The Dynamic Response of Tuned Impact Absorbers for Rotating Flexible Structures
Bibliographic record
Abstract
This paper describes an analytical investigation of the dynamic response and performance of impact vibration absorbers fitted to flexible structures that are attached to a rotating hub. This work was motivated by experimental studies at NASA, which demonstrated the effectiveness of these types of absorbers for reducing resonant transverse vibrations in periodically excited rotating plates. Here we show how an idealized model can be used to describe the essential dynamics of these systems, and used to predict absorber performance. The absorbers use centrifugally induced restoring forces so that their nonimpacting dynamics are tuned to a given order of rotation, whereas their large amplitude dynamics involve impacts with the primary flexible system. The linearized, nonimpacting dynamics are first explored in detail, and it is shown that the response of the system has some rather unique features as the hub rotor speed is varied. A class of symmetric impacting motions is also analyzed and used to predict the effectiveness of the absorber when operating in its impacting mode. It is observed that two different types of grazing bifurcations take place as the rotor speed is varied through resonance, and their influence on absorber performance is described. The analytical results for the symmetric impacting motions are also used to generate curves that show how important absorber design parameters—including mass, coefficient of restitution, and tuning—affect the system response. These results provide a method for quickly evaluating and comparing proposed absorber designs.
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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 | 0.001 |
| 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) | 0.001 | 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".