Data-Driven Multi-Scale Simulations for Materials-by-Design of Energetic Materials
Inside Livermore Lab via YouTube
Google Data Analytics, IBM AI & Meta Marketing — All in One Subscription
Learn Backend Development Part-Time, Online
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore multi-scale modeling of energetic material sensitivity in this 1-hour 10-minute webinar from Inside Livermore Lab. Delve into the telescoping physics from nano- to macro-scales, learning how machine learning algorithms bridge scales in multi-scale simulations. Discover data-driven closures for upscaling key localization physics from subgrid scales. Examine structure-property-performance relationships through surrogate modeling and deep learning approaches. Investigate in silico frameworks for microstructure optimization, and explore transfer learning and multi-fidelity modeling strategies for cross-species applications in energetic materials. Gain insights from Udaykumar, Roy J. Carver Professor of mechanical engineering and Associate Dean at the University of Iowa, as he shares his expertise in multi-scale modeling and simulation of moving boundary problems in thermomechanical systems.
Syllabus
DDPS | Data-driven multi-scale simulations for materials-by-design of energetic materials |Udaykumar
Taught by
Inside Livermore Lab