Viscoelastic Coupling Dampers (VCDs) for Outrigger Systems in Tall Building Structures
Bibliographic record
Abstract
Viscoelastic coupling dampers (VCDs) were developed at the University of Toronto over the past few decades to increase the inherent damping of tall building structures. The VCD system consists of viscoelastic (VE) panels bolted to steel ductile structural sections anchored to reinforced concrete walls and columns. VE panels are comprised of high damping viscoelastic layers bonded in between steel plates. These panels add damping and stiffness to structures for frequent wind and earthquake loads, while specialty ductile elements activate and dissipate energy for high levels of ground shaking. The experimental validation of the VCD system to date has focused on coupled shear wall reinforced concrete tall buildings. This thesis presents the largest experimental validation ever conducted on this type of system, and advanced numerical studies of the damped outrigger VCD system to validate its use in super-tall and mega-tall buildings (over 300 m of height), as well as highly dynamically sensitive slender buildings. A full-scale dynamic testing setup was designed to simulate the boundary conditions of outrigger coupling elements, and a wide variety of testing protocols were conducted including dynamic real time tests at very small amplitudes of vibration (thousands of a millimetre) to high amplitude rare hurricanes and earthquakes time histories reaching high rotation demands from simulations that considered a wide range of tall buildings from 142 m to 640 m in height. Guidelines for the design and modelling of VCDs are presented for three-dimensional finite element models and simplified models for common commercial structural engineering software such as ETABs and PERFORM 3D. The effectiveness of the VCD system implemented in single or multi-outrigger configurations is then studied for a group of five tall buildings with different levels of wind and earthquake hazards revealing significant reductions in all engineering demand parameters, such as drifts, roof accelerations, base moments, and shears, among others.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".