@article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, number = {Art. 9108222}, publisher = {IEEE}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {111381 -- 111393}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @article{DachwaldUlamecPostbergetal.2020, author = {Dachwald, Bernd and Ulamec, Stephan and Postberg, Frank and Sohl, Frank and Vera, Jean-Pierre de and Christoph, Waldmann and Lorenz, Ralph D. and Hellard, Hugo and Biele, Jens and Rettberg, Petra}, title = {Key technologies and instrumentation for subsurface exploration of ocean worlds}, series = {Space Science Reviews}, volume = {216}, journal = {Space Science Reviews}, number = {Art. 83}, publisher = {Springer}, address = {Dordrecht}, issn = {1572-9672}, doi = {10.1007/s11214-020-00707-5}, pages = {45}, year = {2020}, abstract = {In this chapter, the key technologies and the instrumentation required for the subsurface exploration of ocean worlds are discussed. The focus is laid on Jupiter's moon Europa and Saturn's moon Enceladus because they have the highest potential for such missions in the near future. The exploration of their oceans requires landing on the surface, penetrating the thick ice shell with an ice-penetrating probe, and probably diving with an underwater vehicle through dozens of kilometers of water to the ocean floor, to have the chance to find life, if it exists. Technologically, such missions are extremely challenging. The required key technologies include power generation, communications, pressure resistance, radiation hardness, corrosion protection, navigation, miniaturization, autonomy, and sterilization and cleaning. Simpler mission concepts involve impactors and penetrators or - in the case of Enceladus - plume-fly-through missions.}, language = {en} } @article{HoevelerBauknechtWolfetal.2020, author = {Hoeveler, B. and Bauknecht, Andr{\´e} and Wolf, C. Christian and Janser, Frank}, title = {Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight}, series = {Journal of Aircraft}, volume = {57}, journal = {Journal of Aircraft}, number = {4}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-3868}, doi = {10.2514/1.C035422}, year = {2020}, abstract = {It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility G{\"o}ttingen of DLR, German Aerospace Center in G{\"o}ttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25\% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1\%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan.}, language = {en} } @article{GoettenHavermannBraunetal.2020, author = {G{\"o}tten, Falk and Havermann, Marc and Braun, Carsten and Marino, Matthew and Bil, Cees}, title = {Airfoil drag at low-to-medium reynolds numbers: A novel estimation method}, series = {AIAA Journal}, volume = {58}, journal = {AIAA Journal}, number = {7}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-385X}, doi = {10.2514/1.J058983}, pages = {2791 -- 2805}, year = {2020}, abstract = {This paper presents a novel method for airfoil drag estimation at Reynolds numbers between 4×10⁵ and 4×10⁶. The novel method is based on a systematic study of 40 airfoils applying over 600 numerical simulations and considering natural transition. The influence of the airfoil thickness-to-chord ratio, camber, and freestream Reynolds number on both friction and pressure drag is analyzed in detail. Natural transition significantly affects drag characteristics and leads to distinct drag minima for different Reynolds numbers and thickness-to-chord ratios. The results of the systematic study are used to develop empirical correlations that can accurately predict an airfoil drag at low-lift conditions. The new approach estimates a transition location based on airfoil thickness-to-chord ratio, camber, and Reynolds number. It uses the transition location in a mixed laminar-turbulent skin-friction calculation, and corrects the skin-friction coefficient for separation effects. Pressure drag is estimated separately based on correlations of thickness-to-chord ratio, camber, and Reynolds number. The novel method shows excellent accuracy when compared with wind-tunnel measurements of multiple airfoils. It is easily integrable into existing aircraft design environments and is highly beneficial in the conceptual design stage.}, language = {en} } @article{MaurischatPerkins2020, author = {Maurischat, Andreas and Perkins, Rudolph}, title = {Taylor coefficients of Anderson generating functions and Drinfeld torsion extensions}, number = {Vol. 18, No. 01}, publisher = {World Scientific}, address = {Singapur}, doi = {10.1142/S1793042122500099}, pages = {113 -- 130}, year = {2020}, abstract = {We generalize our work on Carlitz prime power torsion extension to torsion extensions of Drinfeld modules of arbitrary rank. As in the Carlitz case, we give a description of these extensions in terms of evaluations of Anderson generating functions and their hyperderivatives at roots of unity. We also give a direct proof that the image of the Galois representation attached to the p-adic Tate module lies in the p-adic points of the motivic Galois group. This is a generalization of the corresponding result of Chang and Papanikolas for the t-adic case.}, language = {en} } @article{HeinEubanksHibberdetal.2020, author = {Hein, Andreas M. and Eubanks, T. Marshall and Hibberd, Adam and Fries, Dan and Schneider, Jean and Lingam, Manasvi and Kennedy, Robert and Perakis, Nikolaos and Dachwald, Bernd and Kervella, Pierre}, title = {Interstellar Now! Missions to and sample returns from nearby interstellar objects}, publisher = {Elsevier}, address = {Amsterdam}, pages = {1 -- 8}, year = {2020}, abstract = {The recently discovered first high velocity hyperbolic objects passing through the Solar System, 1I/'Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects. In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system. In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology. We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition. Interstellar objects likely formed very far from the solar system in both time and space; their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy. These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system.}, language = {en} } @article{WildSchrezenmeierCzupallaetal.2020, author = {Wild, Dominik and Schrezenmeier, Johannes and Czupalla, Markus and F{\"o}rstner, Markus}, title = {Thermal Characterization of additive manufactured Integral Structures for Phase Change Applications}, series = {2020 International Conference on Environmental Systems}, journal = {2020 International Conference on Environmental Systems}, publisher = {Texas Tech University}, year = {2020}, abstract = {"Infused Thermal Solutions" (ITS) introduces a method for passive thermal control to stabilize structural components thermally without active heating and cooling systems, by using phase change material (PCM) in combination with lattice - both embedded into an additive manufactured integral structure. The technology is currently under development. This paper presents the results of the thermal property measurements performed on additive manufactured ITS breadboards. Within the breadboard campaigns key characteristics of the additive manufactured specimens were derived: Mechanical parameters: specimen impermeability, minimum wall thickness, lattice structure, subsequent heat treatment. Thermal properties: thermo-optical surface properties of the additive manufactured raw material, thermal conductivity and specific heat capacity measurements. As a conclusion the paper introduces an overview of potential ITS hardware applications, expected to increase the thermal performance.}, language = {en} } @techreport{ThomaLaarmannMerkensetal.2020, author = {Thoma, Andreas and Laarmann, Lukas and Merkens, Torsten and Franzke, Till and M{\"o}hren, Felix and Buttermann, Lilly and van der Weem, Dirk and Fischer, Maximilian and Misch, Philipp and B{\"o}hme, Mirijam and R{\"o}th, Thilo and Hebel, Christoph and Ritz, Thomas and Franke, Marina and Braun, Carsten}, title = {Entwicklung eines intermodalen Mobilit{\"a}tskonzeptes f{\"u}r die Pilotregion NRW/Rhein-Maas Euregio und Schaffung voller Kundenakzeptanz durch Transfer von Standards aus dem PKW-Bereich auf ein Flugtaxi : Schlussbericht : Projektakronym: SkyCab (Kategorie B) : Laufzeit in Monaten: 6 : Hauptthema: Kategorie B: Innovative Ideen mit Bezug zu UAS/Flugtaxis}, publisher = {FH Aachen}, address = {Aachen}, pages = {97 Seiten}, year = {2020}, language = {de} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0}, series = {IEEE Access}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York, NY}, isbn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {1 -- 12}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @inproceedings{GoettenFingerHavermannetal.2020, author = {G{\"o}tten, Falk and Finger, Felix and Havermann, Marc and Braun, Carsten and Marino, Matthew and Bil, Cees}, title = {Full Configuration Drag Estimation of Small-to-Medium Range UAVs and its Impact on Initial Sizing Optimization}, series = {Deutscher Luft- und Raumfahrtkongress - DLRK 2020}, booktitle = {Deutscher Luft- und Raumfahrtkongress - DLRK 2020}, year = {2020}, language = {en} }