Despite their classification as "non-lethal," Kinetic Energy Non-Lethal Projectiles (KENLPs) still causing fatal injuries, necessitating rigorous biomechanical assessment. Ethical and technical limits of Post Mortem Human Subjects (PMHS) and experimental testing have elevated Finite Element Human Body Models (HBMs) for blunt trauma research. This study develops a two-stage numerical framework for cranial and thoracic injury prediction using LS-DYNA. Firstly, Hybrid III (H3) sub-models are validated against the Ballistics Load Sensing Headform (BLSH) envelope and NATO STANREC 4744 (AEP-99) thorax guidelines using validated KENLPs. Building upon these validations, the second stage proposes the Simplified Head (SH-FEM), featuring a dual-layer scalp and skull architecture, and the Simplified Thorax (STh-FEM)-a three-layer construct comprising muscle, a lung slab, and a central skeletal structure preserving dominant load paths while reducing computational cost. Simulation results indicate peak forces scale nonlinearly from 0.82 to 16.03 kN across 20-80 m⋅s⁻¹, with neck coupling reducing peaks by 20-30%. A velocity inflection at 40 m⋅s⁻¹ marks sub-concussive-to-injurious transitions: 55 m⋅s⁻¹ exceeds 7.5 kN (fracture/coma). For thoracic impacts across Cases A-E, VCmax-based AIS ≥ 2 risks vary by model and projectile. In Case E, STh-FEM predicted 46% risk versus H3 at 91%; in Case C, values were 10% and 52%, respectively. Furthermore, STh-FEM overpredicted rigid PVC projectile forces (98% in Case C) but matched the deformable SIR-X projectile (∼8 kN peaks). These simplified models demonstrate controlled, reproducible responses, confirming their feasibility as performant alternatives for rapid KENLPs design screening and safety assessment.
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Younes Kebbab
Amar Oukara
Mohamed Abderaouf Louar
Computer Methods in Biomechanics & Biomedical Engineering
École Polytechnique
Laboratoire de Tribologie et Dynamique des Systèmes
Polytechnic School of Algiers
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Kebbab et al. (Sat,) studied this question.
www.synapsesocial.com/papers/69e7138bcb99343efc98d02e — DOI: https://doi.org/10.1080/10255842.2026.2658117