A Hybrid Model for Characterizing Pre-Yield Properties of MR Fluids
Bibliographic record
Abstract
This study aims to present a field dependent phenomenological model to characterize the Magneto-Rheological (MR) fluid in the pre-yield region under varying frequency and applied magnetic field. Systematic analytical and experimental studies are proposed to formulate a hybrid model for representing complex shear modulus of a typical MR fluid (MR 122EG from Lord Corporation) as a function of both applied magnetic field and frequency. Two fully treated MR based sandwich beams with aluminum and copper face layers and MR fluid as the core layer are designed and fabricated. Uniform magnetic flux across the sandwich beam is provided using two permanent magnets. The fabricated MR based sandwich beams are then tested on an electrodynamic shaker under sweep sine excitation and different applied magnetic field to realize the effect of external excitation frequency and applied magnetic field on the stiffness and damping properties of the structure. The finite element model based on classical plate theory is also developed to analyze vibration response of the designed MR based sandwich beams incorporated with MR fluid. Then, by correlating the finite element results with those of the experiment, the frequency and field dependent complex shear modulus of the MR fluid is identified.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".