An Integrated Helmet and Neck Support (iHANS) for Racing Car Drivers: A Biomechanical Feasibility Study
Bibliographic record
Abstract
A new form of head and neck protection for racing car drivers is examined. The concept is one whereby the helmet portion of the system is attached, by way of a quick release clamp, to a collar-like platform which is supported on the driver's shoulders. The collar, which encircles the back and sides of the driver's neck, is held in place by way of the on-board restraint belts. The interior of the helmet portion of the assembly is large enough to provide adequate volitional head motion. The overall objective of the design is to remove the helmet from the wearer's head and thereby to mitigate the deleterious features of helmet wearing such as neck fatigue, poor ventilation and aerodynamic buffeting. Just as importantly, by transferring the weight of the helmet and all attendant reaction forces associated with inertial and impact loads to the shoulder complex (instead of to the neck), reduced head and neck injury probability should be achievable. This paper describes the concept development and the evolution of various prototype designs. Prototypes have been evaluated on track and sled tested in accordance with contemporary head neck restraint systems practice. Also discussed is a series of direct impact tests. In addition, low mass high velocity ballistic tests have been conducted and are reviewed herein. It is concluded that this new concept indeed does address most of the drawbacks of the customary helmet and that it generally can reduce the probability of head and neck injury.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".