Equivalent mechanical model for tuned liquid damper of complex tank geometry coupled to a 2D structure
Bibliographic record
Abstract
Tuned liquid dampers (TLDs) control the wind-induced vibrations of tall buildings using sloshing fluid. TLD tanks of complex geometry may be required in practice due to space limitations; however, their behaviour has not been considered in the literature. This study develops and experimentally validates a model to describe the structure–TLD interaction of a 2D system when the TLD tank geometry is complex. The equations of motion of the structure–TLD system are developed using Lagrange's equation. In general, the 2D structure–TLD interaction must be represented as a coupled four degree of freedom system. The model is validated using new structure–TLD system tests where the structure is subjected to 1D and 2D harmonic and random excitation. Two TLD tanks of complex geometry are considered; the first tank is anti-symmetric about both axes, whereas the second tank is symmetric about both axes. For the anti-symmetric tank, energy transfer between orthogonal structural sway modes and sloshing modes is significant; however, for the symmetric tank, this energy transfer is negligible. Experimental results indicate that the model adequately predicts the structural response; however, the nonlinear behaviour of the fluid response cannot be captured by the linearized model. Copyright © 2013 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".