187 citations · 529 across the 67 of their papers we have counts for
4 papers · 2 filters
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…
A note on the error analysis of data-driven closure models for large eddy simulations of turbulence
Dibyajyoti Chakraborty, Shivam Barwey, Hong Zhang +1
In this work, we provide a mathematical formulation for error propagation in flow trajectory prediction using data-driven turbulence closure modeling. Under the assumption that the…
Understanding Latent Timescales in Neural Ordinary Differential Equation Models for Advection-Dominated Dynamical Systems
Ashish S. Nair, Shivam Barwey, Pinaki Pal +3
The neural ordinary differential equation (ODE) framework has emerged as a powerful tool for developing accelerated surrogate models of complex physical systems governed by partial…
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective
Sunwoong Yang, Hojin Kim, Yoonpyo Hong +3
This study explores the potential of physics-informed neural networks (PINNs) for the realization of digital twins (DT) from various perspectives. First, various adaptive sampling…