Image/Model Based System for Optimized Helmet Design

Military helmets are designed based on costly and time consuming laboratory ballistic tests, firing range, and forensic data. Until now advanced medical imaging and computational modeling tools have not been adequately utilized in the design and optimization of military helmets. The overall objective of this project is to develop 3D medical imaging techniques for the brain ballistic injury model and high-fidelity Finite Element Model (FEM)-based computational tools for design of new generation military helmets. The integrated experimental and computational models will be used to study the blunt impact effect on the Kevlar helmet materials and the dynamic responses of the skull and brain. The numerical model will be validated against experimental data involving manikin, cadaver, and animal data. The tools will be demonstrated on the computational optimization of the helmet design and a multi-parametric design window: variable material composition, thickness, helmet-head standoff distance, and others. In phase II we will develop the test stand and a 3D imaging system scalable for various skull phenotypes. An integrated experimental/computational framework for the design of military helmets will be used to improve and optimize the latest generation of helmets to reduce ballistic and blast injuries. The framework will be delivered to the Army.