16 citations · 22 across the 3 of their papers we have counts for
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physics.comp-ph2020
Massively Parallel Transport Sweeps on Meshes with Cyclic Dependencies
Jan I C Vermaak, Jean C Ragusa, Jim E Morel
When solving the first-order form of the linear Boltzmann equation, a common misconception is that the matrix-free computational method of ``sweeping the mesh", used in conjunction…
physics.comp-ph2019★ 16 cited
Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models
Sheroze Sheriffdeen, Jean C. Ragusa, Jim E. Morel +2
Inverse problems are pervasive mathematical methods in inferring knowledge from observational and experimental data by leveraging simulations and models. Unlike direct inference me…
physics.comp-ph2019★ 2 cited
Acceleration of Radiation Transport Solves Using Artificial Neural Networks
Mauricio Tano, Jean Ragusa
Discontinuous Finite Element Methods (DFEM) have been widely used for solving radiation transport problems in participative and non-participative media. In the DFEM met…