2 citations · 3 across the 3 of their papers we have counts for
3 papers
A physics-aware deep learning model for shear band formation around collapsing pores in shocked reactive materials
Xinlun Cheng, Bingzhe Chen, Joseph Choi +5
Modeling shock-to-detonation phenomena in energetic materials (EMs) requires capturing complex physical processes such as strong shocks, rapid changes in microstructural morphology…
On resolving meso-scale calculations of pore-collapse-generated hotspots in energetic crystals for consistency with atomistic models
Chukwudubem Okafor, Jacob Herrin, Catalin R. Picu +4
Meso-scale calculations of pore collapse and hotspot formation in energetic crystals provide closure models to macro-scale hydrocodes for predicting the shock sensitivity of energe…
Challenges and opportunities for machine learning in multiscale computational modeling
Phong C. H. Nguyen, Joseph B. Choi, H. S. Udaykumar +1
Many mechanical engineering applications call for multiscale computational modeling and simulation. However, solving for complex multiscale systems remains computationally onerous…