Michael Mitterlindner

Michael Mitterlindner
Dipl.-Ing. BSc
Phone
+43 316 873 - 30411

About me

I began my studies in chemical engineering at Graz University of Technology in 2018. Upon completing my bachelor's program, I pursued a master's degree in chemical engineering with a focus on systems engineering and process technology. During my master's studies, my fascination for various simulation methods and techniques grew. This interest led me to work at the Institute of Process and Particle Engineering, where I applied CFD simulations to predict potential distributions in the wafer etching process. Additionally, I was involved in a project exploring flow behavior for cleanroom decontamination using H2O2. As part of my master's thesis at the Institute of Chemical and Environmental Engineering, I developed and implemented an optimization algorithm aimed at determining optimal parameters of thermodynamic models based on experimental data, employing a machine learning strategy. In 2023, I embarked on my Ph.D. journey at the Institute of Process and Particle Engineering under the guidance of Stefan Radl.

Research interests

My current research focuses on the "Ni2Steel" project, aimed at enhancing the recycling process of NiMH batteries. The primary objective of my research is to model extremely compactable and cohesive materials using the Discrete Elemental Method (DEM). In addition to mechanical properties, accurately modeling heat conduction within the bulk material is essential for safety reasons and the design of further equipment. I aim to utilize experimental data to optimize simulation parameters for DEM, enabling realistic representation of flow and thermal conduction properties of crushed batteries. Furthermore, I plan to leverage AI-supported models and intelligent optimization algorithms to efficiently determine appropriate parameters for simulation.

Figure 1. Ni2Steel battery recyclate
Figure 2. CT-Scan of the battery recyclate
Figure 3. Multi-Cycle compaction simulation
Figure 4. Calibration of the effective thermal conductivity