TY - JOUR A1 - Rupp, Matthias A1 - Schulze, Sven A1 - Kuperjans, Isabel T1 - Comparative life cycle analysis of conventional and hybrid heavy-duty trucks JF - World electric vehicle journal N2 - Heavy-duty trucks are one of the main contributors to greenhouse gas emissions in German traffic. Drivetrain electrification is an option to reduce tailpipe emissions by increasing energy conversion efficiency. To evaluate the vehicle’s environmental impacts, it is necessary to consider the entire life cycle. In addition to the daily use, it is also necessary to include the impact of production and disposal. This study presents the comparative life cycle analysis of a parallel hybrid and a conventional heavy-duty truck in long-haul operation. Assuming a uniform vehicle glider, only the differing parts of both drivetrains are taken into account to calculate the environmental burdens of the production. The use phase is modeled by a backward simulation in MATLAB/Simulink considering a characteristic driving cycle. A break-even analysis is conducted to show at what mileage the larger CO2eq emissions due to the production of the electric drivetrain are compensated. The effect of parameter variation on the break-even mileage is investigated by a sensitivity analysis. The results of this analysis show the difference in CO2eq/t km is negative, indicating that the hybrid vehicle releases 4.34 g CO2eq/t km over a lifetime fewer emissions compared to the diesel truck. The break-even analysis also emphasizes the advantages of the electrified drivetrain, compensating the larger emissions generated during production after already a distance of 15,800 km (approx. 1.5 months of operation time). The intersection coordinates, distance, and CO2eq, strongly depend on fuel, emissions for battery production and the driving profile, which lead to nearly all parameter variations showing an increase in break-even distance. Y1 - 2018 U6 - http://dx.doi.org/10.3390/wevj9020033 SN - 2032-6653 VL - 9 IS - 2 SP - Article No. 33 PB - MDPI CY - Basel ER - TY - JOUR A1 - Röhlen, Desiree A1 - Pilas, Johanna A1 - Dahmen, Markus A1 - Keusgen, Michael A1 - Selmer, Thorsten A1 - Schöning, Michael Josef T1 - Toward a Hybrid Biosensor System for Analysis of Organic and Volatile Fatty Acids in Fermentation Processes JF - Frontiers in Chemistry N2 - Monitoring of organic acids (OA) and volatile fatty acids (VFA) is crucial for the control of anaerobic digestion. In case of unstable process conditions, an accumulation of these intermediates occurs. In the present work, two different enzyme-based biosensor arrays are combined and presented for facile electrochemical determination of several process-relevant analytes. Each biosensor utilizes a platinum sensor chip (14 × 14 mm²) with five individual working electrodes. The OA biosensor enables simultaneous measurement of ethanol, formate, d- and l-lactate, based on a bi-enzymatic detection principle. The second VFA biosensor provides an amperometric platform for quantification of acetate and propionate, mediated by oxidation of hydrogen peroxide. The cross-sensitivity of both biosensors toward potential interferents, typically present in fermentation samples, was investigated. The potential for practical application in complex media was successfully demonstrated in spiked sludge samples collected from three different biogas plants. Thereby, the results obtained by both of the biosensors were in good agreement to the applied reference measurements by photometry and gas chromatography, respectively. The proposed hybrid biosensor system was also used for long-term monitoring of a lab-scale biogas reactor (0.01 m³) for a period of 2 months. In combination with typically monitored parameters, such as gas quality, pH and FOS/TAC (volatile organic acids/total anorganic carbonate), the amperometric measurements of OA and VFA concentration could enhance the understanding of ongoing fermentation processes. Y1 - 2018 U6 - http://dx.doi.org/10.3389/fchem.2018.00284 IS - 6 PB - Frontiers CY - Lausanne ER - TY - JOUR A1 - Röth, Thilo A1 - Pielen, Michael A1 - Wolff, Klaus A1 - Lüdiger, Thomas T1 - Urbane Fahrzeugkonzepte für die Shared Mobility JF - Automobiltechnische Zeitschrift - ATZ N2 - Urbane Mobilitätskonzepte der Zukunft erfordern neue Unternehmensformen, idealerweise aus Old Economy und New Economy, sowie eine enge Anbindung an die gesellschaftsrelevante Zukunftsforschung. Für neue Fahrzeugkonzepte des Carsharing bedeutet dies, dass alle kostenverursachenden Faktoren erfasst und analysiert werden müssen. Die FH Aachen, share2drive und FEV geben einen Ausblick auf die zukünftige Fahrzeugklasse der Personal Public Vehicles als „Rolling Device“. Y1 - 2018 U6 - http://dx.doi.org/10.1007/s35148-017-0176-8 SN - 0001-2785 VL - 120 IS - 1 SP - 18 EP - 23 PB - Springer Vieweg CY - Wiesbaden ER - TY - JOUR A1 - Schiffer, Stefan A1 - Ferrein, Alexander T1 - ERIKA—Early Robotics Introduction at Kindergarten Age JF - Multimodal Technologies Interact N2 - In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents. Y1 - 2018 U6 - http://dx.doi.org/10.3390/mti2040064 SN - 2414-4088 VL - 2 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schirra, Julian A1 - Bissonnette, William A1 - Bramesfeld, Götz T1 - Wake-model effects on induced drag prediction of staggered boxwings JF - Aerospace Y1 - 2018 U6 - http://dx.doi.org/10.3390/aerospace5010014 SN - 2226-4310 VL - 5 IS - 1 ER - TY - JOUR A1 - Schmidt, Bernd A1 - Enning, Manfred A1 - Pfaff, Raphael T1 - Güterwagen 4.0 – Der Güterwagen für das Internet der Dinge Teil 3: Einführungsszenarien für aktive, kommunikative Güterwagen JF - ETR - Eisenbahntechnische Rundschau N2 - Wenn durch innovative, automatisierte Güterwagen betriebswirtschaftliche Vorteile nutzbar gemacht werden sollen, muss die Migration auf das neue System in sinnvollen Teilschritten unter Berücksichtigung der organisationellen und betrieblichen Vereinbarkeit vorgenommen werden. Eine stufenweise Migration mit Nachrüstbarkeit und Kompatibilität kann die optimale Ausstattungsvariante für die unterschiedlichen Betriebsszenarien sowie eine Steigerung der Wirtschaftlichkeit des Gesamtsystems bieten. Y1 - 2018 SN - 0013-2845 VL - 67 IS - 5 SP - 60 EP - 64 PB - DVV Media Group CY - Hamburg ER - TY - JOUR A1 - Schwabedal, Justus T. C. A1 - Sippel, Daniel A1 - Brandt, Moritz D. A1 - Bialonski, Stephan T1 - Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning N2 - Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle. Y1 - 2018 U6 - http://dx.doi.org/10.48550/arXiv.1809.08443 ER - TY - JOUR A1 - Sun, Hui A1 - Altherr, Lena A1 - Pei, Ji A1 - Pelz, Peter F. A1 - Yuan, Shouqi T1 - Optimal booster station design and operation under uncertain load JF - Applied Mechanics and Materials N2 - Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the system’s resilience can be engineered KW - Stochastic Programming KW - Chance Constraint KW - Engineering Application KW - Pump System KW - Water Distribution Y1 - 2018 U6 - http://dx.doi.org/10.4028/www.scientific.net/AMM.885.102 SN - 1662-7482 VL - 885 SP - 102 EP - 115 PB - Trans Tech Publications CY - Bäch ER - TY - JOUR A1 - Svaneborg, Carsten A1 - Karimi-Varzaneh, Hossein Ali A1 - Hojdis, Nils A1 - Fleck, Franz A1 - Everaers, Ralf T1 - Kremer-Grest Models for Universal Properties of Specific Common Polymer Species JF - Soft Condensed Matter N2 - The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and Müller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli. Y1 - 2018 IS - 1606.05008 ER - TY - JOUR A1 - Tekin, Nurettin A1 - Ashikaga, Mitsugu A1 - Horikawa, Atsushi A1 - Funke, Harald T1 - Enhancement of fuel flexibility of industrial gas turbines by development of innovative hydrogen combustion systems JF - Gas for energy N2 - For fuel flexibility enhancement hydrogen represents a possible alternative gas turbine fuel within future low emission power generation, in case of hydrogen production by the use of renewable energy sources such as wind energy or biomass. Kawasaki Heavy Industries, Ltd. (KHI) has research and development projects for future hydrogen society; production of hydrogen gas, refinement and liquefaction for transportation and storage, and utilization with gas turbine / gas engine for the generation of electricity. In the development of hydrogen gas turbines, a key technology is the stable and low NOx hydrogen combustion, especially Dry Low Emission (DLE) or Dry Low NOx (DLN) hydrogen combustion. Due to the large difference in the physical properties of hydrogen compared to other fuels such as natural gas, well established gas turbine combustion systems cannot be directly applied for DLE hydrogen combustion. Thus, the development of DLE hydrogen combustion technologies is an essential and challenging task for the future of hydrogen fueled gas turbines. The DLE Micro-Mix combustion principle for hydrogen fuel has been in development for many years to significantly reduce NOx emissions. This combustion principle is based on cross-flow mixing of air and gaseous hydrogen which reacts in multiple miniaturized “diffusion-type” flames. The major advantages of this combustion principle are the inherent safety against flashback and the low NOx-emissions due to a very short residence time of the reactants in the flame region of the micro-flames. Y1 - 2018 IS - 2 PB - Vulkan-Verlag CY - Essen ER -