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    Scale-up of aerobic bioreactors by Eulerian and Lagrangian approaches
    This project aims to improve the scale-up tools for industrial aerobic bioreactors. The reduction of greenhouse gases emissions is based, among other solutions, on the decarbonation of industries, and especially of the production of chemicals and fuels (including Sustainable Aviation Fuels). In this regard, biotechnologies make it possible to replace some fossil-based chemicals and fuels with bio-based alternatives produced by selective and energy-efficient fermentation processes. However, the scale-up of bioreactors is a non-trivial task, for which CFD has been identified for years as a promising extrapolation tool, replacing empirical correlations that are too imprecise. But its use remains limited by the difficulty of predicting the properties of gas-liquid systems such as the size of bubbles, their velocity, and their trajectories, especially in complex fermentation environments. The proposed strategy is based on two major originalities. From an experimental point of view, it is proposed to investigate the properties of the gas phase of some aerated stirred tanks over a wide range of scales, i.e., from 20L to 15000L, taking advantage of existing experimental setups at IFPEN and TU Hamburg. From a numerical point of view, Lattice-Boltzmann modeling will be used to follow the evolution of a realistic large number of bubbles (up to several millions) in a Lagrangian framework. This rigorous digital twin will allow us to analyze bubble trajectories in pilot-scale stirred tanks, which in turn will serve as a basis for validating or improving the closure laws employed in Euler/Euler RANS CFD models. Such Euler/Euler approaches are less spatially resolved but capable of simulating bioreactors at industrial scale. The validation of the improved Euler/Euler approach will be carried out in the 15000L setup available in TU Hamburg.
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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.
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    SPP 2240: Establishing jet loop reactors as scalable bioelectrochemical reactor systems for anodic and cathodic production processes
    Bioelectrochemical reactor systems are typically surface limited. It is the amount of electrode surface area per reactor volume that is key for advancing space-time-yields. At the same time the electrode surface and the electroactive organisms building a biofilm on the electrodes have to be seen as one composite material that can be advanced regarding the interaction of its components. Last but not least it is challenging to construct these surface dependent reactor systems in a way that dead volumes are avoided and the architecture of the living whole cell biocatalyst is steered towards process optimization. To address these topics we will engineer a scalable bioelectrochemical jet loop reactor concept and will show its versatility by operating it as microbial electrolysis as well as bioelectrosynthesis platform. In the bioelectrosynthesis research direction we will operate it with the recently isolated extremophile Kyrpidia spormannii and aim to produce biomass and the biopolymer polyhydroxybutyrate from carbon dioxide and electrical energy. In the microbial electrolysis research direction, we will increase reactor performance by producing synthetic conductive nanowires as well as conductive direct cell-cell connections. To this end we will use Shewanella oneidensis as well as a currently developed Escherichia coli strain as model organism and produce the platform chemical acetoin in an anode assisted fermentation. In both reactor configurations we will be able to benefit from additive manufacturing of 3D-electrodes as well as their functionalization by conductive polymers.
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    CRC 1615 - Project B04: Tailored transport processes in multiphase reactors
    Project B04 investigates transport processes in the vicinity of nanostructured surfaces, which are an essential component of SMART reactors. Test microreactors with defined but manipulable flow characteristics are built to determine the influence of partially functionalized and switchable interfaces on mass transport processes. These are analysed using microscopic flow measurements with fluorescent particles and concentration imaging with pH-sensitive dyes. Phenomenological models of the transport processes are derived by correlating Lagrangian analysis with concentration fields. The results enable the optimisation of the positioning and design of nanostructured interfaces in SMART reactors.
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    CRC 1615 - Project C01: Integration of components into adaptive geometries
    Within this project, self-adaptive structures that control reactions based on the reactor conditions are investigated. In the beginning, suitable unit cells and materials for selected reactions are investigated, so that structures for high heat- and mass transport can be designed. With this, self-adapting, additive manufactured (AM) structures with temperature-controlled actuators, as well as self-adapting AM structures with pH-controlled actuators will be investigated. Furthermore, the integration of components for in situ detection & self-adjustment into AM structures is part of the research activities. The final step is the validation by means of experiments and CFD.
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    CRC 1615 - Project B06: Systematic multiscale modelling and design approach for SMART reactors
    In this project, a systematic approach for multiscale modelling and design of SMART reactors is developed. For this purpose, internal structures of multiphase reactors are analysed and locally optimized by means of high-resolution validated CFD simulations. In addition, superstructure optimization will be used to derive optimal reactor networks, as well as systemic and compartment models, on the basis of which a systematic optimization-based design of local and global reactor structures will be performed. In the course of the SFB, the flexibility of smart components will be systematically considered by a multistage optimization approach to enable autonomous SMART reactors.
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