Harnessing the Dynamics of Reconfigurable Metastructures - From Wave Control to Embodying Mechano-Intelligence

an illustration of a futuristic structure

Department of Mechanical Engineering

Location: Babbio 320

Speaker: Kon-Well Wang, A. Galip Ulsoy Distinguished University Professor of Engineering and Stephen P. Timoshenko Professor of Mechanical Engineering | University of Michigan

ABSTRACT

In recent years, the concept of reconfigurable matter developed based on nature-inspired modular architectures has been explored to create advanced engineering systems. For example, inspired by the observation that some of skeletal muscle's intriguing macroscale functionalities result from the assembly of nanoscale cross-bridge constituents with metastability, the idea of synthesizing metastructures from the integration of mechanical metastable modules has been pursued. In another example, inspired by the physics behind the plant nastic movements and the rich designs of origami folding, a class of metastructures is created building on the innovation of fluidic-origami modular elements. Overall, the modules are designed to be reconfigurable in their shape, mechanical properties, and stability features, so to produce synergistic and intriguing dynamic functionalities at the system level, such as programmable phononic bandgap control and nontraditional wave steering. More recently, with the rapid advances in high-performance intelligent systems, we are witnessing a prominent demand for the next generation of mechanical matter to have much more built-in intelligence and autonomy. An emerging direction is to pioneer and harness the metastructures’ high dimensionality, multiple stability, and nonlinearity for mechano-intelligence via physical computing. That is, we aim to embody computing power and functional intelligence, such as perception, learning, memorizing, decision-making and execution, concurrently and directly in the mechanical domain, advancing from conventional systems that solely rely on add-on digital computer to achieve intelligence. This presentation will highlight some of these advancements in harnessing reconfigurable matter for structural dynamics tailoring, from adaptive wave and vibration controls to self-learning-self-tuning intelligence.

BIOGRAPHY

Headshot of Professor Kon-Well Wang

Dr. Kon-Well Wang is the A. Galip Ulsoy Distinguished University Professor of Engineering and Stephen P. Timoshenko Professor of Mechanical Engineering (ME) at the University of Michigan (U-M). He has been the U-M ME Department Chair from 2008 to 2018, and has served as a Division Director at the U.S. National Science Foundation for two years, 2019-20, via an Executive Intergovernmental Personnel Act appointment. Wang received his Ph.D. degree from the University of California, Berkeley, worked at the General Motors Research Labs as a Sr. Research Engineer, and started his academic career at the Pennsylvania State University in 1988. At Penn State, Wang has served as the William E. Diefenderfer Chaired Professor, co-founder and Associate Director of the Vertical Lift Research Center of Excellence, and a Group Leader for the Center for Acoustics & Vibration. He joined the U-M in 2008. Wang’s main technical interests are in structural dynamics and controls, especially in the emerging field of intelligent structural & material systems, with applications in vibration, acoustic & wave controls, energy harvesting, and sensing & monitoring. He has received numerous recognitions, such as the ASME Rayleigh Lecture Award, the Pi Tau Sigma-ASME Charles Russ Richards Memorial Award, the ASME J.P. Den Hartog Award, the SPIE Smart Structures and Materials Lifetime Achievement Award, the ASME Adaptive Structures and Materials Systems Prize, the ASME N.O. Myklestad Award, the ASME Rudolf Kalman Award, and several other best paper awards. He has been the Editor in Chief for the ASME Journal of Vibration & Acoustics, and an Associate Editor or Editorial Board Member for various journals. Wang is a Fellow of the ASME, AAAS, IOP, and RAeS.


For questions about the speaker, contact Prof. Long Wang.