Energy Absorption of Seated Occupants Exposed to Horizontal Vibration and Role of Back Support Condition
Bibliographic record
Abstract
Absorbed power characteristics of seated human subjects under fore-aft (x-axis) and lateral (y-axis) vibration are investigated through measurements of dynamic interactions at the two driving-points formed by the body and the seat pan, and upper body and the backrest. The experiments involved: (i) three back support conditions (no back support, and back supported against a vertical and an inclined backrest); (ii) three seat pan heights (425, 390 and 350 mm); and three magnitudes (0.25, 0.5 and 1.0 m/s2 rms acceleration) of band limited random excitations in 0.5-10 Hz frequency range, applied independently along the x- and y- axes. The force responses, measured at the seat pan and the backrest are applied to characterize total energy transfer reflected on the seat pan and the backrest. The mean responses suggest strong contributions due to back support, and direction and magnitude of vibration. In the absence of a back support, the seat pan responses dominated in lower frequency bands centered at 0.63 and 1.25 Hz under both directions of motion. Most significant interactions of the upper body against the back support was observed under fore-aft vibration. The addition of back support caused the seat pan response to converge to a single primary peak near a higher frequency of 4 Hz under x- axis, with only little effect on the y-axis responses. The back support serves as an additional source of vibration to the occupant and an important constraint to limit the fore-aft movement of the upper body and thus relatively higher energy transfer under. The mean responses were further explored to examine the Wd frequency-weighting used for assessing exposure to horizontal vibration. The results show that the current weighting is suited for assessing the vibration exposure of human subjects seated only without a back support.
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.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".