Nonlinear vibration analysis of circular/annular/sector sandwich panels incorporating magnetorheological fluid operating in the post-yield region
Bibliographic record
Abstract
This study offers a comprehensive analysis on the nonlinear vibratory behavior of circular, annular, and sector sandwich panels containing magnetorheological (MR) fluid as the core layer. Due to the large deformation experienced by the sandwich structures, the MR fluid operates in the post-yield region, in which the shear strain and shear stress are nonlinearly dependent. The post-yield characteristics of the MR fluid are quantified using the experimental results available in the literature. The present study also employs the experimental results presented in the literature on the dynamic characteristics of a MR based sandwich circular plate to demonstrate accuracy of the results. To identify governing equations of motion of the structures, a finite element approach based on von Karman formulations is employed. Moreover, displacement control strategy is used to solve the extracted nonlinear equations and evaluate dynamic characteristics of the MR based circular/annular/sector sandwich plates in terms of resonant frequencies and loss factors. This study highlights the effect of post-yield behavior of the MR fluid in the nonlinear vibration attenuation of MR sandwich structures, under different levels of magnetic field. Also, the effects of maximum deformation and magnetic field on the functionality of the MR fluid are comprehensively investigated.
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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) | 0.000 | 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".