OpenFOAM® is a widely-used open-source code and a powerful framework for solving a variety of problems mainly in the field of CFD. The five-day workshop gives an introduction to OpenFOAM® applied on CFD phenomena and is intended for beginners as well as for people with CFD background knowledge. The user will learn about case setup, meshing tools like snappyHexMesh and cfMesh. Available OpenFOAM® utilities and additional libraries like swak4Foam, that can be used for pre- and postprocessing tasks, are further aspects of this course. Additionally, basic solvers and major aspects of code structure are highlighted. Lectures and hands-on sessions with typical CFD examples will guide through this course including first steps in own coding.
HLRS, University of Stuttgart Nobelstraße 19 70569 Stuttgart, Germany Room 0.439 / Rühle Saal Location and nearby accommodations
Oct 17, 2022 08:30
Oct 21, 2022 15:30
Stuttgart, Germany
German
Basic
Domain-Specific Courses
Simulation
Numerical Simulation
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Prerequisites
To take full advantage of the course offering it would be advisable to have a standing knowledge of using Linux, as it is used for all exercises. Basics in programming will be required for some of the exercises as well as some insights into CFD theory (see e.g. the recording and material of the 2020 CFD course; password required, please refer to howto Self-study-materials & Terms and Conditions of Use).
Content levels
Community level: 33 hours
Learn more about course curricula and content levels.
Andreas Ruopp (HLRS), Dipl.-Ing. Daniel Harlacher (ZIMT, Uni. Siegen), Thorsten Zirwes (SCC, Karlsruher Institut für Technologie), Elisabeth Beer (Ostbayerische Technische Hochschule Regensburg, co-author only).
After this course, participants will:
All times are in the Central European Summer Time zone (Berlin).
The preliminary course outline can be found here (PDF).
Each participant will get a paper copy of all slides. The course language is German. The slides are in English.
Besides the content of the training itself, another important aspect of this event is the scientific exchange among the participants. We try to facilitate such communication by
For your safety, we will only allow fully vaccinated or fully recovered or COVID-19 negative tested participants on all days. You must wear a medical face mask or FFP2 mask everywhere on site. If a distance of 1.5 m cannot be guaranteed inside, e.g., if you are working in pairs in exercises, it must be an FFP2 mask. Details can be found on the registration page.
We strongly recommend to choose travel options and hotels with the possibility to cancel (even close to the event) because we might be forced to deliver the course as an online course.
Register via the button at the top of this page. We encourage you to register to the waiting list if the course is full. Places might become available.
Students without Diploma/Master: 40 EUR. Students with Diploma/Master (PhD students) at German universities: 90 EUR. Members of German universities and public research institutes: 90 EUR. Members of universities and public research institutes within EU or PRACE member countries: 180 EUR. Members of other universities and public research institutes: 360 EUR. Others: 960 EUR.
Our course fees includes coffee breaks (in classroom courses only). The fee only applies if your application is accepted. In that case you will receive an invoice.
Khatuna Kakhiani phone 0711 685 65796, kakhiani(at)hlrs.de Andreas Ruopp phone 0711 685 87259, andreas.ruopp@hlrs.de
HLRS is part of the Gauss Centre for Supercomputing (GCS), which is one of the six PRACE Advanced Training Centres (PATCs) that started in Feb. 2012.
HLRS is also member of the Baden-Württemberg initiative bwHPC.
This course is also provided within the framework of the bwHPC training program. This course is not part of the PATC curriculum and is not sponsored by the PATC program.
This offering is not approved or endorsed by ESI Group or ESI-OpenCFD®, the producer of the OpenFOAM® software and owner of the OpenFOAM® trademark.
https://www.hlrs.de/training/2022/OF1/
See the training overview and the Supercomputing Academy pages.
