Practical trainings, student assistants and theses

Currently, there is a broad discussion whether ventilation by frequent window opening is sufficient for providing a sufficient amount of fresh air or if technical air purification devices based on e.g. HEPA filters are better solutions for public spaces. Furthermore, there is another discussion ongoing, whether a well-guided laminar flow or a high degree of mixing within a room is more beneficial. The latter, on the one hand distributes the potentially virus-laden aerosols in the whole room, but on the other hand reduces the peak concentrations of these aerosols clouds by magnitudes.

The objective is to perform aerosol propagation experiments and to estimate the potential aerosol inhalation of people in dynamic situations. To achieve this, an aerosol generator will be used in a demonstrator room under different flow conditions. The data from different scenarios will be processed in order to obtain a transference function that can relate the aerosol source with the aerosol receivers.

Storing energy is a promising solution to address the intermittent nature of renewables sources and to increase their share in the energy mix. Indeed, during periods of surplus production, energy can be stored as heat and later released to a power cycle when demand peaks. Since the involved temperatures are high to store a maximum of energy, power cycles with supercritical CO2 (sCO2) show higher efficiency than any traditional power cycle. Hence, each component of the system must be carefully optimized, with this work focusing specifically on the heat exchangers.
Printed Circuit Heat Exchangers (PCHEs) have drawn attention as potential heat exchangers for sCO2 power cycles for the past 40 years, due to the compact design and high thermal efficiency. The channels have a characteristic cross-flow section in the order of 1 mm2 and they exhibit a large variety of shapes, ranging from straight channels to more complex shapes like airfoils fins. The optimization of such heat exchangers is a promising topic to improve processes within the energy system. However, most optimization algorithms are based on Nusselt number and friction factor correlations, which limited to simple designs and are not suitable for the complex geometry.
For this reason, developing a Computational Fluid Dynamics (CFD)-aided optimization algorithm is essential to maximize the heat transfer performance, while minimizing pressure drop, especially when no established correlation exists. The first step will involve the creation of a Python or MATLAB script to automatically generate and mesh the geometries in Ansys. Next, the model will be validated by an objective function or experimental data from the literature. Ideally, the algorithm would be extend to handle more complex geometries.

• Academic studies in the field of process engineering, chemical engineering, mechanical engineering or comparable fields of study
• Knowledge of thermodynamics, heat and mass transfer phenomena
• Knowledge of Python or MATLAB
• Knowledge of Ansys Package

• Duration: 6 months
• Funding: Remuneration according to HZDR internal regulations
• Start Date: As soon as possible

Understanding the behaviour of fibre-laden drops is critical due to their presence in various industrial applications, including microelectronics fabrication, portable medical devices, and biofuel production. Our work focuses on the numerical simulation of fibre-laden drops, specifically investigating a single long deformable fibre within a drop impacting a solid substrate. The study aims to elucidate the dynamic interactions between the fibre and the drop. Key objectives include determining the changes in drop dynamics due to the fibre and observing fibre deformation upon impact.

This work will involve computational fluid dynamics (CFD), particularly finite volume methods, with a focus on interface tracking using the Volume of Fluid approach. The simulation will incorporate surface wettability to enhance our understanding of elasto-capillary interactions, offering insights relevant to real-world applications.

We are seeking a motivated student with prior experience in CFD (preferably OpenFOAM) or similar modelling software.

• Enrolled in a degree program such as Process Engineering, Mechanical Engineering, or Computational Modelling and Simulation
• Strong interest in particle-fluid dynamics and numerical simulations
• Preliminary experience in CFD, ideally with OpenFOAM
• Basic coding skills, preferably in C++

• Immediate start possible
• Duration of internship or thesis as per university regulations
• Remuneration available, scholarship holders (e.g. ERASMUS+) are welcome