Safety and Comfort Analysis of Optimal Seats With Active and Semi-Active Suspension
Bibliographic record
Abstract
A generalized nonlinear model is formulated for dynamic analysis of suspension seats with passive, semi-active and active dampers. The model incorporates coulomb friction due to suspension linkages and bushings, forces arising from interactions with the elastic limit stops, a linear suspension spring and nonlinear damping force on the basis of passive, semi-active and active dampers, while the contribution due to biodynamics of the human operator is considered to be negligible. The semi-active and active dampers are charcterized by force generators in accordance with the control laws based upon suspension mass velocity. Two different suspension seats are experimentally assessed in the laboratory under sinusoidal and random excitations arising from an urban bus, and the measured data is used to demonstrate the validity of the proposed generalized model. The results showed reasonably good agreement between the model results and the measured data. Optimal model parameters are selected using the sequential unconstrained minimization technique with an objective to minimize the acceleration due to vibration transmitted to the occupant mass. The comfort and safety performance characteristics of the optimal suspension seat with semi-active and active dampers are evaluated under both the sinusoidal and random excitations on the basis of the guidelines provided in ISO-2631. From the results it is concluded that the comfort performance of a suspension seat with semi-active and active dampers can be considerably enhanced, in the 20% to 30% range.
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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) | 0.000 | 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".