“…The compressive stress increased almost linearly with increasing stress until stress occurred that was accompanied by an overall elastic deformation of the cell walls. From this linear elastic range, the modulus of elasticity was determined according to the methodology [ 44 , 45 ]. As a result of the loading, the cell edge struts stretched and the "cell face" bent [ 46 ].…”
The development of additive technology has made it possible to produce metamaterials with a regularly recurring structure, the properties of which can be controlled, predicted, and purposefully implemented into the core of components used in various industries. Therefore, knowing the properties and behavior of these structures is a very important aspect in their application in real practice from the aspects of safety and operational reliability. This article deals with the effect of cell size and volume ratio of a body-centered cubic (BCC) lattice structure made from Acrylonitrile Butadiene Styrene (ABS) plastic on mechanical vibration damping and compression properties. The samples were produced in three sizes of a basic cell and three volume ratios by the fused deposition modeling (FDM) technique. Vibration damping properties of the tested 3D-printed ABS samples were investigated under harmonic excitation at three employed inertial masses. The metamaterial behavior and response under compressive loading were studied under a uniaxial full range (up to failure) quasi-static compression test. Based on the experimental data, a correlation between the investigated ABS samples’ stiffness evaluated through both compressive stress and mechanical vibration damping can be found.
“…The compressive stress increased almost linearly with increasing stress until stress occurred that was accompanied by an overall elastic deformation of the cell walls. From this linear elastic range, the modulus of elasticity was determined according to the methodology [ 44 , 45 ]. As a result of the loading, the cell edge struts stretched and the "cell face" bent [ 46 ].…”
The development of additive technology has made it possible to produce metamaterials with a regularly recurring structure, the properties of which can be controlled, predicted, and purposefully implemented into the core of components used in various industries. Therefore, knowing the properties and behavior of these structures is a very important aspect in their application in real practice from the aspects of safety and operational reliability. This article deals with the effect of cell size and volume ratio of a body-centered cubic (BCC) lattice structure made from Acrylonitrile Butadiene Styrene (ABS) plastic on mechanical vibration damping and compression properties. The samples were produced in three sizes of a basic cell and three volume ratios by the fused deposition modeling (FDM) technique. Vibration damping properties of the tested 3D-printed ABS samples were investigated under harmonic excitation at three employed inertial masses. The metamaterial behavior and response under compressive loading were studied under a uniaxial full range (up to failure) quasi-static compression test. Based on the experimental data, a correlation between the investigated ABS samples’ stiffness evaluated through both compressive stress and mechanical vibration damping can be found.
“…As explained in recent studies, the Gibson–Ashby mathematical model for open cell foams indicates a linear correlation between the elastic modulus and the square of porosity [ 62 , 64 , 65 ]. Depends on the lattice geometry, it was found that the m coefficient can range between 0.1 and 4.0 [ 26 ].…”
The demand of lattice structures for medical applications is increasing due to their ability to accelerate the osseointegration process, to reduce the implant weight and the stiffness. Selective laser melting (SLM) process offers the possibility to manufacture directly complex lattice applications, but there are a few studies that have focused on biocompatible Ti6Al7Nb alloy. The purpose of this work was to investigate the physical–mechanical properties and the microstructure of three dissimilar lattice structures that were SLM-manufactured by using Ti6Al7Nb powder. In particular, the strut morphology, the fracture characterization, the metallographic structure, and the X-ray phase identification were analyzed. Additionally, the Gibson-Ashby prediction model was adapted for each lattice topology, indicating the theoretical compressive strength and Young modulus. The resulted porosity of these lattice structures was approximately 56%, and the pore size ranged from 0.40 to 0.91 mm. Under quasi-static compression test, three failure modes were recorded. Compared to fully solid specimens, the actual lattice structures reduce the elastic modulus from 104 to 6–28 GPa. The struts surfaces were covered by a large amount of partial melted grains. Some solidification defects were recorded in struts structure. The fractographs revealed a brittle rupture of struts, and their microstructure was mainly α’ martensite with columnar grains. The results demonstrate the suitability of manufacturing lattice structures made of Ti6Al7Nb powder having unique physical–mechanical properties which could meet the medical requirements.
“…As known, the mechanical properties of AM lattices are essentially determined by the qualities of the materials used to create them. Another consideration is the structure’s topology [ 6 ]. For a potential application, a material such as metals and alloys [ 7 , 8 ], composites, polymers, glass, ceramics, etc., and their lattice structures [ 8 ] are evaluated for their effectiveness in terms of their phase field performance [ 9 ], corrosion [ 10 , 11 ], mechanical properties, microstructure [ 12 ], fracture [ 13 ] as well as fatigue behavior [ 14 ] depending on that application.…”
Extensive amount of research on additively manufactured (AM) lattice structures has been made to develop a generalized model that can interpret how strongly operational variables affect mechanical properties. However, the currently used techniques such as physics models and multi-physics simulations provide a specific interpretation of those qualities, and are not general enough to assess the mechanical properties of AM lattice structures of different topologies produced on different materials via several fabrication methods. To tackle this problem, this study develops an optimal deep learning (DL) model based on more than 4000 data points, which has been optimized by analyzing three different hyper-parameters optimization schemes including gradient boost regression trees (GBRT), gaussian process (GP), and random forest (RF) with different data distribution schemes such as normal distribution, nth root transformation, and robust scaler. With the robust scaler and nth root transformation, the accuracy of the model increases from R2 = 0.85 (for simple distribution) to R2 = 0.94 and R2 = 0.88, respectively. After feature engineering and data correlation, the stress, unit cell size, total height, width, and relative density are chosen to be the input parameters to model the strain. The optimal DL model is able to predict the strain of different topologies of lattices (such as circular, octagonal, Gyroid, truncated cube, Truncated cuboctahedron, Rhombic do-decahedron, and many others) with decent accuracy (R2 = 0.936, MAE = 0.05, and MSE = 0.025). The parametric sensitivity analysis and explainable artificial intelligence (by using DeepSHAP library) based insights confirm that stress is the most sensitive input to the strain followed by the relative density from the modeling perspective of the AM lattices. The findings of this study would be helpful for the industry and the researchers to design AM lattice structures of different topologies for various engineering applications.
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