Design and development of a hybrid Magneto-Rheological clutch for safe robotic applications
Bibliographic record
Abstract
In this paper, we present a new concept for generating magnetic field in Magneto-Rheological (MR) clutches intended for safe robotic applications. The main rationale behind this concept is to divide the magnetic field generation into two parts using an electromagnetic coil and a permanent magnet. The permanent magnet generates a bias magnetic field density at the optimum working point of the MR clutch while the energized coil can add or negate the magnetic field to a desired value. The results will show clear advantages of this concept in reducing the total weight of the MR clutch, improving the torque-to-mass ratio, and reducing electrical power consumption. The proposed concept is validated using computer model of an MR clutch and Finite Element Method (FEM) is hired to compare the characteristics of the proposed MR clutch with those from conventional coil based clutch. Experimental results will be provided to further validate the advantages of the proposed new concept.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".