Identifying boundaries of topology optimization results using basic parametric features

Topology optimization yields an overall layout of a structure in the form of discrete densities or continuous boundaries. One of important drawbacks, however, is that a serious gap exists between the topology results (e.g., greyscale images with irregular shapes) and parameterized CAD models that are ready for subsequent optimization and manufacturing. Without the corresponding CAD model, topology optimization design is difficult to be interpreted for manufacturing, as well as to be utilized in subsequent applications such as section and shape optimization. It is considered the most significant bottleneck to interpret topology optimization results and to produce a parameterized CAD model that can be used for subsequent optimization. The objective of this paper is to extract geometric features out of topology designs for parameterized CAD models with minimal manual intervention. The active contour method is first used to extract boundary segments from topology geometry. Using the information of roundness and curvature of segments, basic geometric features, such as lines, arcs, circles and fillets, are then identified. An optimization method is used to find parameters of these geometric features by minimizing errors between the boundary of geometric features and corresponding segments. Lastly, using the parameterized CAD model, section optimization is performed for beam-like structures, and surrogate-based shape optimization is employed to determine the final shapes. The entire process is automated with MATLAB and Python scripts in Abaqus, while manual intervention is needed only when defining geometric constraints and design parameters. Three examples are presented to demonstrate effectiveness of the proposed methods.