Projekt Titel
I³-Projects
Startdatum
January 1, 2019
Enddatum
December 31, 2024
Übergeordnetes Projekt
I³-Programm
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Principal Investigator
Smirnova, Irina
Das I³-Programm ist ein zentraler Bestandteil des Wachstums der TUHH. I³ (sprich Englisch eye-cube) steht hierbei für "Interdisziplinarität und Innovation in den Ingenieurwissenschaften". Dieses Programm hat zum Ziel, neue interdisziplinäre Projekte zu identifizieren und durch eine interne Anschubfinanzierung soweit zu fördern, dass die Projekte anschließend externe Fördermittel einwerben können, sei dies von DFG, EU oder in Form von Bundesmitteln. Idealerweise können hierdurch auch entstehende Keimzellen für zukünftige Forschungsschwerpunkte an der TUHH frühzeitig erkannt werden. Das I³-Programm ist kompetitiv angelegt und gliedert sich in drei Linien mit unterschiedlichen Rahmenbedingungen.

I³-Projects fördern Projekte von zwei Wissenschaftlern für zwei Jahre mit je einer Wissenschaftler­stelle zzgl. Sachmittel. Danach ist ein Anschluss-Antrag als I³-Lab oder die Einwerbung externer Mittel vorstellbar.

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    I³-Project - Cyber Physical Energy Systems - Sustainability, Resilience and Economics
    It is common goal to avoid greenhouse gas (GHG) emissions as soon as possible to overcome issues regarding climate change. In Germany, most reduction can be observed in the electricity sector due to intensive expansion of renewables like wind and photovoltaic energy. Renewable energy mostly arises in form of electric energy, therefore the ongoing GHG reduction is mainly located in the electricity sector. To decarbonize the whole energy system, electric energy should be used in other sectors too which leads to the concept of sector coupling. During energy transition, single big producer will be exchanged by geographically dispersed supply-dependent decentralized energy resources (DER) with different energy quality. Because energy conversion, for example from electricity via Power-to-Gas to hydrogen or further to synthetic methane, is always entailed by efficiency loss, direct electrification of these sectors is a part of this transition. However, this conversion path provides long-term energy storage options with the ability to compensate for seasonal intermittency in energy production. To maintain today’s high standard of supply availability, new concepts for flexibility provision have to be developed in this context. The creation of new flexibility options, which can be provided by generator side as well as demand side, requires sophisticated information and communication technologies (ICT) to achieve the high information density needed. Furthermore, sector coupling happens not only on the primary physical part, but also on the secondary digital part. Fig. 1 below depicts these two coupling paths. Energy transition and sector coupling requires not only changes on the physical and digital side, but also on the market side. Detailed availability of data, e.g. due to the ongoing roll out of smart meters, and the lack of tradability with small amounts of energy produced by DER will result in possible new market concepts. One example for this are virtual power plants, which make use of geographically distributed producer and pooling effects in form of combination of different technologies and more precise forecast possibilities due to stochastic effects. Despite a large number of existing energy models, these mostly consider only one sector. As soon as more sectors participate in the modelled energy provision, modeling depth decreases due to complexity and computational cost. Although simplifications led to the possibility of simulating the overall system, this approach diminishes the result accuracy. Market-related considerations are also often considered specifically for individual sectors. The goal of this project is to develop a co-simulation platform that takes dynamic effects on the physical side into account and is capable of simulating event based ICT models and protocols. Furthermore, optimization algorithms are developed and investigated which allow simulation of coupled effects for this holistic approach and derive optimal operating conditions on the background of the German energy policy goal triangle.
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    I³-Project - Machine Learning in Aeronautical Communications
    The research area of Machine Learning provides methods and data-driven statistical models that "learn" through experimentation or observation. This is advantageous for complex problems where it becomes very difficult if not impossible to design exact models. As a consequence, deep learning achieves breakthroughs mainly in areas where models do not exist at all or human-made models capture only small parts of the reality. The highly dynamic problem space of aeronautical communications in a shared radio spectrum is such a field. While Machine Learning-based methods promise good performance, the common pitfall is that such algorithms provide a well-performing blackbox. In aeronautical communications, however, strict performance guarantees have to be made and kept. In this project, the Institute of Communications and the Institute of Communication Networks will join forces to turn Machine Learning-based methods into a scientifically rigorous approach. Machine Learning-based methods are to be applied, evaluated and explained to problems in the field of communications engineering. These shall be shown to work within strict performance bounds required for safety-critical applications. For this, expert domain knowledge is to be combined with data-driven learning algorithms. The understanding of internal processes is focused upon, and the information bottleneck method shall be applied to gain understanding of the intricacies of deep learning methods. At the same time, novel efficient signal processing units shall be designed, leveraging the information bottleneck method, to develop deep learning solutions that are practically implementable in hardware-constrained communication devices. The ongoing cooperation with scientific and industrial partners as well as the preparation of a project application at the DFG are key objectives of this endeavor.
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    I³-Project - Safety Critical Functions on Many-Core Avionics Architectures
    Complex problems such as investigating the influence of many-core embedded systems for safety-critical systems, usually cannot be solved by an institute alone as it requires the competences of several institutes. An interdisciplinary team consisting of experts from aircraft systems (avionics) and computer sciences (embedded systems) shall address the issue of defining and assessing new many-core architectures. M-7 and E-13-ES work in different fields of safety-critical function development. Although scientific exchange takes place, the potential of both institutes working together on hot topics in that field is currently not realised through joint projects. The first goal is, to tighten the connection of the institutes and to develop a strong core research topic for TUHH. New design- and analysis methods for safety-critical systems and software on many-core architectures shall be developed, taking modern flight control system platforms as use-case. These methods shall especially consider runtime-and qualification aspects (second goal). E-13-ES delivers into the projects the requirements and capabilities of many-core applications through the layer of implementation (bottom-up approach). M-7 provides a realistic, complex reference system as well as system- and architecture requirements (top-down approach). The institutes complement each other in their competences very well in that area. A corporate research platform shall be developed that allows technology assessment and access to more complex projects (third goal). At the end of the project, a virtual research avionics platform (ViRAP) shall run parallelised, safety-critical (redundant) flight control system applications based on many-core technology. New methods and tools shall allow a systematic, model-based system design and simulation-based validation. One aspect is to understand the influence on the overall system when changing the hardware architecture and/or its parameters.
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    I³-Project - Selective Oxy-anion Removal from Drinking Waters by modified Hollow Fiber Membranes
    Situation: In 2020, 30% of the world population had no access to safe and clean drinking water supply. Some of the rreasons for this are microbiological pollution and the presence of arsenate and other heavy metals in raw water sources. High concentration of arsenate in ground water is a health problem for more than 300 million people in 100 countries in the world. Related to arsenate, chromate is another geogene pollutant that causes problems for the water supply of millions people worldwide. Both substances belong to the chemical group of the oxyanions (HAsO42-, CrO42-) and are highly carcinogenic and listed as most hazardous health issues by the WHO (World Heath Organization). Due the negative charge of this substances, ion exchange is a possible technology of the treatment of this raw water. However, this technology is technically complicated as well as cost and energy intensive. Methodology: Goal of this project is the development of a new ultrafiltration membrane which is capable of rejecting microbiological pollutants as well as remove oxyanions by adsorption onto the membrane material. For this, the Institute for Water Resources and Water Supply (TUHH) and the Institute for Polymer Research (HZG) will collaborate interdisciplinary to develop a functionalized polymer membrane. The novel membrane should be able to remove particular substances due its small pore size (10-30 nm) and operate at moderate pressures of max. 0.3 bar. The membrane will be modified with anion exchange groups to create a selective adsorption capacity for arsenate and chromate ions. Due to a periodic backwash, particular fouling will be removed and anion exchange groups will be regenerated. By this technology, only a single filtration is necessary to produce microbiologically safe and oxyanion-free drinking water.
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