8 citations · 8 across the 2 of their papers we have counts for
4 papers
Multi-Agent Design Assistant for the Simulation of Inertial Fusion Energy
Meir H. Shachar, Dane M. Sterbentz, Harshitha Menon +10
Inertial fusion energy promises nearly unlimited, clean power if it can be achieved. However, the design and engineering of fusion systems requires controlling and manipulating mat…
Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media
M. Giselle Fernández-Godino, Meir H. Shachar, Kevin Korner +4
Predicting the extreme hydrodynamic response of porous and architected lattice materials is a fundamental challenge in high energy density physics, where shock-induced pore collaps…
StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials
Yinan Wang, Diane Oyen, Weihong +7
Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal…
Review of multi-fidelity models
M. Giselle Fernández-Godino
Multi-fidelity models provide a framework for integrating computational models of varying complexity, allowing for accurate predictions while optimizing computational resources. Th…