Block course (8 days attendance, plus preparation & follow-up) with three parallel hands-on experiments on spectroscopy with tritium using a Mac-E filter (monitor spectrometer from KATRIN) for electrons, an IR spectrometer for analyzing tritium in water and a laser Raman system for determining the molecular composition of hydrogen isotopes. Lecturers teach core competencies in optical tritium spectroscopy, process monitoring & spectroscopy with low-energy electrons. The aim of the course is to understand the modern methods of spectroscopy in theory and to use them in experiments. In optical spectroscopy, a spectroscopic system is set up directly in the laboratory and calibration data sets are then generated, which are then used to measure unknown samples. Students work on the systems that are also used for real research.

Students will gain a holistic understanding of the potential of turbomachinery to increase energy conversion efficiency, reduce emissions and optimize performance. The course also provides a hands-on application of machine learning, with a particular focus on its central role in the development of digital twins that utilize sensor data. In the experimental labs, students explore how sensor data can be used to monitor and optimize the performance of centrifugal compressors. Through a combination of theory and hands-on lab experience, this course provides students with the knowledge and skills necessary to utilize turbomachinery technology to design a sustainable and efficient future energy system.