An accurate technique for pre-yield characterization of MR fluids
Bibliographic record
Abstract
This study is concerned with the characterization of two types of magnetorheological (MR) fluids (MR 122EG and MR 132DG) in the pre-yield region. A phenomenological model is proposed for characterizing the complex shear modulus of the MR fluids as a function of both the magnetic flux density and the excitation frequency using the experimental data acquired for both the fluids. The experiments were conducted with a sandwich beam structure with an aluminum face layer and MR fluid as the core layer. A nearly uniform magnetic field was applied across the sandwich beam using two ceramic permanent magnet bars. The frequency response characteristics of the sandwich cantilevered beam were subsequently measured under harmonic excitations swept in the 0 to 500 Hz frequency range considering different densities of the applied magnetic flux, ranging from 0 to 90 mT. Dynamic responses of the structure were also obtained through analysis of a finite element (FE) model developed using the classical plate theory. The frequency and field-dependent complex shear moduli of the two MR fluids were identified from both the experimental data and the FE model results. The validity of the proposed methodology is demonstrated by comparing the FE model results with the experimental data for a copper sandwich structure comprising the two MR fluids.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".