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      14
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    NWO-DFG, Fluidization Technology for Regeneration of Hydrogen-based Iron Fuel
    Climate change necessitates an energy transition from fossil fuels to renewable energy. Due to fluctuating availability of energy resources such as solar and wind, the global energy transition requires innovative energy carriers for decentralized, long-term, and long-distance storage and transportation to complement the future energy mix. Iron powder has emerged as a clean, safe, and cost-effective energy carrier, particularly because of its high (volumetric) energy density. It releases chemical energy through oxidation with air or reaction with water, generating high-temperature heat and/or hydrogen. The resultant iron oxide powder can be regenerated into iron via chemical reduction using (green) hydrogen generated from renewable energy. This cyclical oxidation-reduction process, known as the Iron Power Cycle, establishes a circular, CO2-free energy economy. While development of iron combustion technology has grown rapidly with MW-scale fluidized bed boiler demonstration, development of green iron fuel regeneration (iron oxide reduction) technology is lagging. This proposal focuses on the regeneration/reduction challenges in fluidized beds. Fluidization technology has a wide application in chemical engineering, energy conversion, and pharmaceuticals production. Because of its advantage in high heat and mass transfer rates between the fluid phase and solid phase, it is very attractive and has been preliminarily investigated for the regeneration process in the Iron Power Cycle. The aim of this project is to leverage the fundamental understanding of reactive, cohesive particulate flows in fluidized bed H2-ironmaking process towards the industrial application of Iron Power Energy Cycle. With a novel experimental setup for the first time, the collision and consequent sintering of laser heated particles will be measured with two high-speed cameras. Furthermore, the most suitable fluidized bed configuration for this H2-DRI process will be examined. The fluidization regimes to be investigated include bubbling regime, spouted fluidization and fast fluidization. The experiments will provide datasets of cohesive particle collision and reactive gas-solid flow dynamics in different fluidization regimes, which are essential for development and validation of numerical models. Finally, effective numerical tools with generic modules should be established which are applicable beyond this project towards wide applications involving dense gas-solid flows with phase transition and chemical reactions. Despite a focus on scientific impact, this project will, in the long term, also generate impact on technological development (increasing TRL) and implementation of the Iron Power Cycle as well as green steelmaking. The research employes a combined experimental and numerical approach. At Hamburg University of Technology, the work focuses on experiments. At Eindhoven University of Technology, the focus will be on numerical model development and CFD-DEM simulations.
      10
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    Understanding of mechanical deformations in soft, porous particles under consideration of solvent-matrix interactions: experiments and coarse-grained DEM simulations
    This project aims to investigate the impact of mechanical stresses on soft, porous particles during their production in packed beds. Aerogels, known for their high porosity, low density, and large surface area, are used as representative porous systems. Their production involves several extraction steps, during which the porous matrix is exposed to different solvent mixtures with varying concentration gradients. Consequently, the mechanical and structural properties of the particles undergo significant changes, which will be experimentally investigated. In addition to experimental studies, coarse-grained Discrete Element Method (DEM) simulations will be used to explore mechanical deformations during aerogel formation, particularly under conditions that cannot be easily accessed through experiments, such as those involving elevated pressure. DEM simulations will also be further developed to include the influence of solvent-matrix interactions on the mechanical behavior of gels and their response to mechanical stress. The research will begin by analyzing individual particles and gradually scale up to packed beds of varying sizes. The focus will then shift to dynamic processes during solvent exchange and supercritical drying, where DEM simulations will be integrated with Computational Fluid Dynamics (CFD) simulations. The ultimate goal is to predict the mechanical behavior of the particles and define process conditions that maintain the structural integrity and desired properties of the particles during large-scale production
      8
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    GRK 3068 - Climate-informed Engineering
    Spokesperson: Professor Dr. Shokri Deputy spokesperson: Professor Dr. Smirnova Breakthroughs in computing have led to the development of new generations of Earth Systems Models, which provide detailed information on how our planet may locally respond to the ongoing global warming, with unprecedented spatial and temporal resolutions of 1 km and a few minutes, respectively. This massive climate data may be of little value, if not utilized by engineers who are involved in developing technical solutions for real-world challenges. Engineers stand to benefit from seizing this opportunity and by incorporating climate data in engineering designs, solutions, and practices. This benefit is precisely the key driving force for founding the Research Training Group (RTG) on Climate-informed Engineering (CIE) as an emerging interdisciplinary field of research integrating state-of-the-art climate information with engineering education. A structured training strategy is designed in the RTG featuring a broad range of educational activities to facilitate training and promote early-career researchers who will contribute to developing the next generation of engineering solutions that are adaptive to climate. In doing so, we will integrate a new generation of climate models in our training through the active involvement of the Max-Planck Institute for Meteorology (MPI-M), an internationally renowned organization at the forefront of global efforts on climate models. Furthermore, the RTG offers a joint PhD program between TUHH and the United Nations University Institute for Water, Environment and Health (UNU-INWEH). Hence, the PhD candidates will benefit from the interactions with renowned experts at UNU and the UN on a variety of topics related to United Nations Sustainable Development Goals, which is at the heart of our RTG. The RTG will utilize engineering science and innovative approaches to develop new materials, processes, and predictive capabilities to help people, businesses, and ecosystem in the face of climate change. The RTG will include three main Research Areas, namely CIE for Built Environment, CIE for Process Engineering and CIE for Sustainable Resource Management and Environment. Ten projects are designed in the first funding phase, covering a wide range of topics, spanning from influence of climate on renewable resources and food engineering to developing novel materials for latent heat storage. The projects will couple indoor and outdoor climates based on Internet-of-Things technologies and will develop predictive capabilities for water and food security. All the principal investigators and PhD candidates share the common goal of employing new-generation climate information to devise strategies for mitigating climate change. This interdisciplinary RTG is the first of its kind, ultimately enabling engineers to build infrastructure and to develop new materials and processes that are informed by the climate data, which will be an increasingly important dimension of engineering education in the 21st century.
      128
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    Enhancing Sustainability in Ceramic Tile Manufacturing through Process Simulation and Optimization
    Porcelain tiles are structure ceramic plates that are widely utilized to cover the floors and walls of residential, industrial, and commercial buildings. Porcelain tiles are unique. The process typically involves molding granulated raw material through high-pressure compaction, followed by firing in continuous roller kilns for a duration of 30-60 minutes. Automation and digitalization have increased with Industry 4.0. However, the ceramic industry lacks the ability to integrate measuring system output with automated equipment control. The distribution of properties in solid processes is complicated by particle chemical composition, shape, size, and structure. New environmental policies, especially for energy-intensive industries like porcelain tile production, require more sustainable manufacturing processes to maintain product quality. For numerical investigations of complex plants with material and energy streams connecting production steps, flowsheet calculations can be effectively applied . Even though flowsheet simulation tools are common in chemical engineering for fluid processes, they are not yet common for solid processes, especially ceramic powders. Only recently have such tools for interconnected solids processes been developed and applied. The typical practice is to design, simulate, and optimize each apparatus separately, ignoring its impact on neighboring processes. Previous studies have shown that flowsheet simulation accurately quantifies key process parameter sensitivity. The simulations can evaluate each processing unit's locally and process chain effects. Experimental data and semi-empirical models prevent a complete process sequence sensitivity analysis. Implementing a multiscale process treatment and gathering more material and process parameter data can improve models and optimize processes. To address this problem, this project aims to enhance the current models and simulate the manufacturing process of porcelain tiles through a joint collaborative research initiative involving UFSC in Brazil and TUHH in Germany. The multiscale process treatments will enable the digitalization and optimization of the entire processing chain. CFD simulations data will be used to improve the constitutively developed semi-empirical relations used in macroscale models by means of data driven surrogate models. This will build the foundation for computationally efficient optimization and model-predictive control for an industry that faces the challenges for digitalization. This project is part of DFG-CAPES Collaborative Research Initiative in the field of Industry 4.0, Advanced Digitalization.
      95
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    Identification of the mechanical behavior and coupling with improved internal structural analysis of frozen particle-fluid-systems
    Frozen particle-fluid systems (PFS) can be considered as particle-reinforced composite materials and are frequently encountered in both natural and technical systems. When subjected to mechanical loading at low temperatures for water-based fluids within the PFS, a phase transition occurs, leading to changes in their mechanical behavior and associated properties. For instance, soil stability is critical in the Arctic for construction projects, and artificial ground freezing (AGF) is commonly used to stabilize soil for mining and tunneling projects. Similarly, materials stored in silos at low temperatures or subjected to cryogenic grinding are exposed to changes in their mechanical properties. Therefore, it is important to investigate frozen PFS using in-situ methods to understand their characteristic properties and behavior under realistic conditions. Currently, different approaches are used to simulate frozen PFS, including finite element method (FEM) simulations and discrete element method (DEM) simulations with an alternate contact model. However, these approaches have limitations, such as higher computational costs, problems with discretization, and an inability to precisely describe the behavior of complex materials. To overcome these limitations, this project proposes using the Bonded Particle Model (BPM), which extends the DEM by connecting particles with bridges, forming agglomerates. A newly developed solid bond model considers creep behavior to describe the mechanics of frozen PFS in relation to different temperatures, strain rates, and volumetric ice contents. Micro-computed tomography (Micro-CT) measurements will also be carried out to generate the internal structure of frozen PFS based on different volumetric ice contents and particles. This non-destructive three-dimensional imaging of the internal structure with a high spatial resolution of the slice images using X-rays will be used. Using an in-situ Micro-CT device, a miniaturized uniaxial compression test apparatus will be developed to capture the freezing process with coupled mechanical loading in real time. Artificial neural networks (ANNs) will be used to calibrate the DEM-BPM material parameters and predict the mechanical properties of the agglomerate during freezing and loading. The computational time necessary for predicting the mechanical properties of agglomerates can be significantly reduced through the proposed method. For this purpose, a database consisting of thousands of simulations will be created and expanded to correlate with additional scenarios and realistic experimental data, which will further enhance the predictive capabilities of this tool.
      15
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    CRC 1615 - Project A07: Highly integrated sensors for in-line detection of granulation state in fluidised bed reactors
    In project A07 novel Lagrangian sensor particles will be developed, which allow the measurement of temperature, humidity and applied coating layer thickness during fluidized bed spray granulation based on impedance spectroscopy. The first prototype is of 25 mm size, whereby further miniaturization to 5 mm will be achieved by designing and fabricating an application specific integrated circuit (ASIC). Particle position will be measured by a magnetic particle tracking setup, which is for the first time adapted to a fluidized bed spray granulation process.
      74
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    CRC 1615 - Project C04: SMART continuously operated fluidised bed for spray granulation with self-regulating residence time distribution
    In project C04 a concept for a continuously operated fluidised bed spray granulation process will be developed based on recurrence CFD (rCFD) simulations and reactor adaptation. The rCFD simulation framework is obtained by calibration experiments and detailed CFD-DEM simulations of the particle formulation step. Once the database is created, the simulations will be fed by live process data from inline sensors such as Lagrangian sensor particles. As they are running faster than real-time, the timely intervention is enabled. Together with the adaptable residence time distribution by novel flexible vertical weirs, this project delivers important features for SMART reactors.
      45
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    SPP 2289: Spouted bed processing for structuring of conductive battery hetero-aggregates
    In this project, a novel spouted bed dry coating process will be established, which is able to fabricate hetero aggregates consisting of three materials, that are suitable for the use in all-solid-state-batteries. The materials, with primary particle sizes ranging from 40 nm to around 1 µm, will be provided within the SPP by the working group of Prof. Kwade in Braunschweig and resemble candidates for the production of high-performance batteries. The composites will be formed inside the spouted bed by mixing the materials and creating aggregates due to the cohesive forces. The main advantage of this novel method are the avoidance of dangerous-to-health solvents, high forces acting in spouted bed processes and at the same time a scale-up potential. To be able to handle three solid streams in the spouted bed simultaneously, two new, different approaches regarding the injection of solids will be evaluated: a central nozzle-like injection and an injection together with the fluidization gas. Therefore, an existing miniaturized spouted bed plant will be reconstructed and afterwards the first composites will be produced, which will be evaluated regarding their mechanical properties and their composition. Especially the stability of the aggregates as well as the distribution of the different materials inside the aggregate are key factors, which determine the later application in solid-state batteries. The electro-chemical properties of the composites, especially the electric and ionic conductivity as well as the chemical stability will be investigated in Braunschweig. By receiving feedback from our partners, the process parameters (e.g. solids mass flows, gas velocities and bed mass) will be changed, to achieve a fundamental understanding of the relationship between process parameters and aggregate structure and produce aggregates with the best properties for the use in all-solid-state batteries. The foundation of this work will be the evaluation and expansion of existing theoretical models for interparticular forces acting during dry coating processes. By using experimental as well simulative methods, the forces (cohesion, breakage, compression) acting on particles during a spouted bed process will be analysed experimentally as well as by simulation. The gas flow inside the plant will be modelled by CFD to determine the velocities of the trajectories of the particles, which indicate the highest stresses acting on the particles. With this knowledge it is possible to simulate the particular interactions in DEM. Goal of this work is the ability to predict the behaviour during a dry coating spouted process by describing the microprocesses numerically. Afterwards, it will be possible to describe the process by population balances, which in turn will be used to create a theoretical model for the use in flowsheet simulations (Dyssol) and lay the foundation for further coupled CFD-DEM simulations of the process, which are planned for the second funding period.
      56
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    Untersuchung der Mikroprozesse bei Interpartikelkollisionen unter trockenen und feuchten Bedingungen
    Due to the very good heat, mass and momentum transfer, fluidized beds are widely applied in several industrial fields, e.g. chemical engineering, combustion, pharmaceutical and food industry, whereby a liquid is often injected for granulation or coating purposes. When the particle is not growing by solidified liquid layers but by wetted particles that stick together, agglomeration takes place, resulting in black-berry shaped and porous particles. The agglomeration may either be desired e.g. for the size-enlargement of food powders, or undesired, e.g. in pharmaceutical coating processes. Alternatively, particle adhesion can occur for particles that undergo glass transition by increasing the temperature. If the process temperature is near the glass transition temperature, the particle local surface may become sticky or rubbery. Particle collision at these spots will subsequently form agglomerates. Independent of the underlying mechanism, the extent of agglomeration of the bed material will determine its further transport within the system and the product quality and morphology. Therefore, this project aims to provide a fundamental understanding of the micro-mechanisms of agglomeration as well as deagglomeration of agglomerates, which is so far missing in literature. These findings will allow a better prediction and control of fluidized bed processes and an increase of the process performance. A multi-scale experimental setup will be used and extended by numerical investigations.In a first step, single particle experiments will be performed. The experimental setup created in a former DFG program (HE 4526/9-1, HE 4526/9-2) will be extended to allow for particle agglomeration. The deagglomeration mechanism will be analyzed by collisions of agglomerates with walls and other particles. Experiments will be performed first at ambient conditions to focus on collision dynamics and statics and later on heat and mass transfer will be integrated. The investigations include model particles as well as visco-elastic materials. The findings from the single particle experiments will be transferred to a fluidized bed process. This will connect the macroscopic process parameters and their influence on the flow behavior dynamics to their influence on the micromechanics of agglomeration on different length and time scales. By comparing the flow patterns and the size distributions of the agglomerates by digital image analysis, a regime map will be obtained for different substance systems indicating the limits for particle agglomeration.CFD-DEM simulations will be used for the numerical investigations. To account for agglomeration and deagglomeration, the effect of liquid bridges will be included into the model. After validation with experimental data, the results from these simulations will be used to construct agglomeration kernels for the open-source dynamic flowsheet simulation tool DYSSOL, which has been developed during DFG Priority Program SPP 1679.
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