Performance Analysis of a Relative Motion Based Magneto-Rheological Damper Controller for Suspension Seats
Bibliographic record
Abstract
A kineto-dynamic model of a suspension seat is formulated to account for contributions due to suspension kinematics. A regression-based model of a magneto-rheological (MR) fluid damper is also formulated and integrated to the suspension model. Two semi-active controllers based on the ‘sky-hook’ and ‘relative states’ are synthesized and simulations are performed to evaluate the shock and vibration performance of the MR suspension seat. The simulations are performed under an exponentially-decaying transient excitation with fundamental frequency in the vicinity of the suspension natural frequency, random excitations encountered at the seat base of vehicles with both low and high frequency components. The shock and vibration isolation properties of the suspension seat model are evaluated in terms of frequency-weighted rms accelerations and vibration dose values. Comparisons of the responses of the suspension seat model with ‘sky-hook’ and ‘relative states’ controllers revealed significant improvements compared to those of the passive suspension seat. The semi-active suspension seats could yield 19 to 40% reductions in the transmission of continuous vibration and 26 to 55% reduction of the shock motions. Both semi-active suspension models could considerably reduce the amount of end-stop impacts under high intensity excitations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".