Nutation Damper Undergoing a Coupled Motion
Bibliographic record
Abstract
A novel numerical model is proposed to simulate liquid sloshing in a rectangular nutation damper (i.e. a tuned liquid damper) undergoing a coupled horizontal and rotational motion. Shallow water theory is used consistently to derive the governing equations of motion so that the model is applicable to large sloshing involving a hydraulic jump. It can also accommodate exposure of part of the damper’s floor to air by using a somewhat improved boundary shear approximation. A simple finite difference approach – the Lax scheme – is found to solve the equations of motion surprisingly well. Numerical predictions are checked against limited experimental data for a purely horizontal motion. Good agreement is generally observed. Furthermore, to demonstrate the model’s broader scope, the effect of a rotation is also considered in conjunction with a horizontal motion. The rotation is shown to significantly enhance the damper’s energy dissipation and, hence, its attenuation capability. For convenient practical application, an equivalent singledegree-of-freedom oscillator model is presented to characterize a nutation damper’s behavior for a coupled motion. The equivalent parameters of the model are determined so that the dissipated energy “best” fits a numerical counterpart. Their effect is investigated for different lengths, depths, and vibration levels of the damper. While the motivation of this investigation is to control the wind-induced galloping of overhead power lines, the proposed approach is applicable more generally to any excitation that induces low frequency vibrations.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".