Isogeometric multi-patch topology optimization based on pix2pix

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