Master (f/m/x)- Analysis of Microstructure Evolution in Thermochemical Energy Storage in Stuttgart

Vacancy-ID: 6740
Place of work: Stuttgart
Starting date: sofort
Career level: Student research project and final thesis
Type of employment: Part time
Duration of contract: 6 Monate
Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund).

Short Description of Institute/Facility - At the Institute of Engineering Thermodynamics we investigate the energy storage systems of today and tomorrow.

The Computational Electrochemistry Department of the Institute for Technical Thermodynamics in Stuttgart is offering a Master's thesis project in the field of image processing and modelling of porous media.
In a thermochemical energy storage system, thermal energy is stored via a reversible chemical reaction. This enables the storage of large amounts of energy over long periods. In view of the worldwide expansion of renewable energies and the heat transition (Wärmewende) in Germany, thermochemical storage systems are therefore being examined for their suitability for many potential applications – from small short-term storages, such as in thermochemical heat pumps, to large seasonal thermal energy storage systems.
The core component of such a storage system is a fixed bed of powder containing the reactive material. Additionally, there are pipes for the supply and removal of gaseous reactants as well as for heat transport during the charging and discharging of the storage system. The performance of these systems depends significantly on the geometry and the temporal evolution of the microstructure (e.g., due to material ablation, sintering or chemical conversion). To understand these processes, high-resolution micro-CT image series (time series) were recorded, enabling non-invasive observation of structural changes.
The challenge lies in the automated evaluation of these large amounts of data. The aim of this work is to develop a robust pipeline, for the analysis the image data in order to quantitatively describe the evolutionary changes of the microstructure, the reconstruction of the deformation of the bed as a whole, and finally transfer these findings into macroscopic models.
Specifically, the evolution of the microstructure over time is to be characterized, e.g., via pore and grain size distributions, and the deformation field of the bed as a whole is to be reconstructed. For this purpose, various methods of image registration, segmentation and analysis for porous media, including AI based methods are to be used.

Your Tasks:
• Image preprocessing: Implementation of methods for denoising, segmentation (phase separation), and registration/alignment of the time series images, including AI based methods.
• Quantitative image analysis: Characterisation of the microstructure (e.g., porosity, pore size distribution, connectivity) and reconstruction of its deformation field over time.
• Modelling & Validation: (Bonus) Parametrisation of a macroscopic model based on the acquired microstructure data and comparison of simulation results with experimentally measured data.
• Evaluation and documentation of the results.

Your Skills:
• Degree in engineering or natural sciences (mechanical engineering, physics, process engineering, technical mathematics or a comparable field of study).
• Very good programming skills in Python (ideally experience with libraries such as NumPy, pyTorch, scikit-image etc.).
• Interest in or prior knowledge of the field of (3D) digital image processing.
• Basic knowledge of the theory of porous media as well as numerical modelling and simulation.
• A strong interest and talent for theoretical work and data analysis.

We offer
DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 6740) please contact:

Dr. Thomas Jahnke
Tel.: +49 711 6862 8033