Compressive Properties Anisotropy of BCC Lattice Structure Formed by Fused Deposition Modeling

LI Bin, GU Hai, ZHANG Jie, JIANG Jie, ZHANG Hao, LU Ye-hua

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Plastics Science and Technology ›› 2024, Vol. 52 ›› Issue (11) : 111-116. DOI: 10.15925/j.cnki.issn1005-3360.2024.11.022
Process and Control

Compressive Properties Anisotropy of BCC Lattice Structure Formed by Fused Deposition Modeling

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Abstract

The 1×1, 1×2 and 2×2 lattice structures were designed based on body-centered cubic (BCC) lattice structure. The 1×1 lattice structures with 80% and 100% filling rate and the 1×2 and 2×2 lattice structures with 100% filling rate were prepared by fused deposition modeling (FDM) technology, and compression tests were carried out in 0° and 90° directions for the lattice structures, respectively. The anisotropy of compressive properties under different filling rates and different number of lattice units were studied. The results show that the lattice structures exhibit a fracture pattern characterized by cracking along the stacking surface of the formed material. The compressive strength, compressive modulus and total energy absorption of the 2×2 lattice structure at 90° compression are the largest, reaching 0.34 MPa, 7.85 MPa and 4.31 J, respectively, which are increased by 13.3%, 11.2% and 10.4% compared with that at 0°, respectively. The 2×2 lattice structure demonstrates superior energy absorption characteristics under 5% strain. The 1×1 lattice structure with 100% filling rate has the highest specific absorption energy at 90° compression, reaching 206.15 J/kg, which is 30.66% higher than that at 0°. The anisotropy of the mechanical properties of the BCC lattice structure is studied, which provides a basis for the engineering application of the lattice structure formed by FDM process.

Key words

Fused deposition modeling / Body-centered cubic / Lattice structure / Compressive properties / Anisotropy

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LI Bin , GU Hai , ZHANG Jie , et al . Compressive Properties Anisotropy of BCC Lattice Structure Formed by Fused Deposition Modeling. Plastics Science and Technology. 2024, 52(11): 111-116 https://doi.org/10.15925/j.cnki.issn1005-3360.2024.11.022

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