Additive manufacturing technology can make products of arbitrary shapes, greatly expanding the design space of lattice structures. Compared with traditional solid lattice structures, the lattice structures with hollow struts have higher flexural strength, which arouses interests of designers recently. However, owing to the more complex shapes of structures, the model generation and design are facing more challenges. In this article, a novel generative design method for the creation of lattice structures with hollow struts is proposed. This method consists of three stages: initialization, analysis, and optimization. First of all, a ground structure is generated automatically based on initial conditions. Then, the finite element analysis is used to get the stress and coordinate information of finite element nodes as well as deformation information of the ground structure. At last, a rapid optimization method is presented based on the idea of mapping the strut equivalent stress to the strut wall thickness to optimize materials distribution. The proposed method is validated through a case study, demonstrating that this method can enhance performance of products while reducing the complexity of the optimization problem.

Metallic additive manufacturing process parameters, such as inclination angle and minimum radius, impose constraints on the printable lattice cell configurations in complex components. As a result, their mechanical properties are usually lower than their design values. Meanwhile, due to unavoidable process constraints (e.g., additional support structure), engineering structures filled with various lattice cells usually fail to be printed or cannot achieve the designed mechanical performances. Optimizing the cell configuration and printing process are effective ways to solve these problems, but this is becoming more and more difficult and costly with the increasing demand for properties. Therefore, it is very important to redesign the existing printable lattice structures to improve their mechanical properties. In this paper, inspired by the macro- and meso-structures of bamboo, a bionic lattice structure was partitioned, and the cell rod had a radius gradient, similar to the macro-scale bamboo joint and meso-scale bamboo tube, respectively. Experimental and simulated results showed that this design can significantly enhance the mechanical properties without adding mass and changing the printable cell configuration. Finally, the compression and shear properties of the Bambusa-lattice structure were analyzed. Compared with the original scheme, the bamboo lattice structure design can improve the strength by 1.51 times ($\beta =1.5$). This proposed strategy offers an effective pathway to manipulate the mechanical properties of lattice structures simultaneously, which is useful for practical applications.

In order to solve the problem of substantial computational resources of lattice structure during optimization, a local relative density mapping (LRDM) method is proposed. The proposed method uses solid isotropic microstructures with penalization to optimize a model at the macroscopic scale. The local relative density information is obtained from the topology optimization result. The contour lines of an optimized model are extracted using a density contour approach, and the triangular mesh is generated using a mesh generator. A local mapping relationship between the elements’ relative density and the struts’ relative cross-sectional area is established to automatically determine the diameter of each individual strut in the lattice structures. The proposed LRDM method can be applied to local finite element meshes and local density elements, but it is also suitable for global ones. In addition, some cases are considered in order to test the effectiveness of the LRDM method. The results show that the solution time of the LRDM is lower than the RDM method by approximately 50%. The proposed method provides instructions for the design of more complex lattice structures.