3 papers
physics.flu-dyn2026
Super-Resolution Initialization of High-Fidelity CFD Simulations for Pebble-Bed Reactors
Guilherme Gottems, Vasil Ivakimov, Luiz Aldeia Machado +13
High-order CFD simulations provide detailed resolution of the heterogeneous interstitial flow in pebble-bed reactors, but their computational cost is high, especially during the in…
cs.DC2024
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
Shivam Barwey, Riccardo Balin, Bethany Lusch +5
This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer. As the name implies, t…
physics.flu-dyn2024
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
Shivam Barwey, Pinaki Pal, Saumil Patel +5
A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed…