10 citations · 19 across the 3 of their papers we have counts for
3 papers
Probabilistic Flux Limiters
Nga T. T. Nguyen-Fotiadis, Robert Chiodi, Michael McKerns +2
The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular m…
Machine Learning for Detection of 3D Features using sparse X-ray data
Bradley T. Wolfe, Michael J. Falato, Xinhua Zhang +7
In many inertial confinement fusion experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy sug…
Machine Learning Changes the Rules for Flux Limiters
Nga Nguyen-Fotiadis, Michael McKerns, Andrew Sornborger
Learning to integrate non-linear equations from highly resolved direct numerical simulations (DNSs) has seen recent interest for reducing the computational load for fluid simulatio…