The Influence of Impact Angle on the Dynamic Response of a Hybrid III Headform and Brain Tissue Deformation
Bibliographic record
Abstract
The objective of this study was to investigate the influence of impact angle on the dynamic response of a Hybrid III headform and brain tissue deformation by impacting the front and side of the headform with four angle conditions (0° at the impact site and 5°, 10°, and 15° counterclockwise rotations from 0°), as well as three additional angles of −5°, −10°, and −15° (clockwise rotations from 0°) at the side location to examine the effect of direction. The acceleration–time curves were used as input into a finite element model of the brain in which the maximum principal strain was calculated. The results from this study show that impact angle has an asymmetric influence on headform dynamic responses and strain. An increase in impact angle tends to result in the growth of headform linear and rotational acceleration and maximum principal strain for the front location and the negative angles (0° to −15°) at the side; however, varying trends were observed for the positive angles (from 0° to 15°) at the side. When developing sophisticated impact protocols and undertaking head injury reconstruction research, it is important to be aware of impact angle.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".