PDE_FNO_Solver.py is the main script that performs model initialization and fitting. fitting-fno-models.ipynb is the notebook that performs the model fitting by calling the GPU FNO base.ipynb is a ...

This project is a deep dive into solving complex fluid dynamics problems using AI. It numerically analyzes the Navier-Stokes equation, which describes wave phenomena in falling fluid jets, by ...

Partial differential equations (PDEs) are workhorses of science and engineering. They describe a vast range of phenomena, from flow around a ship’s hull, to acoustics in a concert hall, to heat ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster. In high ...

Abstract: Numerically solving partial differential equations (PDEs) remains a compelling application of supercomputing resources. The next generation of computing resources - exhibiting increased ...

Abstract: Partial Differential Equations (PDEs) play a fundamental role in modeling complex systems in physics, biology, and engineering, such as in the context of monitoring systems. Traditional ...