Isogeometric multi-patch topology optimization based on pix2pix

Abstract

We present a novel approach that combines the power of pix2pix, an image-to-image translation framework, with the advanced capabilities of isogeometric multi-patch analysis for topology optimization. The proposed method adds the Nitsche’s methods into the advantages of Isogeometric analysis (IGA), thus gaining the ability to handle complex geometries by generating locally smooth and well-converged results. Additionally, the usage of generative adversarial network based pix2pix allows for a more efficient representation of the design space, reducing the computational cost of the optimization process. This approach has shown promising results in various numerical examples. This technique aims to improve the efficiency of conceptual design in complex engineering applications.