Characterization and modeling of temperature effect on the shear mode properties of magnetorheological elastomers
Bibliographic record
Abstract
Abstract The temperature dependency of the viscoelastic properties of magnetorheological elastomers (MREs) operating in the shear mode was experimentally investigated under broad ranges of strain amplitude, excitation frequency, and applied magnetic field. Experiments were performed with isotropic MRE samples with 25 % volume fraction of carbonyl iron particles dispersed in the silicone rubber matrix under controlled temperature, ranging from − 10 ∘ C to 50 ∘ C together with different levels of magnetic field density ( 0 to 1.0 T ). The results revealed significant effect of temperature on the linear and nonlinear viscoelastic properties of MREs, in addition to the effects of strain amplitude, rate, and applied magnetic flux density. The temperature dependency of mechanical properties of an unfilled rubber matrix was also measured, which served as a reference. The shear properties of the MRE revealed reductions in both the storage and loss moduli with increasing temperature. The temperature dependency of the MRE, however, diminished under shear strain in excess of the critical strain. The results also revealed more pronounced temperature effect at higher temperatures and excitation frequencies, while it was relatively lesser with increasing magnetic field. Increase in temperature resulted in enhanced magnetorheological effect, while a clear trend with regard to the excitation frequency could not be established. Finally, a phenomenological model has been developed to predict the storage and loss moduli of the MRE as a function of excitation frequency, applied magnetic flux density, and temperature. The superb performance of the proposed model in predicting viscoelastic moduli under various operating and environmental conditions has been demonstrated through comparison of the experimental and simulation results.
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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".