# 893401 Applied computational fluid dynamics (in Eng.)

Art
Vorlesung
Semesterstunden
2
Vortragende/r (Mitwirkende/r)
Bikic, Sinisa
Organisation
Angeboten im Semester
Sommersemester 2022
Unterrichts-/ Lehrsprachen
Englisch

Lehrinhalt

Introductions to computational fluid dynamics (CFD). Basic principles of conservation. Lagrangian and Eulerian specification of the flow field. Reynolds transport theorem. Conservation of mass, momentum and energy. General form of conservation equations. Introduction to partial differential equations (PDE). Classification of PDE. Approximate solutions of differential equation. Fundamentals of discretization of PDE by using of: finite element method (FEM), finite difference method (FDM) and finite volume method (FVM). Discretization of diffusion equation, convection equation, convection-diffusion equation, Navier-Stocks equation. Implementation of boundary conditions. Discretization of steady and unsteady state. Structured and unstructured Grid. Introduction to fluid flow turbulence. Turbulence models: Reynolds Averaged Navier-Stokes (RANS), mixing length model and k –  model. Solution of systems of linear algebraic equations. Iterative methods for numerical solution of system of linear algebraic equations. An example of application of CFD in a software: modeling, region, boundary conditions, mesh and physics continuum, turbulence models, post processing.

Inhaltliche Voraussetzungen (erwartete Kenntnisse)

Student should have previous basic knowledge in the field of: fluid mechanics (continuity equation, Bernoulli equation, Navier-Stokes equation), thermodynamics (equation of state, first and second law of thermodynamics), heat transfer (transfer of heat by conduction, convection and radiation phenomena), mass transfer (Fick’s first and second law) and mathematics (solving of system of linear algebraic equations).

Lehrziel

At the end of the course students will get both theoretical and practical knowledge in the field of computational fluid dynamics. Students will get comprehensive theoretical knowledge which will be good basics for understanding and future usage of computational fluid dynamics in their research. They will also be trained to set up numerical simulation in a computational fluid dynamic software and in this way get practical knowledge and gain skills in this field.
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