Optimal Design of Asymmetric Passive and Semi-Active Dampers
Bibliographic record
Abstract
Vibration isolators are essentially used to reduce the magnitude of motion or force transmitted from a vibrating source to vibration recipient bodies. Such recipients might be a foundation, a structure, or even a human’s body. Despite all the advancement in vibration control using active and semi-active systems, passive vibration isolators are still widely used in different industrial applications because of their simplicity and low cost. In this paper we investigate an asymmetric one-degree of freedom vibration isolator. This is very important in practice, because all hydraulic dampers are asymmetric in nature. Due to the non-linearity of this system as a result of asymmetric damping, analytical methods of averaging and numerical simulation are used to analyze its frequency and time response characteristics. Optimal damping and stiffness values for the isolator are obtained by minimizing the cost functions, which are the Root Mean Square (RMS) of the acceleration transmissibility and the relative displacement transmissibility. The effect of the asymmetric damping on the optimal values in passive systems are then analyzed and used to create a design chart for the isolator parameters. In addition, the effect of asymmetry on the conventional semi-active systems is studied and the method to the optimal design of asymmetric semi-active systems is discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".