Data-Driven Computational Design of Engineered Material Systems
ABSTRACT: Design of advanced material systems imposes challenges in integrating knowledge and representation from multiple disciplines and domains such as materials, manufacturing, structural mechanics, and design optimization. Data-driven machine learning and computational design methods provide a seamless integration of predictive materials modeling, manufacturing, and design optimization to enable the accelerated design and deployment of advanced materials systems. In this talk, Chen introduces state-of-the-art data-driven methods for designing heterogeneous nano- and microstructural materials and complex multiscale metamaterial systems. Research developments in design representation, design evaluation, and design synthesis will be introduced with novel design methods that integrate machine learning, mixed-variable Gaussian process modeling, Bayesian optimization, and topology optimization. Challenges and opportunities in designing engineered material systems are discussed.
SPEAKER: Wei Chen is the Wilson-Cook Professor in Engineering Design and Chair of the Department of Mechanical Engineering at Northwestern University. Directing the Integrated DEsign Automation Laboratory (IDEAL), her current research involves the use of statistical inference, machine learning, and uncertainty quantification techniques for design of emerging materials systems including microstructural materials, metamaterials, and programmable materials. She serves as the Design Thrust lead for the newly funded NSF Engineering Research Center (ERC) on Hybrid Autonomous Manufacturing, Moving from Evolution to Revolution (HAMMER), where she works on digital twin systems for concurrent materials and manufacturing process design. Dr. Chen is an elected member of the National Academy of Engineering (NAE) and currently serves as the President of the International Society of Structural and Multidisciplinary Optimization (ISSMO). She served as Editor-in-Chief of the ASME Journal of Mechanical Design and the Chair of the ASME Design Engineering Division (DED). Chen is the recipient of the 2022 Engineering Science Medal from the Society of Engineering Science (SES), ASME Pi Tau Sigma Charles Russ Richards Memorial Award (2021), ASME Design Automation Award (2015), Intelligent Optimal Design Prize (2005), ASME Pi Tau Sigma Gold Medal achievement award (1998), and the NSF Faculty Career Award (1996). She received her Ph.D. from the Georgia Institute of Technology in 1995.