In this talk, we will present an efficient framework algorithm for topology optimization problems, where the interface is implicitly represented by indicator functions. Based on the indicator function representation, we construct a concave approximation and relaxation to the original problem and develop an unconditional stable algorithm. Many applications including fluid flow optimization, flow network formation, and heat sink design will be discussed.
Short Bio: Dong Wang is an Assistant Professor in the School of Science and Engineering at the Chinese University of Hong Kong (Shenzhen). He has broad interests in analytical and computational methods for problems in applied mathematics, especially in computational fluid dynamics, computational material science, image processing, optimization and machine learning. After receiving his Bachelor degree in Mathematics from Sichuan University in 2013, Dong earned his Ph.D. in Applied Mathematics at the Hong Kong University of Science and Technology in 2017. Before moving to CUHK(SZ), he was an Assistant Professor Lecturer in the Department of Mathematics at the University of Utah.