Mechanical metamaterials for sports helmets: structural mechanics, design optimisation, and performance

Abstract

Abstract Sports concussions are a public health concern. Improving helmet performance to reduce concussion risk is a key part of the research and development community response. Direct and oblique head impacts with compliant surfaces that cause long-duration moderate or high linear and rotational accelerations are associated with a high rate of clinical diagnoses of concussion. As engineered structures with unusual combinations of properties, mechanical metamaterials are being applied to sports helmets, with the goal of improving impact performance and reducing brain injury risk. Replacing established helmet material (i.e. foam) selection with a metamaterial design approach (structuring material to obtain desired properties) allows the development of near-optimal properties. Objective functions based on an up-to-date understanding of concussion, and helmet testing that is representative of actual sporting collisions and falls, could be applied to topology optimisation regimes, when designing mechanical metamaterials for helmets. Such regimes balance computational efficiency with predictive accuracy, both of which could be improved under high strains and strain rates to allow helmet modifications as knowledge of concussion develops. Researchers could also share mechanical metamaterial data, topologies, and computational models in open, homogenised repositories, to improve the efficiency of their development.