Luís Sarmento

Luís Sarmento

Ivan Pombo

Ivan Pombo

Sérgio Santos

Sérgio Santos

Maya Hershey

Maya Hershey

Explore available computational resources through the Inductiva API and learn how to choose more powerful hardware to run the "base case"

Luís Sarmento

Luís Sarmento

Ivan Pombo

Ivan Pombo

Sérgio Santos

Sérgio Santos

Maya Hershey

Maya Hershey

Dive into the first crucial step of synthetic data generation and learn how to define your "base case" simulation model.

Luís Sarmento

Luís Sarmento

Ivan Pombo

Ivan Pombo

Sérgio Santos

Sérgio Santos

Maya Hershey

Maya Hershey

Learn how to generate large-scale synthetic datasets for Physics-ML models using the Inductiva API, starting with our unique data generation recipe.

Hugo Penedones

Hugo Penedones

Luís Sarmento

Luís Sarmento

The Inductiva API v0.4 release brings MPI clusters, the latest Google Cloud CPUs, two new simulators, a lighter Python package, a CLI interface, a template engine and totally revamped documentation. Get started in minutes!

Sofia Guerreiro

Sofia Guerreiro

Cristiana Carpinteiro

Cristiana Carpinteiro

In this series of blog posts we will explore a specific case of the use of AI in the pharmaceutical industry - using Graph Neural Networks for predicting binding affinity. But for now, let’s start by understanding the problem of drug discovery and some fundamental concepts like binding affinity.

Ivan Pombo

Ivan Pombo

Luís Sarmento

Luís Sarmento

Coastal engineering projects protect the coast from erosion, flooding and other events. Due to their cost, the design phase of these projects is heavily based on computational simulations. In this blog post, we enlighten how Inductiva API allowed researchers to scale their coastal engineering simulations.

Hugo Penedones

Hugo Penedones

Luís Sarmento

Luís Sarmento

Luís Cunha

Luís Cunha

Guidelines for programming effectively and with high impact.

Bruno Ribeiro

Bruno Ribeiro

João Ribeiro

João Ribeiro

Luís Sarmento

Luís Sarmento

Hugo Penedones

Hugo Penedones

The SimuStruct dataset contains 1000 cases of 2D rectangular plates with holes under load along with measurements of von Mises stress.

Maria Castro

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.

Ivan Pombo

Ivan Pombo

This dataset contains 1000 voltage measurements obtained through simulation of current propagation inside a circular two-dimensional domain for distinct electrical conductivity profiles.

Pedro Ferro Pereira

Pedro Ferro Pereira

David Carvalho

David Carvalho

Ivan Pombo

Ivan Pombo

Fábio Cruz

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

Pedro Ferro Pereira

David Carvalho

David Carvalho

Ivan Pombo

Ivan Pombo

Fábio Cruz

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

Pedro Ferro Pereira

David Carvalho

David Carvalho

Fábio Cruz

Fábio Cruz

Ivan Pombo

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

Pedro Ferro Pereira

Fábio Cruz

Fábio Cruz

David Carvalho

David Carvalho

Ivan Pombo

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

Pedro Ferro Pereira

Fábio Cruz

Fábio Cruz

David Carvalho

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.

Rúben Dhanaraju

Rúben Dhanaraju

David Carvalho

David Carvalho

Fábio Cruz

Fábio Cruz

Luís Sarmento

Luís Sarmento

In this 4th post of the series, we benchmark the performance of a Constraint Programming solver on its own for finding Hadamard matrices.

Fábio Cruz

Fábio Cruz

Maria Castro

Maria Castro

Luís Sarmento

Luís Sarmento

David Carvalho

David Carvalho

Do GPUs solve sparse eigenproblems faster than CPUs? In this post, we answer this question by comparing the SciPy and CuPy eigensolvers.

David Carvalho

David Carvalho

In this new post, we start our discussion on how artificial reefs can also be used to enhance surfability conditions. We start off by introducing what makes a good wave for surfing.

David Carvalho

David Carvalho

Fábio Cruz

Fábio Cruz

In this Outlook series, we look into how the extent of protection afforded by specific artificial reef components can be measured. This task is challenging in itself but progress can be made with the aid of either simulation or experimental data from hydraulic experiments.

David Carvalho

David Carvalho

Fábio Cruz

Fábio Cruz

In this post, we dive deeper into how important coral reefs are for Coastal Protection and how simulation can help custom-designed optimal artificial reefs to be found.

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