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.