Effect of body size and enhanced helmet systems on risk for motorsport drivers.

Objective: Computational modeling has been shown to be a useful tool for simulating representative motorsport impacts and analyzing data for relative injury risk assessment. Previous studies have used computational modeling to analyze the probability of injury in specific regions of a 50th percentile male driver. However, NASCAR drivers can represent a large range in terms of size and female drivers are becoming increasingly more common in the sport.

Simulation-based assessment of injury risk for an average male motorsport driver.

Objective: While well-protected through a variety of safety countermeasures, motorsports drivers can be exposed to a large variety of crash modes and severities. Computational human body models (HBMs) are currently used to assess occupant safety for the general driving public in production vehicles. The purpose of this study was to incorporate a HBM into a motorsport environment using a simulation-based approach and provide quantitative data on relative risk for on-track motorsport crashes.

Correction to: Development and Multi-Scale Validation of a Finite Element Football Helmet Model.

This correction is to add the middle initials of all authors, which were inadvertently omitted from the original article.

Development and Multi-Scale Validation of a Finite Element Football Helmet Model.

Head injury is a growing concern within contact sports, including American football. Computational tools such as finite element (FE) models provide an avenue for researchers to study, and potentially optimize safety tools, such as helmets. The goal of this study was to develop an accurate representative helmet model that could be used in further study of head injury to mitigate the toll of concussions in contact sports.