Master's Thesis (f/m/d) Data-Driven Control of Commercial Solar Tower Power Plants

Deutsches Zentrum für Luft- und Raumfahrt e.V. · Cologne

ThesisGerman needed: not said

Still open on 1 Nov

You apply on the company's own website.

Key facts

Pay: Paid by public sector tariff (TVöD Bund)
Language needed: German and English
Subject you study: Electrical Engineering, Physics, Aerospace Engineering, Mechatronics

Systematic comparison of simulated flux densities with real infrared and camera measurements from the CENER dataset
Identification and characterisation of systematic deviations between simulation and measurement
Development of suitable metrics for quantitative assessment of simulation quality under real operating conditions
Investigation of how infrared images and temperature sensor data can be integrated directly as a loss function into the gradient-based target point optimisation
Construction of a coupling framework between measured operating data and ARTIST-based simulation
Close cooperation with the CENER team on preparation, validation and interpretation of measurement data
Direct insight into the operation and measurement technology of a real commercial plant

Very good Python skills, especially experience with PyTorch
Strong interest in physical modelling and data-driven optimisation
Enjoy collaborative, structured software development
Mandatory internship at DLR (or willingness to do so)
Experience with image processing, sensor data analysis or measurement technology
Basics in inverse modelling or data assimilation methods

DLR stands for diversity, appreciation and equal opportunities for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous further training opportunities are available. Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and management. Applications from severely disabled people are given preference in case of professional suitability.

Systematic comparison of simulated flux densities with real infrared and camera measurements from the CENER dataset
Identification and characterisation of systematic deviations between simulation and measurement
Development of suitable metrics for quantitative assessment of simulation quality under real operating conditions
Investigation of how infrared images and temperature sensor data can be integrated directly as a loss function into the gradient-based target point optimisation
Construction of a coupling framework between measured operating data and ARTIST-based simulation
Close cooperation with the CENER team on preparation, validation and interpretation of measurement data
Direct insight into the operation and measurement technology of a real commercial plant

Very good Python skills, especially experience with PyTorch
Strong interest in physical modelling and data-driven optimisation
Enjoy collaborative, structured software development
Mandatory internship at DLR (or willingness to do so)
Experience with image processing, sensor data analysis or measurement technology
Basics in inverse modelling or data assimilation methods

DLR stands for diversity, appreciation and equal opportunities for all people. We promote independent work and the individual development of our employees in their personal and professional environment. For this purpose, our numerous further training opportunities are available. Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and management. Applications from severely disabled people are given preference in case of professional suitability.