In the previous episodes we used Elmer to develop a few different acoustics models. We were able to verify the accuracy of Elmer with few benchmark problems. Additionally, we studied the effect of mesh order and size on the accuracy. Finally, we started probing vibro-acoustic problems. We only scratched the surface of Elmer capabilities in this field. Still, it is worth to take a step back and reconsider these problems under a different light. The FEniCS project is perfect for this. We will be introducing FEniCS in this episode.

In many of the previous episodes we produced animations of steady state Elmer FEM solutions. For simplicity we did not discuss the details of how to prepare them. The process is actually very simple, but there are few tips and tricks to keep in mind. This episode aims to provide a concise introduction to animations with ParaView.

In the previous episodes we manipulated some of the result fields from Elmer with meshio, a very nice Python package that allows us to do many useful operations with meshes and fields. However, in the episodes we did not focus into the details of how to use the package. Whilst this webiste is perhaps not the best place to do so, as the best place to understand how to use a package is, of course, its official documentation, it is useful to collect here few examples and remarks about using it with Julia, the programming language we are using for this project.

In the previous episodes we often made use of the ParaView postprocessor to visualise our solution field from the Elmer solver. ParaView can do all sorts of cool visualisations and animations, as well as providing the way of doing quantitative analysis. It is by far the best option to visualise and postprocess results from Elmer. It also allows to export data in various formats, such as CSV, that allow us to do any additional kind of postprocessing or verification, by either using Julia, Python or any other language, or even spreadsheet software if you fancy that (for whatever reason…).

In the previous article an overview of the open-source ecosystem for scientific and technical computing was presented. In this article the focus will be on FEM. We will first look at how we build a FEM problem, and then select among the packages we listed the software that is best suited for implementing FEM studies. The Basic Pipeline The diagram above shows the process of creating a FEM study in its simplest form.

In the first episode of this series the open-source ecosystem for the modelling of acoustics was covered. As we will see in the next episodes, we will make extensive use of FEM, at least initially, to model acoustic phenomena. This episode focus on building a simple simulation workstation based around Elmer, a powerful multiphysics FEM suite with excellent acoustics capabilities. Why an Ubuntu Based Workstation? Ubuntu Linux is a very convenient operating system for this purpose as all the needed packages are straightforward to install, especially Elmer and Salome, which can be quite complicated to get up and running in other distributions.

One of the backbones of the scientific paradigms is the repeatability of results. Ideally, all software used for scientific research should be open-source, so to allow complete repeatability of data analysis and models. And in fact, a lot of scientific software is indeed open-source, and a lot of this software can be used to model acoustic phenomena. What follows below is a panoramic overview of the scientific open-source software ecosystem. This overview is far from comprehensive.