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Objective
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Method
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Result
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
Conclusion
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
The enantioselective synthesis of α-hydroxy ketones and vicinal diols is an intriguing field because of the broad applicability of these molecules. Although, butandiol dehydrogenases are known to play a key role in the production of 2,3-butandiol, their potential as biocatalysts is still not well studied. Here, we investigate the biocatalytic properties of the meso-butanediol dehydrogenase from Bacillus licheniformis DSM 13T (BlBDH). The encoding gene was cloned with an N-terminal StrepII-tag and recombinantly overexpressed in E. coli. BlBDH is highly active towards several non-physiological diketones and α-hydroxyketones with varying aliphatic chain lengths or even containing phenyl moieties. By adjusting the reaction parameters in biotransformations the formation of either the α-hydroxyketone intermediate or the diol can be controlled.
Sekundäre galvanische Zelle
(2020)
Die vorliegende Erfindung betrifft eine sekundäre galvanische Zelle, umfassend eine Kathode, eine Anode und einen Separator, der zwischen der Kathode und der Anode angeordnet ist, wobei die Kathode ein erstes elastomeres Polymer umfasst, welches mit einem ersten Füllstoff als Kathodenmaterial gefüllt ist, wobei die Anode ein zweites elastomeres Polymer umfasst, welches mit einem zweiten Füllstoff als Anodenmaterial gefüllt ist, wobei der Separator ein drittes elastomeres Polymer umfasst, wobei das erste elastomere Polymer, das zweite elastomere Polymer und das dritte elastomere Polymer unabhängig voneinander aus vernetzungsfähigen Dienkautschuken ausgewählt sind, und wobei zumindest eines von dem ersten elastomeren Polymer, dem zweiten elastomeren Polymer und dem dritten elastomeren Polymer eine ionische Flüssigkeit und/oder ein elektrisch leitfähiges Polymer enthält. Die vorliegende Erfindung betrifft ferner eine wiederaufladbare Batterie, umfassend die erfindungsgemäße sekundäre galvanische Zelle, ein Verfahren zur Herstellung einer sekundären galvanischen Zelle sowie die Verwendung der erfindungsgemäßen sekundären galvanischen Zelle sowie der erfindungsgemäßen wiederaufladbaren Batterie.
Dargestellt und beansprucht ist eine Funkeinheit mit einem Funkbauteil, einer elektrisch leitfähigen Antenne und einem Kunststoffverbindungsmittel. Das Funkbauteil weist einen Antennenanschluss auf. Das Kunststoffverbindungsmittel weist ein erstes Elastomermaterial mit elektrisch leitfähigem Zusatzmaterial auf, so dass das Kunststoffverbindungsmittel elektrisch leitfähig ist. Das Kunststoffverbindungsmittel bildet eine mechanische und elektrisch leitfähige Verbindung zwischen dem Antennenanschluss und der Antenne. Weiterhin wird eine Vorrichtung mit einem ein Matrixmaterial mit oder aus einem zweiten Elastomermaterial und einer Funkeinheit beschrieben und beansprucht, wobei die Funkeinheit vollständig in das Matrixmaterial eingebettet ist. Die Vorrichtung kann insbesondere ein Fahrzeugreifen sein.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.
The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example
system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient
system behaviour.
The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
There is a broad international discussion about rethinking engineering education in order to educate engineers to cope with future challenges, and particularly the sustainable development goals. In this context, there is a consensus about the need to shift from a mostly technical paradigm to a more holistic problem-based approach, which can address the social embeddedness of technology in society. Among the strategies suggested to address this social embeddedness, design thinking has been proposed as an essential complement to engineering precisely for this purpose. This chapter describes the requirements for integrating the design thinking approach in engineering education. We exemplify the requirements and challenges by presenting our approach based on our course experiences at RWTH Aachen University. The chapter first describes the development of our approach of integrating design thinking in engineering curricula, how we combine it with the Sustainable Development Goals (SDG) as well as the role of sustainability and social responsibility in engineering. Secondly, we present the course “Expanding Engineering Limits: Culture, Diversity, and Gender” at RWTH Aachen University. We describe the necessity to theoretically embed the method in social and cultural context, giving students the opportunity to reflect on cultural, national, or individual “engineering limits,” and to be able to overcome them using design thinking as a next step for collaborative project work. The paper will suggest that the successful implementation of design thinking as a method in engineering education needs to be framed and contextualized within Science and Technology Studies (STS).
Implementation of gender and diversity perspectives in transport development plans in germany
(2020)
As mobility should ensure the accessibility to and participation in society, transport planning has to deal with a variety of gender and diversity categories affecting users’ mobility needs and patterns. Exemplified by an analysis of an instrument of transport development processes – German Transport Development Plans (TDPs) – we investigated to what extent diverse target groups and their mobility requirements are implemented in transport strategy papers. Research results illustrate a still-prevalent neglect of several relevant gender and diversity categories while prioritizing and focusing on eco-friendly topics. But how sustainable can transport be without facing the diversification of life circumstances?