Nonlinear Dynamic Behavior of a Flexible Shaft Supported by Smart Hydrostatic Squeeze Film Dampers
Bibliographic record
Abstract
The aim of this research is to study the nonlinear dynamic behavior of a flexible shaft supported by smart hydrostatic squeeze film dampers, which are filled with a negative electrorheological fluid (NERF). A nonlinear model of the hydrostatic squeeze film damper has been developed in order to study the effect of the electrorheological fluid on the dynamic behavior of a flexible shaft. The results obtained are discussed and compared with the linear model, which is restricted to only small vibrations around the equilibrium position. A new smart hydrostatic squeeze film damper is proposed to reduce the transient response of the shaft and transmitted forces by applying an electric field to the NER fluid, which results in modifying its viscosity. The results show that it is possible to effectively monitor the electric field and the viscosity of the fluid inside the hydrostatic squeeze film dampers (HSFD) for a better control of flexible shaft vibration and bearing transmitted forces.
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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 | 0.000 |
| 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".