Modelling the hysteretic characteristics of a magnetorheological fluid damper
Bibliographic record
Abstract
A generalized model is proposed to characterize the biviscous hysteretic force characteristics of a magnetorheological (MR) fluid damper using symmetric and asymmetric sigmoid functions on the basis of a fundamental force generation mechanism, observed qualitative trends and measured data under a wide range of control and excitation conditions. Extensive laboratory measurements were performed to characterize the hysteretic force properties of an MR damper under a wide range of magnitudes of control current and excitation conditions (frequency and stroke). The global model is realized upon formulation and integration of component functions describing the preyield hysteresis, saturated hysteresis loop, linear rise and current-induced rise. The validity of the proposed model is demonstrated by comparing the simulation results with measured data in terms of hysteretic forcedisplacement and force-velocity characteristics under a wide range of test conditions. The results revealed reasonably good agreement between the measured data and model results, irrespective of the test conditions considered. The results of the study suggest that the proposed model could be effectively applied for characterizing the damper hysteresis and for development of an optimal controller for implementation in vehicular suspension applications.
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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) | 0.001 | 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 | 0.000 |
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".