Introduction to Computational Fluid Dynamics

CFD Simulation - Courtesy Harald Klimach (DLR)
The course will be conducted online and the language was switched to English.

The course introduces into established numerical methods for Computational Fluid Dynamics in the context of high performance computing. An emphasis is placed on explicit methods for compressible flows, but also numerical methods and considerations for incompressible Navier-Stokes equations are discussed. Additional topics are higher order discretizations for the solution of systems of partial differential equations and the Lattice Boltzmann method. The last day is dedicated to parallelization.

Hands-on sessions will manifest the contents of the lectures and train the use of cluster systems for parallel simulations. In most of these sessions the tools from the APES-Suite will be used. They cover grid generation with Seeder,
visualization with ParaView and the usage of parallel CFD solvers Ateles and Musubi on the local HPC system.

The course is organized by HLRS, the TU Dresden (Chair of Fluid Mechanics and  ZIH), the University of Stuttgart (IAG and HLRS) and DLR (Institute of Software Methods for Product Virtualisation).

Location

Online course
Organizer: ZIH at TU Dresden, Germany

Start date

Feb 05, 2024
09:00

End date

Feb 09, 2024
15:30

Language

English

Entry level

Basic

Course subject areas

Community-Specific Courses

Simulation

Topics

Computational Fluid Dynamics

Numerical Methods

Numerical Simulation

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Prerequisites and content levels

Prerequisites
  • Basic knowledge of partial differential equations and physics.
  • Shell and Unix experience for working on a cluster system
  • Discretization schemes of ODEs (optional).
  • Preliminary experience with Python (optional). Since Python is used, the following tutorial can be used to learn the syntax.
Content levels

Community level: 30 hours

Learn more about course curricula and content levels.

Instructors

Dr.-Ing. Harald Klimach (main instructor) and Dr.-Ing. Kannan Masilamani. Other authors: Dr.-Ing. Neda Ebrahimi Pour, Jana Gericke, M.Sc., Raphael Haupt, M.Sc., Dr. Gregorio Gerardo Spinelli (DLR, SP);
Prof. Dr.-Ing. habil. Jochen Fröhlich (Chair of Fluid Mechanics, TU Dresden);
Anna Schwarz, M.Sc. (IAG, Uni. Stuttgart);
Dr. Albert Ruprecht (formerly IHS, Uni. Stuttgart);
Dr.-Ing. Christoph Niethammer (HLRS, Uni. Stuttgart)

Learning outcomes

After this course, participants will:

  • have gained a basic overview of CFD methods.
  • know different types of flow applications and suitable numerical methods.   
  • be able to use HPC systems to perform CFD simulations.
  • have insights into common numerical methods and their implementation.
  • be able to roughly estimate and evaluate the performace by knowing about important factors of parallel execution.

Agenda

See link to the detailed program (CET time, preliminary).

Handout and course material

Each participant will get the pdf of all slides.

The course material will be updated during the course at this link.

Slides, exercises and recordings of the 2020 ONLINE course are available at our self-study materials.

Registration information

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.

The registration is managed by ZIH.

Contact

Anja Gerbes at ZIH (local organiser).

HLRS Training Collaborations in HPC

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.

CEEC CoE

This course is partly realised in cooperation with the Centre of Excellence CEEC. Funded by the European Union. This work has received funding from the European High Performance Computing Joint Undertaking (JU) and Sweden, Germany, Spain, Greece, and Denmark under grant agreement No 101093393.

Further courses

See the training overview and the Supercomputing Academy pages.

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