Seminar: Topology Optimization for Additive Manufacturing

Abstract

Additive manufacturing (AM) is capable of building parts of complex shapes that are difficult to produce with conventional manufacturing processes. Such shape flexibility opens up unprecedented design possibilities and has disruptive potentials for multiple technological fields. To unleash full potentials of the AM technology, computer methods that enable systematical exploration of such enlarged design space are thus needed.
In this talk, I will present our recent work in applying topology optimization to explore large design space enabled by AM. A density-gradient based formulation has been developed to account for AM constraints during topology optimization. It can control undercut and overhang angle in the optimized designs so they can be printed without support structures. It can also identify optimal build directions.
I will also present our recent work on topology optimization of conjugate heat transfer systems. Adjoint formulations for Navier-Stokes equations and convective heat transfer equations are derived to obtain the gradient for optimization. Numerical result shows that topologically optimized heat sinks significantly outperform conventional heat sinks in pressure drop and heat dissipation.

About the speaker

Xiaoping Qian is Professor in the Department of Mechanical Engineering at the University of Wisconsin-Madison. His research focuses on computational design of multi-physics systems, topology optimization, shape optimization, and design for additive manufacturing. His research has been supported by federal funding agencies such as AFOSR, ARO, ONR and NSF as well as private industries such as UTRC and GE. He has served as an associate editor for ASME Journal of Mechanical Design, Journal of Computing and Information Science in Engineering, Journal of Manufacturing Science and Engineering and journal Computer-Aided Design. He is an ASME fellow.

Hosted by Prof. Jami Shah.