Development of a Novel Magneto-Rheological Elastomer-Based Semi-Active Seat Suspension System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human operators in the transportation sector are exposed to whole-body vibration (WBV) while driving. Occupational exposure to WBV, predominant at low frequencies (<20 Hz), has been linked to spinal injuries and reduced functioning. This study aims at the design development of a novel semi-active seat suspension system featuring magneto-rheological elastomers (MREs) to mitigate the WBV. The proposed suspension system allows a greater range of strokes, while ensuring the MRE remains within an acceptable level of deformation. Several MRE samples were fabricated and characterized under shear mode. Afterward, a field- and frequency-dependent phenomenological model was developed to predict the viscoelastic properties of MREs as functions of both the excitation frequency and applied magnetic field. The MRE material model was subsequently used to design and optimize an adaptive seat suspension system incorporating a C-shaped MRE-based isolator in parallel and series with passive springs. The proposed adaptive seat suspension system demonstrated a frequency shift of 29% by increasing the applied current from 0 to 2 A. Finally, a 6-DOF lumped parameter model of a seated human subject combined with the proposed semi-active suspension system featuring the MRE isolator has been formulated to investigate the vibration transmissibility from the floor to the subject’s head.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it