Enhancing helmet pressure sensing with advanced 3D printed gyroid architectures - Chao Bao; Danielle Jaye Agron; Taeil Kim; Chris Vattathichirayi; Edwin L. Thomas; Woo Soo Kim (Materials & Design)
The gyroid structure, known for its exceptional strength and energy absorption, is ideal for 3D printing applications due to its self-supporting capability. Existing simulation models often overlook the complexities of the 3D printing process, leading to discrepancies between isotropic models and empirical data. To address this, we introduce a representative elementary volume (RVE) simulation model to accurately represent the fused layers from the Fused Deposition Modeling (FDM) process. By establishing Young’s modulus of the fused layer at 48.7 % of pure matrix material, we enhance the model’s accuracy to align with experimental data. We explore energy buffering within the triply periodic minimal surface (TPMS) gyroid model. A new design featuring a thin gyroid TPMS structure with double hollow struts improves energy absorption while enhancing overall efficiency. Additionally, we develop a G slab-based capacitive pressure sensor using advanced robotic 3D printing technology, achieving an impressive pressure sensitivity of 78.43 MPa−1 in the range of 0–0.060 MPa, with a sensitivity of 13.72 MPa−1 at operational pressures up to 0.181 MPa. This culminates in the creation of a smart helmet that effectively detects critical pressure changes, advancing protective headgear technology.