Design and experimental characterization of a bypass magnetorheological damper featuring variable stiffness and damping
Bibliographic record
Abstract
Abstract Magnetorheological (MR) fluid dampers (MRFDs) with variable stiffness and variable damping capability (VSVD-MRFDs) have demonstrated excellent vibration mitigation performance. However, there are limited studies on the development of bypass VSVD-MRFDs which offer both higher dynamic range and output force, apart from simple maintenance and straightforward assembly. In this study, a novel large-capacity VSVD-MRFD with an annular-radial bypass MR valve, as opposed to the typical practice of implementing the valve within the traveling piston in the hydraulic cylinder of the MRFD, is proposed. The main contribution of the present work includes: (a) providing the conceptional design and experimental dynamic characterization of the proposed VSVD-MRFD; (b) investigating the feasibility of the proposed damper for realizing the VSVD characteristics under wide ranges of loading conditions. A test rig was, thus, designed to perform experimental characterization of the proposed VSVD-MRFD under wide ranges of mechanical loading and magnetic field conditions. A qualitative analysis including force-displacement, and force-velocity characteristics, together with a quantitative analysis including dynamic range, equivalent viscous and stiffness coefficients, were conducted as a function of loading frequency, displacement amplitude, and applied current. Results showed a maximum dynamic range and maximum output force of 4.5 and 7.8 kN, respectively. Also, the maximum relative increase in the equivalent viscous and stiffness coefficients were obtained, respectively, as 425% and 488%, when the applied current is increased from zero to 2 A. The results confirm the potential of the proposed VSVD-MRFD for applications in off-road suspension systems. The externally designed bypass MR valve permits a straightforward design modification for realizing wide scalability of damping force in different applications (e.g., off-road vehicle suspension systems).
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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 | 0.001 |
| 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 | 0.001 | 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".