43 citations · 86 across the 18 of their papers we have counts for
6 papers · 1 filter
An AMReX-based Compressible Reacting Flow Solver for High-speed Reacting Flows relevant to Hypersonic Propulsion
Shivank Sharma, Ral Bielawski, Oliver Gibson +8
This work presents a comprehensive framework for the efficient implementation of finite-volume-based reacting flow solvers, specifically tailored for high speed propulsion applicat…
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…
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…
Chemical Timescale Effects on Detonation Convergence
Shivam Barwey, Michael Ullman, Ral Bielawski +1
Numerical simulations of detonation-containing flows have emerged as crucial tools for designing next-generation power and propulsion devices. As these tools mature, it is importan…
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…