From density to CAD: Automatic and robust CAD model generation of topology optimization results via sparse optimization

Abstract

Topology optimization (TO) is a mature design technique that provides a conceptual design with the desired structural performance. However, the raw TO results cannot be interactively fine-tuned for conceptual design or further post-processing. This paper proposes an automatic and effective framework that can convert TO results into editable CAD models. The marching cubes algorithm is utilized to obtain discrete boundary points, which are subsequently transformed into CAD format via the sparse curve fitting technique. The proposed framework ensures robust and automatic reconstruction of the TO results of macrostructures and microstructures, especially complex small-scale structures with tiny holes and a few extracted points. We developed a Rhino plug-in, facilitating designers to modify the structural layout and intuitively assess the performance of the editable structures. Furthermore, we address stress concentrations by editing the reconstructed CAD models to illustrate the application of the proposed method.