Data-Driven Multi-Scale Simulations for Materials-by-Design of Energetic Materials

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.

DDPS | Data-driven multi-scale simulations for materials-by-design of energetic materials |Udaykumar