Novel Techniques in Model Building for Gas Turbine Combustion Systems
Leader: Jan Beuth, Moritz Reumschüssel; Institutional affiliation: Institut für Strömungsmechanik und Technische Akustik (ISTA), Technische Universität Berlin
Funding Period: 01.04.2022 – 30.09.2022
To fully exploit the potential of modern gas turbines, further design steps are necessary to optimize the operating behavior. In this context, the possibility of alternative fuels such as hydrogen also places new demands on the combustion process in gas turbines. In our research, we use Machine Learning and Data-Based methods to generate mathematical models of different components of the combustion system that can be used for analysis and optimization. With the participating students, we aim to pursue different approaches for model building.
This course is designed to incorporate students from a variety of disciplines. The students ideally bring along a sound mathematical and/or physical background. Furthermore, a basic knowledge of programming in MatLab or Python to implement the methods is highly recommended. Additional knowledge in areas of fluid dynamics, combustion or Machine Learning can be beneficial but are not a definite prerequisite for the course.
Course language: English
Schedule: wednesdays, 10 a.m.-12 p.m.