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Recent Developments in Additively Manufactured Crash Boxes: Geometric Design Innovations, Material Behavior, and Manufacturing Techniques

Ahmed Saber, A. M. Amer, Ali I. Shehata, Hassan Elgamal, A. Abd_Elsalam

2025Applied Sciences15 citationsDOIOpen Access PDF

Abstract

Crash boxes play a vital role in improving vehicle safety by absorbing collision energy and reducing the forces transmitted to occupants. Additive manufacturing (AM) has become a powerful method for developing advanced crash boxes by enabling complex geometries. This review provides a comprehensive examination of recent progress in AM crash boxes, with a focus on three key aspects: geometric design innovations, material behavior, and manufacturing techniques. The review investigates the influence of various AM-enabled structural configurations, including tubular, origami-inspired, lattice, and bio-inspired designs, on crashworthiness performance. Among these, bio-inspired structures exhibit superior energy absorption characteristics, achieving a mean specific energy absorption (SEA) of 21.51 J/g. Material selection is also explored, covering polymers, fiber-reinforced polymers, metals, and multi-material structures. Metallic AM crash boxes demonstrate the highest energy absorption capacity, with a mean SEA of 28.65 J/g. In addition, the performance of different AM technologies is evaluated, including Stereolithography (SLA), Material Jetting (MJT), Selective Laser Melting (SLM), Selective Laser Sintering (SLS), Fused Deposition Modeling (FDM), and hybrid manufacturing techniques. Among these, crash boxes produced by SLM show the most favorable energy absorption performance, with a mean SEA of 16.50 J/g. The findings presented in this review offer critical insights to guide future research and development in the design and manufacturing of next-generation AM crash boxes intended to enhance vehicle safety.

Topics & Concepts

EngineeringComputer scienceAdditive Manufacturing and 3D Printing TechnologiesCellular and Composite StructuresManufacturing Process and Optimization
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