A finite element based computational model simulating the standard drop tower test for military helmets was created and used in conjunction with a multi-output Gaussian process surrogate to seek different designs of helmets for improved blunt impact performance. Experimental drop test results were used for the validation of the model’s ability to simulate impact. The influence of foam stiffness, impact velocity, strap tension, as well as pad placement and size on parameters on the peak linear acceleration (PLA) of the headform was investigated for the first time through a surrogate model trained by strategically choosing simulation points. Impact velocity was found to have the greatest effect. The strap tension and foam pad stiffness ranges examined within this sampling plan were found to have less of an effect on the performance of the helmet than the pad size and shape parameters examined. The surrogate modeling approach was used to quantify the influence of design parameters and can lead to not only improved helmet designs but also new data-driven design metrics and testing standards to accelerate the development of TBI-mitigating helmets.

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Modeling composites can be an effective way to understand how a part will perform without requiring the destruction of costly specimens. By combining artificial fiber entanglement with manufacturing process simulation, a method was developed to create fiber bundle models using entanglement to control the fiber volume fraction. This fiber entanglement generation uses three parameters, probability of swapping (p_(r_S )), swapping radius standard deviation (r_(σ_S )), and the swapping plane spacing (l_S), to control the amount of entanglement within the fiber bundle. A parametric study was conducted and found that the more entanglement within a fiber bundle, the more compression mold pressure required to compact the fiber bundle to the same fiber volume fraction as that required for a less entangled bundle. This artificial fiber entanglement and manufacturing process simulation method for creating fiber bundles shows the potential to be able to create bundles with controlled final volume fraction using a desired mold compression pressure.