Dynamic behavior analysis of a rigid rotor supported by hydrostatic squeeze film dampers compensated with new electrorheological valve restrictors
Bibliographic record
Abstract
Purpose This paper aims to propose a new hydrostatic squeeze film damper compensated with electrorheological valve restrictors to control the nonlinear dynamic behavior of a rigid rotor caused by high unbalance eccentricity ratio. To investigate the effect of electrorheological valve restrictors on the dynamic behavior of a rigid rotor, a nonlinear model is developed and presented. Design/methodology/approach The nonlinear results are compared with those obtained from a linear approach. The results show good agreement between the linear and nonlinear methods when the unbalanced force is small. The effects of unbalance eccentricity ratio and electric field on the vibration response and the bearing transmitted force are investigated using the nonlinear models. Findings The results of simulation performed that the harmonics generated by high unbalance eccentricities can be reduced by using hydrostatic squeeze film damper compensated with electrorheological valve restrictors. Originality/value The numerical results demonstrate that this type of smart hydrostatic squeeze film damper provides to hydrostatic designers a new bearing configuration suitable to control rotor vibrations and bearing transmitted forces, especially for high speed.
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) | 0.000 | 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".