Ballistic Impacts Experiments and Plastilina/Protection Systems’ Modeling

Gilson, L.; Rabet, L.; Imad, A.; Coghe, F.

doi:10.1007/978-3-030-34123-7_14

Cited by 1 publication

(1 citation statement)

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“…The Plastilina material model was implemented in a computational model of a drop test and compared with experimental results. Next, the same authors 21 used this material model to simulate ballistic tests and compared it with experimental results. They found that, at elevated strain rates, this approach overestimates the materials’ rigidity.…”

Section: Introductionmentioning

confidence: 99%

Behavior of oil-based modeling clay at medium strain rates

Hernández

Buchely

Casas-Rodríguez

et al. 2021

Journal of Defense Modeling & Simulation

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The modeling clay is an oil-based soft, flowable, and pliable material made from waxes and oils. Besides its primary use for making sculptures, the modeling clay is commonly used to evaluate bulletproof vests and simulate metal manufacturing processes by conformation. In ballistic tests, the clay is used to retain the deformation of the rear face of body armors; and in the study of metal forming processes, it is used as a physical model to provide information on the plastic flow. However, its mechanical dynamic behavior is not entirely understood. In this study, Plastilina Roma No. 1 modeling clay was mechanically characterized using the power-law constitutive model at medium strain rates [Formula: see text]. The material parameters were determined using a penetration model based on the Cavity Expansion Theory and an inverse technique involving the comparison of the model with experimentation. The optimum set of constitutive parameters was found by reducing the difference of the calculated penetration profile and the measurements from a drop test. This optimization process was programmed on the MATLAB–Simulink environment. The determined material parameters were validated by comparing the results from a computational model with three test set-ups. Finite element model results show good concordance with experimental measurements.

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Section: Introductionmentioning

confidence: 99%