A novel bi-directional shear mode magneto-rheological elastomer vibration isolator
Bibliographic record
Abstract
In this article, a novel bi-directional shear mode magneto-rheological elastomer–based vibration isolator has been designed, fabricated, and characterized to improve the dynamic response and identification of this class of “intellectual” mechanical devices. A heuristic embodiment has been realized in order to design such an isolator wherein both the vertical and horizontal directions can be operated only in the shear mode not only individually but also simultaneously. Two fixtures have been designed for performing the characterization of the magneto-mechanical behavior of the proposed magneto-rheological elastomer isolator in the vertical and horizontal shear modes under wide ranges of strain amplitude (4%–32%), excitation frequency (1–8 Hz), and magnetic flux density (0–220 mT). Experimental results revealed maximum relative magneto-rheological effects of 35% and 27 % in the vertical and horizontal shear modes, respectively. Furthermore, basic mathematical models of single-degree-of-freedom systems, employing the magneto-rheological elastomer–based isolator in the vertical and horizontal shear modes, have been established. The proposed magneto-rheological elastomer isolator in the vertical mode exhibited natural frequency shift of 6.1% by a small increment in the magnetic flux density which approves the potential of the proposed bi-directional shear mode magneto-rheological elastomer–based vibration isolator for vibration control applications, such as seat suspension systems.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".