Numerical Surrogate for Thoracic Blunt Non-Lethal Impact: Design and Validation.

  • KEBBAB, Younes (Ecole Militaire Polytechnique)
  • LOUAR, Mohamed Abderaouf (Ecole Militaire Polytechnique)
  • OUKARA, Amar (Ecole Militaire Polytechnique)
  • TRIA, Djalel Eddine (Ecole Militaire Polytechnique)

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Despite their non-lethal classification, kinetic energy non-lethal projectiles (KENLPs) can cause severe or fatal injuries, requiring reliable biomechanical assessment tools. To overcome the ethical, financial, and practical limitations of experimental testing, this study employs the explicit finite element solver LS-DYNA for thoracic impact analysis. A newly developed Simplified Thorax Finite Element Model (SThFEM) is proposed to reduce computational cost while preserving biomechanical relevance. The SThFEM follows NATO STANREC 4744 (AEP-99) guidelines and incorporates a three-layer architecture representing the muscle, lungs, and a central composite thoracic structure (sternum, costal cartilage, and ribs), enabling efficient and consistent assessment of KENLP thoracic impacts. The SThFEM was subjected to iterative calibration against Bir cases A–C. The model demonstrated high biofidelity in reproducing load transfer mechanisms, specifically governing sternal compression, across a ballistic velocity range of 20 m/s to 60 m/s. Validation was confirmed by the model’s adherence to established displacement-time and force-time corridors, in term of values and trend. The model’s predictive capacity is enhanced by the Viscous Criterion (VC), which identifies rate-dependent soft-tissue trauma occurring early in the impact event, often before maximum deformation. Results indicate that maintaining both VC and deflection within these validated bounds is critical for ensuring non-lethality. By offering a significant reduction in computational overhead compared to full human models, the SThFEM provides a reproducible tool for large-scale design screening and the establishment of safe operational limits for non-lethal weapon deployment.