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Updated: Jul 16, 2025

A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact
Published on: September 21, 2017
An anatomically-realistic computational framework for evaluating the efficacy of protective plates in mitigating
Maayan Lustig1, Yoram Epstein2, Amit Gefen1
1Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv, Israel.
Background:
A major threat in combat scenarios is the 'behind armor blunt trauma' (BABT) of a non-penetrating ballistic impact with a ballistic protective plate (BPP). This impact results in pressure waves that propagate through tissues, potentially causing life-threatening damage. To date, there is no standardized procedure for rapid virtual testing of the effectiveness of BPP designs. The objective of this study was to develop a novel, anatomically-accurate, finite element modeling framework, as a decision-making tool to evaluate and rate the biomechanical efficacy of BPPs in protecting the torso from battlefield-acquired non-penetrating impacts.
Methods:
To simulate a blunt impact with a BPP, two types of BPPs representing generic designs of threat-level III and IV plates, and a generic 5.56 mm bullet were modeled, based on their real dimensions, physical and mechanical characteristics (plate level-III is smaller, thinner, and lighter than plate level-IV). The model was validated by phantom testing.
Results:
Plate level-IV induced greater strains and stresses in the superficial tissues post the ballistic impact, due to the fact that it is larger, thicker and heavier than plate level-III; the shock wave which is transferred to the superficial tissues behind the BPP is greater in the case of a non-penetrating impact. For example - the area under volumetric tissue exposure histograms of strains and stresses for the skin and adipose tissues were 16.6-19.2% and 17.3-20.3% greater in the case of plate level-IV, for strains and stresses, respectively. The validation demonstrates a strong agreement between the physical phantom experiment and the simulation, with only a 6.37% difference between them.
Conclusions:
Our modelling provides a versatile, powerful testing framework for both industry and clients of BPPs at the prototype design phase, or for quantitative standardized evaluations of candidate products in purchasing decisions and bids.
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