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AerodynamikModern Data Analysis Methods in Aerodynamics - MDAMA

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Modern Data Analysis Methods in Aerodynamics (MDAMA) - !!!! Neu im SoSe 2022 !!!

In recent years, the study of aerodynamic flows has benefitted from significant advances in computing power, data storage capabilities, and data analysis algorithms often derived from the field of machine learning. This has moved the focus of aerodynamics from classical steady (averaged) flow analysis to the exploration of unsteady effects caused by turbulence, vortex formation, and boundary-layer separation. These advances also enabled new paradigms in the optimization of aerodynamic systems. However, the tools required for such analyses are relatively new and are not included in typical aerodynamics classes yet.

The goal of Modern Data Analysis Methods in Aerodynamics (MDAMA) is to introduce the concepts and methods used in the study of unsteady flows and aerodynamic optimization to students already familiar with classical aerodynamics, either from an experimental or a numerical background.

Main topics:

- Fourier decomposition

- Proper Orthogonal Decomposition and its variants

- Vortex flow analysis

- Surrogate-based exploration and optimization.

 

Course type:

- integrierte Veranstaltung – 6 LP

- VL + Matlab Übung

Prerequisites:

- Aerodynamik I or equivalent

- Experimentelle Methoden der Aerodynamik I (or equivalent) OR Angewandte numerische Aerodynamik (or equivalent)

- Basic knowledge of Matlab programming (array, matrices, 2D and 3D plots, functions)

- A reasonably recent laptop computer running the latest version of Matlab provided for free by TU Berlin*

* The Chair of Aerodynamics may provide up to two laptops for classes and personal work within its rooms for students unable to bring their own computer – please contact us beforehand.

 

Begin: 19.04.2022, 14:00 Uhr

Location: F129

Dozent: Prof. Dr.-Ing. Julien Weiss

Contact: Mathis Thieme 

Language: English

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