Bibliographic record
Abstract
An asymmetric damping force generation algorithm is originally proposed to yield the asymmetric force-velocity characteristics for the symmetric magneto-rheological (MR) dampers. The command current is formulated in an asymmetric manner to excite the symmetric MR dampers by employing the on-off control law in response to the direction of velocity, and a smooth modulation function is developed without phase shift to suppress strong transients in the damping forces caused by the current-switching discontinuity. The effectiveness of the proposed algorithm is evaluated by analyzing the dynamic responses of a quarter-vehicle suspension system with a symmetric MR-damper by modulating the command current into the asymmetric manner. The simulation results show that the proposed algorithm could achieve a better compromise between the conflicting requirements of the asymmetric damping force ratio and the force-velocity curve smoothness, and the asymmetric damping MR-suspension design can ideally improve the road holding and ride performances of vehicle motion. The proposed algorithm can be generally incorporated with a controller synthesis to realize an intelligent vehicle suspension design with the symmetric MR dampers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".