TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - http://dx.doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Haugg, Albert Thomas A1 - Kreyer, Jörg A1 - Kemper, Hans A1 - Hatesuer, Katerina A1 - Esch, Thomas T1 - Heat exchanger for ORC. adaptability and optimisation potentials T2 - IIR International Rankine 2020 Conference N2 - The recovery of waste heat requires heat exchangers to extract it from a liquid or gaseous medium into another working medium, a refrigerant. In Organic Rankine Cycles (ORC) on Combustion Engines there are two major heat sources, the exhaust gas and the water/glycol fluid from the engine’s cooling circuit. A heat exchanger design must be adapted to the different requirements and conditions resulting from the heat sources, fluids, system configurations, geometric restrictions, and etcetera. The Stacked Shell Cooler (SSC) is a new and very specific design of a plate heat exchanger, created by AKG, which allows with a maximum degree of freedom the optimization of heat exchange rate and the reduction of the related pressure drop. This optimization in heat exchanger design for ORC systems is even more important, because it reduces the energy consumption of the system and therefore maximizes the increase in overall efficiency of the engine. Y1 - 2020 U6 - http://dx.doi.org/10.18462/iir.rankine.2020.1224 N1 - Conference: IIR International Rankine 2020 Conference - Heating, Cooling, Power Generation. Glasgow, 2020. ER - TY - CHAP A1 - Merkens, Torsten A1 - Hebel, Christoph T1 - Sharing mobility concepts – flexible, sustainable, smart T2 - Proceedings of the 1st UNITED – Southeast Asia Automotive Interest Group (SAIG) KW - Sharing mobility KW - electro mobility KW - business models KW - mobility behaviour Y1 - 2021 SN - 978-3-902103-94-9 N1 - Proceedings of the 1st UNITED – Southeast Asia Automotive Interest Group (SAIG), International Conference, International Collaboration towards Sustainable and Green, Automotive Technology, 21-22 April 2021 Chulalongkorn University, Thailand SP - 43 EP - 44 ER - TY - JOUR A1 - Götten, Falk A1 - Finger, Felix A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, M. A1 - Bil, C. T1 - Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization JF - CEAS Aeronautical Journal N2 - The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft. KW - Parasitic drag KW - UAV KW - CFD KW - Aircraft sizing Y1 - 2021 U6 - http://dx.doi.org/10.1007/s13272-021-00522-w SN - 1869-5590 (Online) SN - 1869-5582 (Print) N1 - Corresponding author: Falk Götten VL - 12 SP - 589 EP - 603 PB - Springer CY - Berlin ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Braun, Carsten T1 - Improving the px4 avoid algorithm by bio-inspired flight strategies T2 - DLRK2020 - „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ Y1 - 2020 N1 - Deutscher Luft- und Raumfahrtkongress 2020, 1. bis 3. September 2020 – Online, „Luft- und Raumfahrt – Verantwortung in allen Dimensionen“ ER - TY - JOUR A1 - Schückhaus, Ulrich T1 - Die SkyCab-Erfinder im WFMG-Interview JF - Business in MG Y1 - 2020 N1 - Interview von WFMG – Wirtschaftsförderung Mönchengladbach GmbH, vertreten durch Dr. Ulrich Schückhaus IS - 1 SP - 6 EP - 7 ER - TY - CHAP A1 - Thoma, Andreas A1 - Fisher, Alex A1 - Bertrand, Olivier A1 - Braun, Carsten ED - Vouloutsi, Vasiliki ED - Mura, Anna ED - Tauber, Falk ED - Speck, Thomas ED - Prescott, Tony J. ED - Verschure, Paul F. M. J. T1 - Evaluation of possible flight strategies for close object evasion from bumblebee experiments T2 - Living Machines 2020: Biomimetic and Biohybrid Systems KW - Obstacle avoidance KW - Bumblebees KW - Flight control KW - UAV KW - MAV Y1 - 2020 SN - 978-3-030-64312-6 U6 - http://dx.doi.org/10.1007/978-3-030-64313-3_34 N1 - 9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings SP - 354 EP - 365 PB - Springer CY - Cham ER - TY - JOUR A1 - Götten, Falk A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, Matthew A1 - Bil, Cees T1 - Improved Form Factor for Drag Estimation of Fuselages with Various Cross Sections JF - Journal of Aircraft N2 - The paper presents an aerodynamic investigation of 70 different streamlined bodies with fineness ratios ranging from 2 to 10. The bodies are chosen to idealize both unmanned and small manned aircraft fuselages and feature cross-sectional shapes that vary from circular to quadratic. The study focuses on friction and pressure drag in dependency of the individual body’s fineness ratio and cross section. The drag forces are normalized with the respective body’s wetted area to comply with an empirical drag estimation procedure. Although the friction drag coefficient then stays rather constant for all bodies, their pressure drag coefficients decrease with an increase in fineness ratio. Referring the pressure drag coefficient to the bodies’ cross-sectional areas shows a distinct pressure drag minimum at a fineness ratio of about three. The pressure drag of bodies with a quadratic cross section is generally higher than for bodies of revolution. The results are used to derive an improved form factor that can be employed in a classic empirical drag estimation method. The improved formulation takes both the fineness ratio and cross-sectional shape into account. It shows superior accuracy in estimating streamlined body drag when compared with experimental data and other form factor formulations of the literature. Y1 - 2020 U6 - http://dx.doi.org/10.2514/1.C036032 SN - 1533-3868 SP - 1 EP - 13 PB - AIAA CY - Reston, Va. ER - TY - CHAP A1 - Götten, Falk A1 - Finger, Felix A1 - Braun, Carsten A1 - Havermann, Marc A1 - Bil, C. A1 - Gomez, F. T1 - Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles T2 - APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018) N2 - The results of a statistical investigation of 42 fixed-wing, small to medium sized (20 kg−1000 kg) reconnaissance unmanned air vehicles (UAVs) are presented. Regression analyses are used to identify correlations of the most relevant geometry dimensions with the UAV’s maximum take-off mass. The findings allow an empirical based geometry-build up for a complete unmanned aircraft by referring to its take-off mass only. This provides a bridge between very early design stages (initial sizing) and the later determination of shapes and dimensions. The correlations might be integrated into a UAV sizing environment and allow designers to implement more sophisticated drag and weight estimation methods in this process. Additional information on correlation factors for a rough drag estimation methodology indicate how this technique can significantly enhance the accuracy of early design iterations. KW - Unmanned Air Vehicle KW - Geometry KW - Correlations KW - Statistics KW - Drag Y1 - 2019 SN - 978-981-13-3305-7 U6 - http://dx.doi.org/10.1007/978-981-13-3305-7_109 N1 - APISAT 2018 - Asia-Pacific International Symposium on Aerospace Technology. 16-18 October 2018. Chengdu, China. Lecture Notes in Electrical Engineering (LNEE, volume 459) SP - 1365 EP - 1381 PB - Springer CY - Singapore ER - TY - CHAP A1 - Finger, Felix A1 - Götten, Falk A1 - Braun, Carsten A1 - Bil, C. T1 - On Aircraft Design Under the Consideration of Hybrid-Electric Propulsion Systems T2 - APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018) N2 - A hybrid-electric propulsion system combines the advantages of fuel-based systems and battery powered systems and offers new design freedom. To take full advantage of this technology, aircraft designers must be aware of its key differences, compared to conventional, carbon-fuel based, propulsion systems. This paper gives an overview of the challenges and potential benefits associated with the design of aircraft that use hybrid-electric propulsion systems. It offers an introduction of the most popular hybrid-electric propulsion architectures and critically assess them against the conventional and fully electric propulsion configurations. The effects on operational aspects and design aspects are covered. Special consideration is given to the application of hybrid-electric propulsion technology to both unmanned and vertical take-off and landing aircraft. The authors conclude that electric propulsion technology has the potential to revolutionize aircraft design. However, new and innovative methods must be researched, to realize the full benefit of the technology. KW - Hybrid-electric aircraft KW - Aircraft design KW - Design rules KW - Green aircraft Y1 - 2019 SN - 978-981-13-3305-7 U6 - http://dx.doi.org/10.1007/978-981-13-3305-7_99 N1 - APISAT 2018 - Asia-Pacific International Symposium on Aerospace Technology. 16-18 October 2018. Chengdu, China. Lecture Notes in Electrical Engineering (LNEE, volume 459) SP - 1261 EP - 1272 PB - Springer CY - Singapore ER - TY - JOUR A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles JF - SAE International Journal of Commercial Vehicles N2 - The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed. Y1 - 2020 U6 - http://dx.doi.org/10.4271/02-13-02-0009 SN - 1946-3928 VL - 13 IS - 2 SP - 129 EP - 143 PB - SAE International CY - Warrendale, Pa. ER - TY - JOUR A1 - Serror, Martin A1 - Hack, Sacha A1 - Henze, Martin A1 - Schuba, Marko A1 - Wehrle, Klaus T1 - Challenges and Opportunities in Securing the Industrial Internet of Things JF - IEEE Transactions on Industrial Informatics Y1 - 2021 U6 - http://dx.doi.org/10.1109/TII.2020.3023507 SN - 1941-0050 VL - 17 IS - 5 SP - 2985 EP - 2996 PB - IEEE CY - New York ER - TY - JOUR A1 - Hoeveler, B. A1 - Bauknecht, André A1 - Wolf, C. Christian A1 - Janser, Frank T1 - Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight JF - Journal of Aircraft N2 - 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 Göttingen of DLR, German Aerospace Center in Göttingen 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. Y1 - 2020 U6 - http://dx.doi.org/10.2514/1.C035422 SN - 1533-3868 VL - 57 IS - 4 PB - AIAA CY - Reston, Va. ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - 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. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Pfaff, Raphael A1 - Gidaszewski, Lars A1 - Schmidt, Bernd T1 - Berücksichtigung von No Fault Found im Diagnose- und Instandhaltungssystem von Schienenfahrzeugen JF - ETR - Eisenbahntechnische Rundschau N2 - Intermittierende und nicht reproduzierbare Fehler, auch als No Fault Found bezeichnet, treten in praktisch allen Bereichen auf und sorgen für hohe Kosten. Diese sind häufig auf unpräzise Fehlerbeschreibungen zurückzuführen. Im vorliegenden Beitrag werden Anpassungen der Vorgehensweise bei der Entwicklung und Anpassungen des Diagnosesystems vorgeschlagen. Y1 - 2020 SN - 0013-2845 IS - 5 SP - 56 EP - 59 PB - DVV Media Group CY - Hamburg ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - 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. Y1 - 2020 SN - 2169-3536 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Dinghofer, Kai A1 - Hartung, Frank T1 - Analysis of Criteria for the Selection of Machine Learning Frameworks T2 - 2020 International Conference on Computing, Networking and Communications (ICNC) Y1 - 2020 U6 - http://dx.doi.org/10.1109/ICNC47757.2020.9049650 SP - 373 EP - 377 ER - TY - JOUR A1 - Wilbring, Daniela A1 - Enning, Manfred A1 - Pfaff, Raphael A1 - Schmidt, Bernd T1 - Neue Perspektiven für die Bahn in der Produktions- und Distributionslogistik durch Prozessautomation JF - ETR - Eisenbahntechnische Rundschau Y1 - 2020 SN - 0013-2845 VL - 69 IS - 3 SP - 15 EP - 19 ER - TY - CHAP A1 - Finger, Felix A1 - de Vries, Reynard A1 - Vos, Roelof A1 - Braun, Carsten A1 - Bil, Cees T1 - A comparison of hybrid-electric aircraft sizing methods T2 - AIAA Scitech 2020 Forum Y1 - 2020 U6 - http://dx.doi.org/10.2514/6.2020-1006 N1 - AIAA Scitech 2020 Forum, Driving aerospace solutions for global challenges, Orlando, 06. - 10. January 2020 ER - TY - CHAP A1 - Kreyer, Jörg A1 - Müller, Marvin A1 - Esch, Thomas T1 - A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude T2 - Deutscher Luft- und Raumfahrtkongress 2019, „Luft- und Raumfahrt – technologische Brücke in die Zukunft“, Darmstadt, 30. September bis 2. Oktober 2019 Y1 - 2020 U6 - http://dx.doi.org/10.25967/490162 PB - Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V CY - Bonn ER -