地点：行健楼学术活动室526
邀请人：王锋副教授
Abstract: The integration of computer-aided design (CAD) and computer-aided engineering (CAE) requires solving partial differential equations (PDEs) over complex geometries and optimizing quantities of interest with respect to the geometric parameterization under physical constraints. In this talk, we will delve into artificial intelligence (AI)-enabled differentiable methods in CAD and CAE, which have the potential to address these challenges. In particular, we will introduce: (1) the random feature method for solving PDEs, which promises to be a robust method in terms of accuracy and geometric complexity; (2) AI-enabled differentiable method, which automates the structure optimization process with little manual intervention.
