Study of Occupant-Seat Models for Vibration Comfort Analysis of Automotive Seats
Bibliographic record
Abstract
The comfort assessments of automotive seats are attempted through development of seat-occupant models in order to minimize the participation of human subjects in such studies. A nonlinear model of a polyurethane foam (PUF) cushion and its support mechanism is developed through measurement of static and dynamic properties as functions of the seated load, and excitation frequencies and amplitudes. Nonlinear analytical models of the seat-occupant system are developed by integrating three different occupant models of different complexities with the cushion model. The analytical response characteristics of these models are derived under sinusoidal and random excitations considered representative of the automotive vibration environment. The vibration transmission properties of the seat are measured in the laboratory under harmonic and random excitations using 6 human subjects. The response characteristics of the models are compared with the mean measured response characteristics to examine the validity of occupant models for automotive applications. From the comparison, it is concluded that the reported occupant models yield poor estimates of vibration transmission performance of automotive seats.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 0.001 |
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".