Topology Optimization and 3D Printing of Steel Joints by SJ-BESO and FDM Method

Abstract

The problems of low computational efficiency and checkerboard phenomenon in optimizing steel joints with the bi-directional evolutionary structural optimization (BESO) method are intractable, which usually leads to failure to achieve optimized solutions even after spending long calculation time. This paper proposes an improved algorithm based on the BESO theory for steel joints (SJ-BESO) by utilizing a sensitivity filtering radius to weight the sensitivity values of each element. And a sensitivity threshold segment is proposed to determine the deletion or addition of elements. Additionally, a convergence parameter is developed to ensure the stability of the optimization calculation. Several real-word examples of steel joints are provided to illustrate the proposed method. The results show that the improved BESO algorithm not only reduces the number of iterations, but also produces ideal structures with good stiffness. The 3D printing manufacturing of the example model verifies the manufacturability of the obtained designs and enhances its intuitive understanding. The SJ-BESO is applicable and promising for the topology optimization of steel joints.