@inproceedings{HingleyDikta2019, author = {Hingley, Peter and Dikta, Gerhard}, title = {Finding a well performing box-jenkins forecasting model for annualised patent filings counts}, series = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019}, booktitle = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019}, pages = {24 Folien}, year = {2019}, language = {en} } @incollection{LeiseAltherrSimonetal.2019, author = {Leise, Philipp and Altherr, Lena and Simon, Nicolai and Pelz, Peter F.}, title = {Finding global-optimal gearbox designs for battery electric vehicles}, series = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, booktitle = {Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-21802-7}, doi = {10.1007/978-3-030-21803-4_91}, pages = {916 -- 925}, year = {2019}, abstract = {In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.}, language = {en} } @article{EngelBayerHoltmannetal.2019, author = {Engel, Mareike and Bayer, Hendrik and Holtmann, Dirk and Tippk{\"o}tter, Nils and Ulber, Roland}, title = {Flavin secretion of Clostridium acetobutylicum in a bioelectrochemical system - Is an iron limitation involved?}, series = {Bioelectrochemistry}, journal = {Bioelectrochemistry}, number = {In Press, Accepted Manuscript}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1567-5394}, doi = {10.1016/j.bioelechem.2019.05.014}, year = {2019}, language = {en} } @inproceedings{FunkeBeckmann2019, author = {Funke, Harald and Beckmann, Nils}, title = {Flexible Fuel Operation of a Dry-Low-Nox Micromix Combustor with Variable Hydrogen Methane Mixtures}, series = {Proceedings of International Gas Turbine Congress 2019 Tokyo, November 17-22, 2019, Tokyo, Japan}, booktitle = {Proceedings of International Gas Turbine Congress 2019 Tokyo, November 17-22, 2019, Tokyo, Japan}, isbn = {978-4-89111-010-9}, year = {2019}, language = {en} } @inproceedings{GrundmannBauerBodenetal.2019, author = {Grundmann, Jan Thimo and Bauer, Waldemar and Boden, Ralf and Ceriotti, Matteo and Chand, Suditi and Cordero, Federico and Dachwald, Bernd and Dumont, Etienne and Grimm, Christian D. and Heiligers, Jeannette and Herč{\´i}k, David and H{\´e}rique, Alain and Ho, Tra-Mi and Jahnke, Rico and Kofman, Wlodek and Lange, Caroline and Lichtenheldt, Roy and McInnes, Colin and Meß, Jan-Gerd and Mikschl, Tobias and Mikulz, Eugen and Montenegro, Sergio and Moore, Iain and Pelivan, Ivanka and Peloni, Alessandro and Plettemeier, Dirk and Quantius, Dominik and Reershemius, Siebo and Renger, Thomas and Riemann, Johannes and Rogez, Yves and Ruffer, Michael and Sasaki, Kaname and Schmitz, Nicole and Seboldt, Wolfgang and Seefeldt, Patric and Spietz, Peter and Spr{\"o}witz, Tom and Sznajder, Maciej and T{\´o}th, Norbert and Vergaaij, Merel and Viavattene, Giulia and Wejmo, Elisabet and Wiedemann, Carsten and Wolff, Friederike and Ziach, Christian}, title = {Flights are ten a sail - Re-use and commonality in the design and system engineering of small spacecraft solar sail missions with modular hardware for responsive and adaptive exploration}, series = {70th International Astronautical Congress (IAC)}, booktitle = {70th International Astronautical Congress (IAC)}, isbn = {9781713814856}, pages = {1 -- 7}, year = {2019}, language = {en} } @inproceedings{ChavezBermudezWollert2019, author = {Chavez Bermudez, Victor Francisco and Wollert, J{\"o}rg}, title = {Gateway for Automation Controllers and Cloud based Voice Recognition Services}, series = {KommA, 10. Jahreskolloquium Kommunikation in der Automation}, booktitle = {KommA, 10. Jahreskolloquium Kommunikation in der Automation}, publisher = {Institut f{\"u}r Automation und Kommunikation}, address = {Magdeburg}, organization = {KommA, 2019, Jahreskolloquium Kommunikation in der Automation, 10., Lemgo, DE, 2019-11-20 - 2019-11-21}, isbn = {978-3-944722-85-6}, pages = {1 -- 8}, year = {2019}, language = {en} } @inproceedings{UlmerBraunLaietal.2019, author = {Ulmer, Jessica and Braun, Sebastian and Lai, Chow Yin and Cheng, Chi-Tsun and Wollert, J{\"o}rg}, title = {Generic integration of VR and AR in product lifecycles based on CAD models}, series = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, booktitle = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, year = {2019}, language = {en} } @incollection{DachwaldOhndorf2019, author = {Dachwald, Bernd and Ohndorf, Andreas}, title = {Global optimization of continuous-thrust trajectories using evolutionary neurocontrol}, series = {Modeling and Optimization in Space Engineering}, booktitle = {Modeling and Optimization in Space Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-10501-3}, doi = {10.1007/978-3-030-10501-3_2}, pages = {33 -- 57}, year = {2019}, abstract = {Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.}, language = {en} } @inproceedings{MatareSchifferFerrein2019, author = {Matar{\´e}, Victor and Schiffer, Stefan and Ferrein, Alexander}, title = {golog++ : An integrative system design}, series = {CogRob 2018. Cognitive Robotics Workshop : Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018) Tempe, AZ, USA, October 27th, 2018}, booktitle = {CogRob 2018. Cognitive Robotics Workshop : Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018) Tempe, AZ, USA, October 27th, 2018}, editor = {Steinbauer, Gerald and Ferrein, Alexander}, issn = {1613-0073}, pages = {29 -- 35}, year = {2019}, language = {en} } @inproceedings{LorenzAltherrPelz2019, author = {Lorenz, Imke-Sophie B. and Altherr, Lena and Pelz, Peter F.}, title = {Graph-theoretic resilience analysis of a water distribution system's topology}, series = {World Congress on Resilience, Reliability and Asset Management 2019}, booktitle = {World Congress on Resilience, Reliability and Asset Management 2019}, pages = {106 -- 109}, year = {2019}, abstract = {Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of WDS, i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the resilience of WDS}, language = {en} }