Human rib response to different restraint systems in frontal impacts: a study using a human body model
Bibliographic record
Abstract
Finite-element human body models (FE-HBMs) can be used to evaluate restraint systems by predicting thoracic injury. The biofidelity assessment of an FE-HBM Total HUman Model for Safety (THUMS) 50th percentile male occupant and the characterisation of its rib response to loads from frontal car crashes are the objectives of this study. The rib-cage mesh of THUMS version 3.0 was refined to improve the shoulder-belt interaction, material properties of lungs and skin modified, and the model biofidelity assessed against tests representative of frontal crashes. The modified THUMS response improved with respect to the baseline model. The modified THUMS was used to analyse the rib loading in frontal impacts. The rib response included shear, torsion and bending in belt and airbag-like load cases. This indicates that a criterion based only on rib anteroposterior compression may not be enough to predict fractures and that a criterion should consider compression, torsion and shear.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".