Accelerated computational modeling of ballistic helmet test protocols

Abstract

In modern combat, helmets play a vital role in protecting the head. Before being delivered to the soldier, combat helmets undergo a series of tests to determine their threat mitigation performance. During ballistic testing, current combat helmet test protocols use clay to record the helmet backface deformation signature, which is used as an important criterion to measure the helmet effectiveness at preventing head injury. However, according to a recent review of the test protocols by the National Research Council, the current test protocols establish no correlation between the backface deformation signature in the clay and head/brain injury. Modeling and simulation are valuable tools to complement experimental helmet testing and can assist in establishing this correlation. The objective of this work is to develop a comprehensive computational framework for the simulation and analysis of the helmet test protocols. In order to achieve this objective the following steps were performed. First, a suitable constitutive model for ballistic clay based on Cam-Clay theory was implemented into the computational framework SUMMIT. Next, a detailed model of the headform used in the helmet test protocols was created. The model was developed using the scanned geometry data from the experimental headform and includes the metal frame, Roma Plastilina clay and a full combat helmet with pads. Subsequently, ballistic impact simulations using the model were performed and the backface deformation signatures of the helmet are recorded in the clay. The results from these impact simulations are compared to results from impact simulations on a human head model. The intracranial pressure distribution in the human head is compared to the pressure distribution in the clay and the differences in the responses are highlighted. We conclude that the proposed computational framework is an effective tool of the analysis of helmet test protocols, which could be used to establish the correlation with injury and to guide the design of improvements to the helmet testing methodologies.