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Found 5 papers, 0 papers with code
A composable machine-learning approach for steady-state simulations on high-resolution grids
The numerical experiments show that our approach outperforms ML baselines in terms of 1) accuracy across quantitative metrics and 2) generalization to out-of-distribution conditions as well as domain sizes.
A composable autoencoder-based iterative algorithm for accelerating numerical simulations
Numerical simulations for engineering applications solve partial differential equations (PDE) to model various physical processes.
A Latent space solver for PDE generalization
In this work we propose a hybrid solver to solve partial differential equation (PDE)s in the latent space.
Sustaining Research Software via Research Software Engineers and Professional Associations
Research software is a class of software developed to support research.
Software Engineering
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization
The two solver characteristics that have been adopted in this work are: 1) the use of discretization-based schemes to approximate spatio-temporal partial derivatives and 2) the use of iterative algorithms to solve linearized PDEs in their discrete form.
