Effect of Occupant Weight and Initial Position in Low-to-High Speed Rear Sled Tests with Older and Modern Seats
Bibliographic record
Abstract
The average body weight of the US population has increased over time. This study investigates the effect of increasing weight on seat and occupant responses in 15-18 km/h and 42 km/h rear sled tests. The effect of initial occupant posture is also discussed. Seven tests were conducted with lap-shoulder belted ATDs (anthropometric test device) placed on older and modern driver seats. Four tests were conducted with a 50th percentile male Hybrid III, two with 95th percentile male Hybrid III and one with a BioRID. The ATDs were ballasted to represent a Class I or II obese occupant in three tests. The tests were matched by seat model and sled velocity. The effect of occupant weight was assessed in three matches. The results indicated an increase in seatback deflection with increasing occupant weight. For example, the average dynamic deflection was 2.8-times greater with a ballasted 95th ATD than with a 50th ATD (20.2 v 7.3 degree) in the 15-18 km/h sled tests and 1.4-times greater with a 95th ATD than with a 50th ATD (35.4 v 25.3 degree) in the 42 km/h sled tests. The effect of initial posture was assessed with an obese Class I 50th ATD initially placed in-position versus leaning inboard. Being out-of-position led to increased occupant loading due to inertial loads from the unsupported portion of the ATD. The thoracic-spine extension moment was 1.3-times greater (−155 Nm v −123 Nm) when the ATD was out-of-position than in-position. All biomechanical responses were below the relevant injury assessment reference values (IARV) for head, neck and chest. The highest responses relative to IARVs were for lower neck extension in the 17 km/h out-of-position test, which was recorded up to 44.7% of the IARV. The lower neck extension moment increased with occupant weight in the Expedition seat. It was similar with the F-250 and Mustang seat. Additionally, lower neck extension was 1.2-times greater when leaning inboard than when positioned in a nominal driving position. The highest normalized responses were chest acceleration in the 42 km/h tests, at 30.3% with the 50th and 28.6% with the 95th ATD. The results highlight an increase in seatback rotation with occupant weight. Seatback rotation was lower in modern than in older seats. Seat strength, occupant weight, seating position and crash severity influence occupant kinematics and loading in rear impacts.
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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 | 0.001 |
| 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 | 0.000 | 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".