Bibliographic record
Abstract
Injuries in side impact collisions, particularly to the thorax, are one of the leading causes of fatalities and severe injury in automotive collisions. Current side impact crash testing standards stipulate an initial position of the anthropometric test device (ATD) before impact; however, there is limited data regarding the relationship between initial ATD position, response and predicted injury. In this study, a finite element model of a full-scale side impact test was developed integrating full-vehicle, barrier and ATD models. The individual models were verified and validated, followed by validation of the fully integrated model using vehicle-specific crash tests and a broader study of late model sedan crash tests. The model predicted that the velocity profile of the impacted door was dominated by occupant interaction during contact and by the vehicle structure before and after contact with the occupant. Generally, the predicted level of injury increased when the ATD model was positioned closer to the intruding door or moved further rearwards due to interaction with the B pillar. Additionally, the door interior geometry was found to have a significant effect on the results due to the timing and location of interaction with the thorax. The thorax deflection was found to be much less sensitive to changes in position than the viscous criterion, which incorporated a velocity term in addition to a deflection. This study demonstrates the importance of occupant position on response and the possibility to enhance safety through interior door design and standoff distance.
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) | 0.001 | 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 | 0.001 |
| 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".