Track: Aerodynamics & Wind Energy
The master Track Aerodynamics and Wind Energy combines fundamental and applied research disciplines of aerospace and wind-power systems, focusing on the development of new analysis techniques and their application in design. It is aimed at those who wish to acquire experience with both experimental and numerical methods as well as design procedures and optimisation techniques.
What you will learn
You build experience through courses, a directed internship and a supervised final research project. The consolidation of the theoretical aspects treated in the various research topics is made possible by a wide range of experimental and computer facilities available for the MSc students.
The objective of this track is to provide you with the opportunity to become a specialist with specific knowledge in analysis of aerodynamic systems, and the methods used for their application in design. You will obtain a thorough fundamental basis in aerodynamics as well as in modern techniques to investigate such systems.
The Track offers two Profiles:
The Aerodynamics Profile is concerned with the understanding and control of flows associated with aerospace vehicles. On the fundamental side, it considers the design of measurement and computational methods for the provision of detailed flow descriptions. Continue...
- Wind Energy
The Wind Energy profile focuses on methods and systems of energy extraction from wind. Both wind turbine and kite power systems are addressed. The profile offers courses on atmospheric wind conditions, rotor aerodynamics, wind turbine design, design of rotor blades and kite systems and of offshore wind farms. Continue...
The Aerodynamics and Wind Energy track is one of six tracks within the Aerospace Engineering master programme. On graduation, students receive a Master of Science degree in Aerospace Engineering (Aerodynamics and Wind Energy).
For the Aerodynamics and Wind Energy track a strong background in mathematics and fluid mechanics is required. A basic knowledge of numerical methods, computer programming, statistical methods and experimental methods is recommended. Make sure that you provide evidence of these skills in your application.