Practical trainings, student assistants and theses

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

Fine-grained solid particles from various industrial sources, which would otherwise be discarded, should ideally be processed to valuable products or inert residues. They contain valuable residuals, such as metals, that can be returned to the industrial cycle instead of being landfilled. This is one aim of the Helmholtz project FINEST in which this work is embedded.
The different finest powders need to be mixed and agglomerated for further processing. Our work in the project deals with the granular mixing. One aim is to describe the process using flow simulations in OpenFOAM.
The particle flow is described based on the rheology of the bulk material, while the mixing process between the particles is described using a transport equation. In addition, there are terms for the segregation that takes place in parallel.
We are looking for someone with experience in CFD or other modelling to refine the implementation of this model and then perform parameter studies and validation using experimental data.

• Student of e.g. Computational Engineering, Modelling and Simulation, Mechanical Engineering, Process Engineering, Chemical Engineering
• General interest in fluid mechanics and simulations
• Preliminary experience in CFD, ideally OpenFOAM
• Preliminary experience in code development (C++) optional

• Start from March 2025
• Duration of internship or thesis according to study regulations
• Remuneration available, scholarship holders (e.g. ERASMUS+) welcome

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

Flowing foam is relevant to many different industrial applications, such as froth flotation in mineral processing, fire-extinguishing systems, or brewing beer and beverage production. In a scientific context, the rheological properties of foams are very complex and significantly different from those of Newtonian fluids such as water. As a result, despite numerous experimental and theoretical studies, the fluid dynamics of foams remain poorly understood.

This project focuses on a classical benchmark experiment: the flow around a cylindrical obstacle. To identify key parameters of flowing foam in this configuration, we use two unique radiographic measurement techniques. First, neutron radiography provides imaging measurements of the local liquid fraction of the flowing foam. Second, X-ray radiography with foam-tailored tracer particles allows to perform local velocity measurements in the flowing foam.

The following subtasks are mainly to be worked on:

• Assistance in preparing and performing the foam flow experiment in the X-ray laboratory at HZDR
• Analysis of the measurement data, including image processing and machine learning if applicable
• Documentation of the experiment and measurement results in written form

• Field of study: process engineering, fluid mechanics, or similar focus in chemistry or physics
• Experience with laboratory work, imaging measurement techniques or measurement data analysis is beneficial (e.g. using ImageJ, Matlab, Python)
• High motivation and interest in the subject
• Careful, structured and independent way of working
• Good oral and written communication skills in English or German
• Enjoyment of scientific work

• Working in a multi-disciplinary and international team
• Place of work: HZDR or TU Dresden
• Start: from March 2025
• Duration: min. 3 months
• Remuneration according to HZDR internal regulations

The development of a multi-channel flow body sensor according to patent WO 2010/069307 A1 aims to quantify the gas content in flow-carrying components. A decisive advantage of this sensor lies in its optical measuring principle, which is based on fiber-optic coupling and the analysis of the light output signal. This avoids electrical potentials in the measuring area, offering significant advantages over electrical measuring methods (intrinsic safety), especially for explosive mixtures.

Preliminary tests at the Institute for Experimental Fluid Dynamics at the Helmholtz Center Dresden-Rossendorf on gas-liquid flows showed that a clear binarization of the sensor output signal can be achieved due to the capillary effects in narrow channels and the different refractive indices of the gas and liquid phases. Building on previous work with a single-channel sensor prototype based on a polymer optical fiber (POF) with a diameter of 1 mm, the following tasks must be completed as part of further research.

Tasks:

• Adjusting the POF diameter to 1.5 mm in the single-channel configuration.
• Conducting experimental investigations of the new single-channel prototype using the already developed test system and evaluation programs.
• Designing a multi-channel sensor body for gas content measurements in the system.
• Developing a transition adapter to optimize the flow distribution between the DN10 flow pipe and the sensor body.

• Students majoring in fields such as process engineering, mechanical engineering, or chemical engineering.
• Interest in fluid mechanics and the development of measurement technology.
• Experience with 3D CAD tools.
• Basic knowledge of Python programming

Start date: 01.01.2025
Duration: according to the respective study regulations

Background:

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.

Objectives:

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.

Tasks:

• Literature survey
• Aerosol experiments in different scenarios.
• Post-processing of the results.

• Student of natural sciences or engineering
• Willingness to conduct experimental work

Duration:

4-6 months

Remuneration:

According to HDZR guidelines