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Modeling of advanced combat helmet under ballistic impact

Publication Year :
2015

Abstract

The use of combat helmets has greatly reduced penetrating injuries and saved lives of many soldiers. However, behind helmet blunt trauma (BHBT) has emerged as a serious injury type experienced by soldiers in battlefields. BHBT results from nonpenetrating ballistic impacts and is often associated with helmet back face deformation (BFD). In the current study, a finite element-based computational model is developed for simulating the ballistic performance of the Advanced Combat Helmet (ACH), which is validated against the experimental data obtained at the Army Research Laboratory. Both the maximum value and time history of the BFD are considered, unlike existing studies focusing on the maximum BFD only. The simulation results show that the maximum BFD, the time history of the BFD, and the shape and size of the effective area of the helmet shell agree fairly well with the experimental findings. In addition, it is found that ballistic impacts on the helmet at different locations and in different directions result in different BFD values. The largest BFD value is obtained for a frontal impact, which is followed by that for a crown impact and then by that for a lateral impact. Also, the BFD value is seen to decrease as the oblique impact angle decreases. Furthermore, helmets of four different sizes - extra large, large, medium, and small - are simulated and compared. It is shown that at the same bullet impact velocity the small-size helmet has the largest BFD, which is followed by the medium-size helmet, then by the large-size helmet, and finally by the extra large-size helmet. Moreover, ballistic impact simulations are performed for an ACH placed on a ballistic dummy head form embedded with clay as specified in the current ACH testing standard by using the validated helmet model. It is observed that the BFD values as recorded by the clay in the head form are in good agreement with the experimental data.<br />QC 20151130

Details

Database :
OAIster
Notes :
Li, Y. Q., Li, Xiaogai, Gao, X. -L
Publication Type :
Electronic Resource
Accession number :
edsoai.on1233753739
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1115.1.4031095