Speech Title: Automation in and through
Reconfigurable Structures with Embodied
Modular Programmability and Mechano-Intelligence
Prof. Kon-Well Wang
Fellow of the American Society of Mechanical Engineers (ASME), American Association for the Advancement of Science (AAAS), and Institute of Physics (IOP)
A. Galip Ulsoy Distinguished University Professor of Engineering and Stephen P. Timoshenko Professor of Mechanical Engineering
Department of Mechanical Engineering
University of Michigan
Ann Arbor, MI, USA
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 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 automation, 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 concurrently embed computing power and functional intelligence, such as perception, learning, memorizing, decision-making and execution, 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/vibration controls to self-learning-self-tuning intelligence and autonomy.
Bio
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, vibration, 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 various 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 American Society of Mechanical Engineers (ASME), American Association for the Advancement of Science (AAAS), and Institute of Physics (IOP).