Investigating Large-Scale Tuned Liquid Dampers through Real-Time Hybrid Simulations
Bibliographic record
Abstract
As buildings become taller and slenderer, managing their vibrational response and mitigating it pose significant challenges in design. Tuned liquid dampers (TLDs) are liquid (usually water)-filled tanks that can mitigate structural vibrations by leveraging the sloshing motion of the contained fluid. However, the dynamic behavior of TLDs and their interaction with structures is complex. While most research on TLDs has focused on mitigating wind-induced vibrations, less attention has been paid to their seismic control of structural responses. Moreover, existing literature on the experimental research involving TLDs mostly pertains to small-scale models. This study aims to experimentally explore the effectiveness of large-scale TLDs in mitigating vibrations in both linear and nonlinear structures under seismic loads. A real-time hybrid simulation is employed as the experimental method, where only the TLD is physically constructed and tested, while the rest of the system is simulated numerically in a coupled manner, allowing for obtaining the dynamic response of the structure equipped with the TLD in real time. This approach offers the flexibility to significantly scale up the TLD size for physical testing while exploring various TLD-structure scenarios by numerically adjusting the structural properties within the simulation.
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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) | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".