TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - 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. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - http://dx.doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel ER - TY - CHAP A1 - Dachwald, Bernd A1 - Ulamec, Stephan A1 - Kowalski, Julia A1 - Boxberg, Marc S. A1 - Baader, Fabian A1 - Biele, Jens A1 - Kömle, Norbert ED - Badescu, Viorel ED - Zacny, Kris ED - Bar-Cohen, Yoseph T1 - Ice melting probes T2 - Handbook of Space Resources N2 - 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. KW - Ice melting probe KW - Ice penetration KW - Icy moons KW - Ocean worlds KW - Mars Y1 - 2023 SN - 978-3-030-97912-6 (Print) SN - 978-3-030-97913-3 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-97913-3_29 SP - 955 EP - 996 PB - Springer CY - Cham ER - TY - JOUR A1 - Thoma, Andreas A1 - Thomessen, Karolin A1 - Gardi, Alessandro A1 - Fisher, A. A1 - Braun, Carsten T1 - Prioritising paths: An improved cost function for local path planning for UAV in medical applications JF - The Aeronautical Journal N2 - 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. KW - Path planning KW - Cost function KW - Multi-objective optimization Y1 - 2023 U6 - http://dx.doi.org/10.1017/aer.2023.68 SN - 0001-9240 (Print) SN - 2059-6464 (Online) IS - First View SP - 1 EP - 18 PB - Cambridge University Press CY - Cambridge ER - TY - JOUR A1 - Baader, Fabian A1 - Boxberg, Marc S. A1 - Chen, Qian A1 - Förstner, Roger A1 - Kowalski, Julia A1 - Dachwald, Bernd T1 - Field-test performance of an ice-melting probe in a terrestrial analogue environment JF - Icarus N2 - 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. Y1 - 2023 U6 - http://dx.doi.org/10.1016/j.icarus.2023.115852 N1 - Forschungsdaten hierzu: "Performance data of an ice-melting probe from field tests in two different ice environments" (https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/10890) IS - 409 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Feldmann, Marco A1 - Francke, Gero A1 - Espe, Clemes A1 - Chen, Qian A1 - Baader, Fabian A1 - Boxberg, Marc S. A1 - Sustrate, Anna-Marie A1 - Kowalski, Julia A1 - Dachwald, Bernd T1 - Performance data of an ice-melting probe from field tests in two different ice environments N2 - This dataset was acquired at field tests of the steerable ice-melting probe "EnEx-IceMole" (Dachwald et al., 2014). A field test in summer 2014 was used to test the melting probe's system, before the probe was shipped to Antarctica, where, in international cooperation with the MIDGE project, the objective of a sampling mission in the southern hemisphere summer 2014/2015 was to return a clean englacial sample from the subglacial brine reservoir supplying the Blood Falls at Taylor Glacier (Badgeley et al., 2017, German et al., 2021). The standardized log-files generated by the IceMole during melting operation include more than 100 operational parameters, housekeeping information, and error states, which are reported to the base station in intervals of 4 s. Occasional packet loss in data transmission resulted in a sparse number of increased sampling intervals, which where compensated for by linear interpolation during post processing. The presented dataset is based on a subset of this data: The penetration distance is calculated based on the ice screw drive encoder signal, providing the rate of rotation, and the screw's thread pitch. The melting speed is calculated from the same data, assuming the rate of rotation to be constant over one sampling interval. The contact force is calculated from the longitudinal screw force, which es measured by strain gauges. The used heating power is calculated from binary states of all heating elements, which can only be either switched on or off. Temperatures are measured at each heating element and averaged for three zones (melting head, side-wall heaters and back-plate heaters). KW - Ocean Worlds KW - Icy Moons KW - Cryobot KW - Analogue Environments KW - Melting Efficiency KW - Melting Performance KW - Melting Probe KW - Ice Melting Y1 - 2022 U6 - http://dx.doi.org/10.5281/zenodo.6094866 N1 - Forschungsdaten zu "Field-test performance of an ice-melting probe in a terrestrial analogue environment" (https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/10889) ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Carsten A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation JF - International Journal of Production Research N2 - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines. KW - Human factors KW - assistance system KW - gamification KW - adaptive systems KW - manufacturing Y1 - 2023 U6 - http://dx.doi.org/10.1080/00207543.2023.2166140 SN - 0020-7543 (Print) SN - 1366-588X (Online) PB - Taylor & Francis ER - TY - JOUR A1 - Böhnisch, Nils A1 - Braun, Carsten A1 - Muscarello, Vincenzo A1 - Marzocca, Pier T1 - About the wing and whirl flutter of a slender wing–propeller system JF - Journal of Aircraft N2 - Next-generation aircraft designs often incorporate multiple large propellers attached along the wingspan (distributed electric propulsion), leading to highly flexible dynamic systems that can exhibit aeroelastic instabilities. This paper introduces a validated methodology to investigate the aeroelastic instabilities of wing–propeller systems and to understand the dynamic mechanism leading to wing and whirl flutter and transition from one to the other. Factors such as nacelle positions along the wing span and chord and its propulsion system mounting stiffness are considered. Additionally, preliminary design guidelines are proposed for flutter-free wing–propeller systems applicable to novel aircraft designs. The study demonstrates how the critical speed of the wing–propeller systems is influenced by the mounting stiffness and propeller position. Weak mounting stiffnesses result in whirl flutter, while hard mounting stiffnesses lead to wing flutter. For the latter, the position of the propeller along the wing span may change the wing mode shapes and thus the flutter mechanism. Propeller positions closer to the wing tip enhance stability, but pusher configurations are more critical due to the mass distribution behind the elastic axis. Y1 - 2024 U6 - http://dx.doi.org/10.2514/1.C037542 SN - 1533-3868 SP - 1 EP - 14 PB - American Institute of Aeronautics and Astronautics ER - TY - CHAP A1 - Thoma, Andreas A1 - Stiemer, Luc A1 - Braun, Carsten A1 - Fisher, Alex A1 - Gardi, Alessandro G. T1 - Potential of hybrid neural network local path planner for small UAV in urban environments T2 - AIAA SCITECH 2023 Forum N2 - This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance. Y1 - 2023 U6 - http://dx.doi.org/10.2514/6.2023-2359 N1 - AIAA SCITECH 2023 Forum, 23-27 January 2023, National Harbor, MD & Online PB - AIAA ER - TY - JOUR A1 - Stiemer, Luc Nicolas A1 - Thoma, Andreas A1 - Braun, Carsten T1 - MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation JF - PLoS ONE N2 - 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. Y1 - 2023 U6 - http://dx.doi.org/10.1371/journal.pone.0291415 SN - 1932-6203 N1 - Corresponding author: Luc Nicolas Stiemer VL - 18 IS - 9 PB - PLOS CY - San Fancisco ER - TY - JOUR A1 - Christen, Marc A1 - Kowalski, Julia A1 - Bartelt, Perry T1 - RAMMS: Numerical simulation of dense snow avalanches in three-dimensional terrain JF - Cold Regions Science and Technology N2 - Numerical avalanche dynamics models have become an essential part of snow engineering. Coupled with field observations and historical records, they are especially helpful in understanding avalanche flow in complex terrain. However, their application poses several new challenges to avalanche engineers. A detailed understanding of the avalanche phenomena is required to construct hazard scenarios which involve the careful specification of initial conditions (release zone location and dimensions) and definition of appropriate friction parameters. The interpretation of simulation results requires an understanding of the numerical solution schemes and easy to use visualization tools. We discuss these problems by presenting the computer model RAMMS, which was specially designed by the SLF as a practical tool for avalanche engineers. RAMMS solves the depth-averaged equations governing avalanche flow with accurate second-order numerical solution schemes. The model allows the specification of multiple release zones in three-dimensional terrain. Snow cover entrainment is considered. Furthermore, two different flow rheologies can be applied: the standard Voellmy–Salm (VS) approach or a random kinetic energy (RKE) model, which accounts for the random motion and inelastic interaction between snow granules. We present the governing differential equations, highlight some of the input and output features of RAMMS and then apply the models with entrainment to simulate two well-documented avalanche events recorded at the Vallée de la Sionne test site. KW - RAMMS KW - snow KW - avalanche Y1 - 2010 U6 - http://dx.doi.org/10.1016/j.coldregions.2010.04.005 SN - 1872-7441 VL - 63 IS - 1-2 SP - 1 EP - 14 PB - Elsevier CY - Amsterdam ER -