencies, TLDs, TLCDs and TMDs are tuned systems whose design requires accurate information on the periods of vibration of the building. The effectiveness of such devices is therefore much improved if they are tuned to the "as-constructed" periods of vibration which can differ appreciably from analytical estimates. Full-scale monitoring of a tall building towards the end and/or after the completion of construction provides valuable information on the "as-constructed" dynamic properties. Measured periods of vibration provide an important input to finalize the design of tuned supplementary damping systems. The effectiveness of such damping systems in reducing wind-induced building motions to acceptable levels also depends on good estimates of the inherent structural damping. Nominal values of the likely structural damping are used in the design of tall buildings. These can differ from the structural damping actually achieved for a constructed building. Consequently, measured values of the structural damping provide a valuable input for sharpening the estimated performance of the building under the action of wind. This paper summarizes monitoring procedures used at the BLWTL and provides examples of information obtained in such studies. Information from such monitoring is often for small amplitude motions and its applicability during stronger wind events requires interpretation. This requires interaction with the structural engineers. This early information on the `as-built' dynamic properties of a tall building is important for assuring effective operations of tuned supplementary damping systems.
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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 | 0.001 | 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) | 0.003 | 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".