activity
20182026
most citedUsing Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

10 citations · 26 across the 8 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cs.DC2023

Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI

Victor A. Mateevitsi, Mathis Bode, Nicola Ferrier +9

In the realm of Computational Fluid Dynamics (CFD), the demand for memory and computation resources is extreme, necessitating the use of leadership-scale computing platforms for pr…

physics.flu-dyn2023

Influence of adversarial training on super-resolution turbulence reconstruction

Ludovico Nista, Christoph David Karl Schumann, Mathis Bode +4

Supervised super-resolution deep convolutional neural networks (CNNs) have gained significant attention for their potential in reconstructing velocity and scalar fields in turbulen…