Search

Abstract Cellular materials have drawn increasing interest in numerous applications due to their promising specific stiffness, strength and energy absorption capacity. In this work, a variety of rather novel lattice topologies pertinent to additive manufacturing are derived and examined. A number of these are derived by free-domain and constrained domain topology optimization procedures, while others are inspired by the triply periodic minimum surface (TPMS) sheet-based topologies. The topology optimization module utilized a single objective function of minimizing strain energy under linear elastic conditions. A total of fifteen different lattice topologies are investigated numerically, including both novel and conventional topologies (e.g. strut-based lattices) and their effective elastic properties are determined with respect to relative density through finite element analysis (FEA). Based on the preliminary FEA results, a number of these topologies are selected of which tessellated lattice structures are fabricated through laser powder bed fusion (LPBF) additive manufacturing technique out of Nylon thermoplastic material. The tessellated lattice structures are experimentally tested in compression and their mechanical performance, including uniaxial modulus, yield strength, and energy absorption capacity (EAC), is assessed. FEA simulations have been conducted using an elastic-plastic constitutive model for the Nylon base material. Both the experimental and numerical results reveal that the mechanical performance of the novel tube-based TPMS lattice P-100 and the combined loading (CL) topology derived through free-domain topology optimization surpasses all other topologies. P-100 uses a primitive TPMS with equal-length tubular connections in each direction, where the tubular length percentage compared to the primitive lattice size is 100%, while CL lattice topology is a free domain topology optimized under compressive loads on the centers of faces, edges, and vertices toward the center. The innovative lattice topologies proposed in the current study, particularly the P-100 and CL topologies, can become crucial in applications where it is necessary to improve the energy absorption capacity, such as sandwich panel cores, supports, and infills for 3D printed components. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pyramidal lattice structures (PLS) with I-shaped struts were 3D printed via DLP. • The utilization of I-shaped struts led to an increase in energy absorption of up to 68%. • Lateral buckling of the lattice struts was observed in the tailored PLS. • The measurements and observed collapse modes were in good agreement with FE predictions. • Specific cross-sectional designs can achieve enhancements in strength of up to 93%. This study examines the compressive response of geometrically tailored pyramidal lattice structures composed of struts with I-shaped cross-sections. Geometrically tailored pyramidal lattices with micro-scale features are 3D printed using the Digital Light Processing (DLP) technique, and their effective elastic modulus, collapse strength and energy absorption capacity are experimentally evaluated under quasi-static compressive loading. Furthermore, detailed non-linear finite element (FE) calculations are performed to examine underlying collapse mechanisms and explore the vast design space offered by the proposed geometrical tailoring scheme. Both the experimental and numerical results show that the geometrically tailored lattice structures outperform conventional pyramidal lattices of equal weight in terms of elastic modulus (+24 %), collapse strength (+21 %) and energy absorption (+68 %). Notably, these strength improvements are attributed to lateral buckling that prompts the I-shaped struts to bend sideways during collapse. Specific cross-sectional designs demonstrate remarkable enhancements in strength and energy absorption, reaching up to 93 % and 161 %, respectively, differentiating them significantly from conventional designs. [ABSTRACT FROM AUTHOR]

• Enhanced flexural properties of four point bend (4 PB) beam specimens through relative density gradation and hybridization based on TPMS topologies. • Strategies for gradation and hybridization deduced through stress state in 4 PB beam. • Hybridization and relative density gradation schemes is accomplished based on level-set functions of stretching-dominated TPMS sheet-based lattices. • Numerical results are validated through 4 PB testing on additive manufactured beams. • Enhanced flexural stiffness achieved by combining relative density gradation and hybridization with several different TPMS topologies. Due to the recent boom in digital design for additive manufacturing and 3D printing, there has been a significantly growing interest in latticed structures for light design and improved mechanical properties. However, the focus in the literature has mostly been on compressive mechanical properties of uniformly latticed structures with little emphasis on flexural properties of latticed-beams that are functionally graded and hybridized with different lattice topologies. Therefore, this paper aims to explore the effect of lattice relative density gradation and hybridization on the specific flexural properties of prominent sheet-based triply periodic minimal surfaces (TPMS) cellular four-point loaded beams. First, the effective elastic properties of the cubic porous topologies are evaluated computationally to converge to certain sheet-based TPMS cellular structures capable of providing high flexural properties. Schwartz primitive (P) revealed high stiffness to shear loading, meanwhile, the F-Rhombic Dodecahedron (FRD) showed better resistance to uniaxial loading, and the Diamond (D) showed well-combined uniaxial and shear moduli. The selected four-point bend (4 PB) latticed-beams are functionally graded following a bilinear pattern and hybridized through the span of their length inspired by the shearing force and bending moment diagrams arising in the 4 PB beam, in view of the effective elastic properties of the TPMS topologies. The additively manufactured AlSi10Mg uniform, functionally-graded, and hybridized latticed-beams are tested in four-point bending and the results are compared with the finite element results. Both the experimental and numerical outcomes show good agreement within the elastic-plastic regime. From experimental results, it is found that functional grading and hybridization can considerably enhance the specific flexural modulus of sheet-based TPMS latticed-beams. Also, relative density gradation within the four-point bend specimens proved very essential in deflecting crack growth thereby retarding the final failure, meanwhile hybridization is conveyed to mitigate shear-band failure. Combination of functional gradation and hybridization on the latticed-beams resulted in a significant increase in the specific flexural stiffness. Therefore, this study provides guidelines on how to enhance the flexural properties of lightweight beams through lattice functional grading and hybridization. [Display omitted] [ABSTRACT FROM AUTHOR]

Metamaterials are architected cellular materials, also known as lattice materials, that are inspired by nature or human engineering intuition, and provide multifunctional attributes that cannot be achieved by conventional polymeric materials and composites. There has been an increasing interest in the design, fabrication, and testing of polymeric metamaterials due to the recent advances in digital design methods, additive manufacturing techniques, and machine learning algorithms. To this end, the present review assembles a collection of recent research on the design, fabrication and testing of polymeric metamaterials, and it can act as a reference for future engineering applications as it categorizes the mechanical properties of existing polymeric metamaterials from literature. The research within this study reveals there is a need to develop more expedient and straightforward methods for designing metamaterials, similar to the implicitly created TPMS lattices. Additionally, more research on polymeric metamaterials under more complex loading scenarios is required to better understand their behavior. Using the right machine learning algorithms in the additive manufacturing process of metamaterials can alleviate many of the current difficulties, enabling more precise and effective production with product quality. [ABSTRACT FROM AUTHOR]