Challenges and opportunities for machine learning in multiscale computational modeling
PCH Nguyen, JB Choi… - … of Computing and …, 2023 - asmedigitalcollection.asme.org
Many mechanical engineering applications call for multiscale computational modeling and
simulation. However, solving for complex multiscale systems remains computationally …
simulation. However, solving for complex multiscale systems remains computationally …
Convolutional neural networks for large-scale dynamical modeling of itinerant magnets
Complex spin textures in itinerant electron magnets hold promises for next-generation
memory and information technology. The long-ranged and often frustrated electron …
memory and information technology. The long-ranged and often frustrated electron …
[HTML][HTML] Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry
RSAE Ali, J Meng, MEI Khan, X Jiang - Artificial Intelligence Chemistry, 2024 - Elsevier
Artificial intelligence (AI) is driving a revolution in chemistry, reshaping the landscape of
molecular design. This review explores AI's pivotal roles in the field of organic synthesis …
molecular design. This review explores AI's pivotal roles in the field of organic synthesis …
Data-scarce surrogate modeling of shock-induced pore collapse process
Understanding the mechanisms of shock-induced pore collapse is of great interest in
various disciplines in sciences and engineering, including materials science, biological …
various disciplines in sciences and engineering, including materials science, biological …
PARCv2: Physics-aware recurrent convolutional neural networks for spatiotemporal dynamics modeling
Modeling unsteady, fast transient, and advection-dominated physics problems is a pressing
challenge for physics-aware deep learning (PADL). The physics of complex systems is …
challenge for physics-aware deep learning (PADL). The physics of complex systems is …
Mapping microstructure to shock-induced temperature fields using deep learning
The response of materials to shock loading is important to planetary science, aerospace
engineering, and energetic materials. Thermally activated processes, including chemical …
engineering, and energetic materials. Thermally activated processes, including chemical …
Multi-scale modeling of shock initiation of a pressed energetic material III: Effect of Arrhenius chemical kinetic rates on macro-scale shock sensitivity
Multi-scale predictive models for the shock sensitivity of energetic materials connect energy
localization (“hotspots”) in the microstructure to macro-scale detonation phenomena …
localization (“hotspots”) in the microstructure to macro-scale detonation phenomena …
Physically evocative meso-informed sub-grid source term for energy localization in shocked heterogeneous energetic materials
Reactive burn models for heterogeneous energetic materials (EMs) must account for
chemistry as well as microstructure to predict shock-to-detonation transition (SDT). Upon …
chemistry as well as microstructure to predict shock-to-detonation transition (SDT). Upon …
Investigations of high-speed projectile impact on symmetric sandwich structures containing solid propellant with core perforations
The response of solid rocket motors (SRMs) to high-speed fragment impacts is crucial for
their safety design and operational use in scenarios such as rocket launches and space …
their safety design and operational use in scenarios such as rocket launches and space …
Effect of shock-induced plastic deformation on mesoscale criticality of 1, 3, 5-trinitro-1, 3, 5-triazinane (RDX)
BH Lee, JP Larentzos, JK Brennan… - Journal of Applied …, 2023 - pubs.aip.org
Shock-induced plasticity and structural changes in energetic molecular crystals are well
documented. These processes couple with the leading shock wave and affect its …
documented. These processes couple with the leading shock wave and affect its …