@article{StiemerThomaBraun2023, author = {Stiemer, Luc Nicolas and Thoma, Andreas and Braun, Carsten}, title = {MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation}, series = {PLoS ONE}, volume = {18}, journal = {PLoS ONE}, number = {9}, publisher = {PLOS}, address = {San Fancisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0291415}, pages = {e0291415}, year = {2023}, abstract = {This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking algorithm for bumblebee tracking. It incorporates an offline trained appearance descriptor along with a Kalman Filter for appearance and motion matching. Different detector architectures for upstream detections (You Only Look Once (YOLOv5), Faster Region Proposal Convolutional Neural Network (Faster R-CNN), and RetinaNet) are investigated in a comparative study to optimize performance. The detection models were trained on a dataset containing 11359 labeled bumblebee images. YOLOv5 reaches an Average Precision of AP = 53, 8\%, Faster R-CNN achieves AP = 45, 3\% and RetinaNet AP = 38, 4\% on the bumblebee validation dataset, which consists of 1323 labeled bumblebee images. The tracker's appearance model is trained on 144 samples. The tracker (with Faster R-CNN detections) reaches a Multiple Object Tracking Accuracy MOTA = 93, 5\% and a Multiple Object Tracking Precision MOTP = 75, 6\% on a validation dataset containing 2000 images, competing with state-of-the-art computer vision methods. The framework allows reliable tracking of different bumblebees in the same video stream with rarely occurring identity switches (IDS). MBT3D has much lower IDS than other commonly used algorithms, with one of the lowest false positive rates, competing with state-of-the-art animal tracking algorithms. The developed framework reconstructs the 3-dimensional (3D) flight paths of the bumblebees by triangulation. It also handles and compares two alternative stereo camera pairs if desired.}, language = {en} } @inproceedings{FunkeBeckmannStefanetal.2023, author = {Funke, Harald and Beckmann, Nils and Stefan, Lukas and Keinz, Jan}, title = {Hydrogen combustor integration study for a medium range aircraft engine using the dry-low NOx "Micromix" combustion principle}, series = {Proceedings of the ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition. Volume 1: Aircraft Engine. Boston, Massachusetts, USA. June 26-30, 2023}, booktitle = {Proceedings of the ASME Turbo Expo 2023: Turbomachinery Technical Conference and Exposition. Volume 1: Aircraft Engine. Boston, Massachusetts, USA. June 26-30, 2023}, publisher = {ASME}, address = {New York}, isbn = {978-0-7918-8693-9}, doi = {10.1115/GT2023-102370}, pages = {12 Seiten}, year = {2023}, abstract = {The feasibility study presents results of a hydrogen combustor integration for a Medium-Range aircraft engine using the Dry-Low-NOₓ Micromix combustion principle. Based on a simplified Airbus A320-type flight mission, a thermodynamic performance model of a kerosene and a hydrogen-powered V2530-A5 engine is used to derive the thermodynamic combustor boundary conditions. A new combustor design using the Dry-Low NOx Micromix principle is investigated by slice model CFD simulations of a single Micromix injector for design and off-design operation of the engine. Combustion characteristics show typical Micromix flame shapes and good combustion efficiencies for all flight mission operating points. Nitric oxide emissions are significant below ICAO CAEP/8 limits. For comparison of the Emission Index (EI) for NOₓ emissions between kerosene and hydrogen operation, an energy (kerosene) equivalent Emission Index is used. A full 15° sector model CFD simulation of the combustion chamber with multiple Micromix injectors including inflow homogenization and dilution and cooling air flows investigates the combustor integration effects, resulting NOₓ emission and radial temperature distributions at the combustor outlet. The results show that the integration of a Micromix hydrogen combustor in actual aircraft engines is feasible and offers, besides CO₂ free combustion, a significant reduction of NOₓ emissions compared to kerosene operation.}, language = {en} } @article{BaaderBoxbergChenetal.2023, author = {Baader, Fabian and Boxberg, Marc S. and Chen, Qian and F{\"o}rstner, Roger and Kowalski, Julia and Dachwald, Bernd}, title = {Field-test performance of an ice-melting probe in a terrestrial analogue environment}, series = {Icarus}, journal = {Icarus}, number = {409}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.1016/j.icarus.2023.115852}, pages = {Artikel 115852}, year = {2023}, abstract = {Melting probes are a proven tool for the exploration of thick ice layers and clean sampling of subglacial water on Earth. Their compact size and ease of operation also make them a key technology for the future exploration of icy moons in our Solar System, most prominently Europa and Enceladus. For both mission planning and hardware engineering, metrics such as efficiency and expected performance in terms of achievable speed, power requirements, and necessary heating power have to be known. Theoretical studies aim at describing thermal losses on the one hand, while laboratory experiments and field tests allow an empirical investigation of the true performance on the other hand. To investigate the practical value of a performance model for the operational performance in extraterrestrial environments, we first contrast measured data from terrestrial field tests on temperate and polythermal glaciers with results from basic heat loss models and a melt trajectory model. For this purpose, we propose conventions for the determination of two different efficiencies that can be applied to both measured data and models. One definition of efficiency is related to the melting head only, while the other definition considers the melting probe as a whole. We also present methods to combine several sources of heat loss for probes with a circular cross-section, and to translate the geometry of probes with a non-circular cross-section to analyse them in the same way. The models were selected in a way that minimizes the need to make assumptions about unknown parameters of the probe or the ice environment. The results indicate that currently used models do not yet reliably reproduce the performance of a probe under realistic conditions. Melting velocities and efficiencies are constantly overestimated by 15 to 50 \% in the models, but qualitatively agree with the field test data. Hence, losses are observed, that are not yet covered and quantified by the available loss models. We find that the deviation increases with decreasing ice temperature. We suspect that this mismatch is mainly due to the too restrictive idealization of the probe model and the fact that the probe was not operated in an efficiency-optimized manner during the field tests. With respect to space mission engineering, we find that performance and efficiency models must be used with caution in unknown ice environments, as various ice parameters have a significant effect on the melting process. Some of these are difficult to estimate from afar.}, language = {en} } @incollection{HeimesKampkerDornetal.2023, author = {Heimes, Heiner Hans and Kampker, Achim and Dorn, Benjamin and Kehrer, Mario and D{\"u}nnwald, Simon and Badura, Dennis and Terren, Maximilian and R{\"o}th, Thilo}, title = {Produktionsprozesse der Fahrzeugstruktur}, series = {Elektromobilit{\"a}t: Grundlagen einer Fortschrittstechnologie}, booktitle = {Elektromobilit{\"a}t: Grundlagen einer Fortschrittstechnologie}, editor = {Kampker, Achim and Heimes, Heiner Hans}, publisher = {Springer Vieweg}, address = {Berlin}, isbn = {978-3-662-65811-6 (Print)}, doi = {10.1007/978-3-662-65812-3_13}, pages = {227 -- 247}, year = {2023}, language = {de} } @incollection{HeimesKampkerKehreretal.2023, author = {Heimes, Heiner Hans and Kampker, Achim and Kehrer, Mario and D{\"u}nnwald, Simon and Heetfeld, Lennart and Polzenberg, Jens and Budde, Lucas and Keusen, Maximilian and Pandey, Rahul and R{\"o}th, Thilo}, title = {Fahrzeugstruktur}, series = {Elektromobilit{\"a}t: Grundlagen einer Fortschrittstechnologie}, booktitle = {Elektromobilit{\"a}t: Grundlagen einer Fortschrittstechnologie}, editor = {Kampker, Achim and Heimes, Heiner Hans}, publisher = {Springer Vieweg}, address = {Berlin}, isbn = {978-3-662-65811-6 (Print)}, doi = {10.1007/978-3-662-65812-3_5}, pages = {69 -- 106}, year = {2023}, abstract = {Um sowohl Treibhausgas-Emissionen zu verringern als auch Kraftstoffressourcen zu schonen, wird zunehmend an einer Transformation konventionell angetriebener Kraftfahrzeuge hin zu elektrifizierten Antriebskonzepten gearbeitet. Basierend auf herk{\"o}mmlichen Fahrzeugen mit Verbrennungsmotor wurde eine Vielzahl neuer Antriebssysteme mit verschiedenem Elektrifizierungsgrad entwickelt. Mitte der 1990er-Jahre kamen erste Fahrzeuge mit einem Hybridantrieb auf den Markt. Die Kombination aus Verbrennungs- und Elektromotor erlaubt eine Verbrauchsreduktion und Bremsenergier{\"u}ckgewinnung sowie lokal emissionsfreies Fahren.}, language = {de} } @book{JanserHavermannHoeveleretal.2023, author = {Janser, Frank and Havermann, Marc and Hoeveler, Bastian and Hertz, Cyril and Bergmann, Ole}, title = {Str{\"o}mungslehre und Aerodynamik : inkompressible Profile und Tragfl{\"u}gelaerodynamik, Band 2}, edition = {4. Auflage}, publisher = {Mainz}, address = {Aachen}, isbn = {978-3-8107-0261-6}, pages = {XIII, 211 Seiten}, year = {2023}, abstract = {Das vorliegende Buch dient als Grundlage f{\"u}r die Bachelor- und Master-Ausbildung von Studierenden im Fachgebiet Str{\"o}mungslehre und Aerodynamik. Im hier behandelten Teilbereich der inkompressiblen Profile und Tragfl{\"u}gelaerodynamik werden schwerpunktm{\"a}ßig die folgenden Themen besprochen: - Profilaerodynamik - Tragfl{\"u}gelaerodynamik - Flugzeugpolare - Methoden zur Flugbereichserweiterung - Schwebeschub und Schwebeleistung - Propellerblattaerodynamik - Numerische Methoden zur Tragfl{\"u}gelberechnung}, language = {de} } @article{ThomaThomessenGardietal.2023, author = {Thoma, Andreas and Thomessen, Karolin and Gardi, Alessandro and Fisher, A. and Braun, Carsten}, title = {Prioritising paths: An improved cost function for local path planning for UAV in medical applications}, series = {The Aeronautical Journal}, journal = {The Aeronautical Journal}, number = {First View}, publisher = {Cambridge University Press}, address = {Cambridge}, issn = {0001-9240 (Print)}, doi = {10.1017/aer.2023.68}, pages = {1 -- 18}, year = {2023}, abstract = {Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50\% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26\%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30\%. These results show promise for further enhancements and to support broader applicability.}, language = {en} } @incollection{DachwaldUlamecKowalskietal.2023, author = {Dachwald, Bernd and Ulamec, Stephan and Kowalski, Julia and Boxberg, Marc S. and Baader, Fabian and Biele, Jens and K{\"o}mle, Norbert}, title = {Ice melting probes}, series = {Handbook of Space Resources}, booktitle = {Handbook of Space Resources}, editor = {Badescu, Viorel and Zacny, Kris and Bar-Cohen, Yoseph}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-97912-6 (Print)}, doi = {10.1007/978-3-030-97913-3_29}, pages = {955 -- 996}, year = {2023}, abstract = {The exploration of icy environments in the solar system, such as the poles of Mars and the icy moons (a.k.a. ocean worlds), is a key aspect for understanding their astrobiological potential as well as for extraterrestrial resource inspection. On these worlds, ice melting probes are considered to be well suited for the robotic clean execution of such missions. In this chapter, we describe ice melting probes and their applications, the physics of ice melting and how the melting behavior can be modeled and simulated numerically, the challenges for ice melting, and the required key technologies to deal with those challenges. We also give an overview of existing ice melting probes and report some results and lessons learned from laboratory and field tests.}, language = {en} } @article{SchulzeFeyerlPischinger2023, author = {Schulze, Sven and Feyerl, G{\"u}nter and Pischinger, Stefan}, title = {Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions}, series = {Energies}, volume = {16}, journal = {Energies}, number = {13}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {10.3390/en16135171}, pages = {29 Seiten, Art. Nr.: 5171}, year = {2023}, abstract = {To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15\% more efficiently by 2025 and 30\% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2\% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.}, language = {en} } @article{FayyaziSardarThomasetal.2023, author = {Fayyazi, Mojgan and Sardar, Paramjotsingh and Thomas, Sumit Infent and Daghigh, Roonak and Jamali, Ali and Esch, Thomas and Kemper, Hans and Langari, Reza and Khayyam, Hamid}, title = {Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles}, volume = {15}, number = {6}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/su15065249}, pages = {38}, year = {2023}, abstract = {Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.}, language = {en} }