# Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing
###### Abstract  
At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1-2.3% smaller than that obtained by isotropic optimization. additive manufacturing; space nodes; BESO method; anisotropy; SLM Article  
[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing  
distribution for optimizing topology (SEMDOT) [10] can generate a clear and smooth boundary representation. These methods break the limitation of the finite element mesh to enable researchers to get a relatively accurate model boundary. This can be considered a significant key for promoting topology optimization in engineering. Additive manufacturing technology is well known in the form of 3D printing, which enables the direct fabrication of topologically optimized structures. [PERSON] et al. [11] pointed out that the biggest bottleneck of the application of typical topology optimization methods to additive manufacturing is that the additive manufacturing constraints are not considered. However, with the development of technologies, some researchers have found some methods to solve the problems where the overhanging part of the structure may collapse during manufacture, and topology results are not smooth. For example, [PERSON] [12] developed an AM filter to overcome the overhanging angle problem by combining a layer-wise nonlinear spatial filtering scheme using the SIMP method. [PERSON] and [PERSON] et al. [13] developed a sub-support method for cone density filtering based on the SIMP method. Both methods have been used in commercial software. In recent years, [PERSON] et al. developed a new SIMP-based method by integrating [PERSON]'s AM filter, which is capable of generating smooth boundaries [14]. In addition, [PERSON] et al. thoroughly investigated the influences of parameters including the filter radius, mesh size, and target volume fraction on the performance and manufacturability of smooth self-supporting topologies [15]. Importantly, these methods have been validated in practical manufacturing, and the manufacturing of topology optimization results is no longer affected by the shape of complex structures. These advanced studies have brought AM and topology optimization closer together. Although topology optimization and additive manufacturing have only been used in fields with high-precision requirements such as high-end equipment and aerospace for a long time [16], with the advancement of additive manufacturing technology and the in-depth study of topology optimization design, many researchers have turned their attention to other industrial designs that can combine topology optimization and additive manufacturing. As a prefabricated building, space structure is one of the application directions of additive manufacturing and topology optimization.