## Computational Fluid Dynamics (CFD) / Numerische Strömungsmechanik

##### Studiengang:

Masterstudiengang; Alle Masterstudiengänge der FVST

##### Ziele des Moduls (Kompetenzen):

Numerical flow simulation (usually called Computational Fluid Dynamics or CFD) is playing an essential role in many modern industrial projects. Knowing the basics of fluid dynamics is very important but insufficient to be able to learn CFD on its own. In fact the best way of learning CFD is by relying to a large extent on “learning by doing” on the PC. This is the purpose of this Module, in which theoretical aspects are combined with many hands-on and exercises on the PC. By doing this, students are able to use autonomously, efficiently and target-oriented CFD-programs in order to solve complex fluid dynamical problems. They also are able to analyse critically CFD-results

##### Inhalt:
• Introduction and organization. Historical development of CFD. Importance of CFD. Main methods (finite-differences, -volumes, -elements) for discretization.
• Type of errors in CFD. Validation procedure, Best Practice Guidelines.
• Linear systems of equations. Iterative solution methods. Examples and applications. Tridiagonal systems. Realization of a Matlab-Script for the solution of a simple flow in a cavity (Poisson equation), with Dirichlet and Neumann boundary conditions.
• Choice of convergence criteria and tests. Grid independency. Impact on the solution.
• Introduction to finite volumes on the basis of Matlab.
• Introduction to StarCCM+ and practical use based on a simple example.
• Carrying out CFD: CAD, grid generation and solution. Importance of gridding. Best Practice (ERCOFTAC). Introduction to CAD and meshing tools of StarCCM+, production of a simple CAD-data and grids. Surface-wrapper. Grid quality.
• Physical models available in StarCCM+. Importance of these models for obtaining a good solution. Flow visualization in StarCCM+. Influence of grid and convergence criteria. First- and second-order discretization. Grid-dependency.
• Properties and computation of turbulent flows. Turbulence modeling. Computation of a turbulent flow behind a backward-facing step. Dispatching subjects for the final project.
##### Lehrformen:
• Vorlesung mit Übungen und Computerpraktika
##### Voraussetzung für die Teilnahme:
• Strömungsmechanik
##### Arbeitsaufwand:
• 3 SWS
• Präsenzzeit: 42 Stunden
• Selbststudium: 78 Stunden
• M; 4 CP
##### Modulverantwortlicher:

Dr. G. Janiga

Letzte Änderung: 10.03.2020 - Ansprechpartner: Dominique Thevenin