Coupled magneto-hyperelasticity-thermal behavior of magnetorheological elastomers: A physics-based model and experimental verification
Bibliographic record
Abstract
Recently, magnetorheological elastomers (MREs), known as a class of functional materials, have garnered considerable attention. MREs adapt their mechanical properties under external magnetic fields, positioning them as versatile materials for a range of engineering and biomedical applications. Therefore, accurately characterizing and modeling of their response under near-real-life conditions is of paramount importance. In this study, a physics-based model based on nonlinear continuum mechanics framework and total Helmholtz energy function has been formulated to predict the response of soft isotropic MREs under coupled magneto-hyperelasticity-thermal conditions. The deformation gradient, magnetic induction, and temperature are treated as independent variables in the proposed model. Additionally, the state of temperature and its gradient within the medium are examined to assess their influence on both the shear modulus and the total energy function. The Yeoh hyperelastic energy function is modified to incorporate magnetic and magneto-mechanical coupling effects, representing the isothermal component in the total Helmholtz energy function. In addition to the proposed mathematical model, a series of experimental tests are carried out to determine the material parameters and validate the accuracy of the developed model. The experimental results reveal that the fabricated MRE exhibits an increase in shear modulus in linear viscoelastic region with rising temperature. The model is subsequently utilized to study a boundary-value problem addressing a solid cylinder made of MRE subjected to torque-twist loading and under thermal boundary conditions. The effects of temperature and magnetic flux density on the response of the MRE cylinder, specifically torque–twist behavior, material stiffening, and strain softening, are subsequently examined and discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".