Maria Castro

The Fluid Cube dataset contains 100 fluid dynamics simulations of a fluid block with varying viscosity and initial shape, velocity and positions, flowing inside a unit cube domain.

Pedro Ferro Pereira

David Carvalho

Ivan Pombo

Fábio Cruz

In this grand finale, we explore how the Graph Network simulator fits into test scenarios of fluid dynamics, generalising from simple to chaotic ones, passing through a real experimental case.

Pedro Ferro Pereira

David Carvalho

Ivan Pombo

Fábio Cruz

In this blog post, we delve in to the architecture behind the Deep Learning model we will use --- an Encoder-Processor-Decoder (E-P-D) model and how a Graph Network Simulator can be devised from it.

Pedro Ferro Pereira

David Carvalho

Fábio Cruz

Ivan Pombo

In this third post of the series, we establish graphs as appropriate data structures to handle Smoothed Particle Hydrodynamics (SPH) data. We then construct own graphs with the aim of encoding the input of our Deep Learning model.

Pedro Ferro Pereira

Fábio Cruz

David Carvalho

Ivan Pombo

In this second post of the series, we dive deeper into the theoretical and implementational foundations of Smoothed Particle Hydrodynamics (SPH) as a Computational Fluid Dynamics framework.

Pedro Ferro Pereira

Fábio Cruz

David Carvalho

In the debut of a series on learning Computational Fluid Dynamics (CFD) using Machine Learning, we start off precisely by making sense of what a fluid is, which equations dictate how they evolve physically and how computational methods can help us simulate their solutions.