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Dynamic loads significantly impact the structural design of propeller blades due to fatigue and static strength. Since propellers are elastic structures, deformations and aerodynamic loads are coupled. In the past, propeller manufacturers established procedures to determine unsteady aerodynamic loads and the structural response with analytical steady-state calculations. According to the approach, aeroelastic coupling primarily consists of torsional deformations. They neglect bending deformations, deformation velocities, and inertia terms. This paper validates the assumptions above for a General Aviation propeller and a lift propeller for urban air mobility or large cargo drones. Fully coupled reduced-order simulations determine the dynamic loads in the time domain. A quasi-steady blade element momentum approach transfers loads to one-dimensional finite beam elements. The simulation results are in relatively good agreement with the analytical method for the General Aviation propeller but show increasing errors for the slender lift propeller. The analytical approach is modified to consider the induced velocities. Still, inertia and velocity proportional terms play a significant role for the lift propeller due to increased elasticity. The assumption that only torsional deformations significantly impact the dynamic loads of propellers is not valid. Adequate determination of dynamic loads of such designs requires coupled aeroelastic simulations or advanced analytical procedures.
Ice melting probes
(2023)
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.
New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier–Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40% up to 85%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments.
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.
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.
Research on robotic lunar exploration has seen a broad revival, especially since the Google Lunar X-Prize increasingly brought private endeavors into play. This development is supported by national agencies with the aim of enabling long-term lunar infrastructure for in-situ operations and the establishment of a moon village. One challenge for effective exploration missions is developing a compact and lightweight robotic rover to reduce launch costs and open the possibility for secondary payload options. Existing micro rovers for exploration missions are clearly limited by their design for one day of sunlight and their low level of autonomy. For expanding the potential mission applications and range of use, an extension of lifetime could be reached by surviving the lunar night and providing a higher level of autonomy. To address this objective, the paper presents a system design concept for a lightweight micro rover with long-term mission duration capabilities, derived from a multi-day lunar mission scenario at equatorial regions. Technical solution approaches are described, analyzed, and evaluated, with emphasis put on the harmonization of hardware selection due to a strictly limited budget in dimensions and power.
In Europe, efforts are underway to develop key technologies that can be used to explore the Moon and to exploit the resources available. This includes technologies for in-situ resource utilization (ISRU), facilitating the possibility of a future Moon Village. The Moon is the next step for humans and robots to exploit the use of available resources for longer term missions, but also for further exploration of the solar system. A challenge for effective exploration missions is to achieve a compact and lightweight robot to reduce launch costs and open up the possibility of secondary payload options. Current micro rover concepts are primarily designed to last for one day of solar illumination and show a low level of autonomy. Extending the lifetime of the system by enabling survival of the lunar night and implementing a high level of autonomy will significantly increase potential mission applications and the operational range. As a reference mission, the deployment of a micro rover in the equatorial region of the Moon is being considered. An overview of mission parameters and a detailed example mission sequence is given in this paper. The mission parameters are based on an in-depth study of current space agency roadmaps, scientific goals, and upcoming flight opportunities. Furthermore, concepts of the ongoing international micro rover developments are analyzed along with technology solutions identified for survival of lunar nights and a high system autonomy. The results provide a basis of a concise requirements set-up to allow dedicated system developments and qualification measures in the future.
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.
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.
Subglacial environments on Earth offer important analogs to Ocean World targets in our solar system. These unique microbial ecosystems remain understudied due to the challenges of access through thick glacial ice (tens to hundreds of meters). Additionally, sub-ice collections must be conducted in a clean manner to ensure sample integrity for downstream microbiological and geochemical analyses. We describe the field-based cleaning of a melt probe that was used to collect brine samples from within a glacier conduit at Blood Falls, Antarctica, for geomicrobiological studies. We used a thermoelectric melting probe called the IceMole that was designed to be minimally invasive in that the logistical requirements in support of drilling operations were small and the probe could be cleaned, even in a remote field setting, so as to minimize potential contamination. In our study, the exterior bioburden on the IceMole was reduced to levels measured in most clean rooms, and below that of the ice surrounding our sampling target. Potential microbial contaminants were identified during the cleaning process; however, very few were detected in the final englacial sample collected with the IceMole and were present in extremely low abundances (∼0.063% of 16S rRNA gene amplicon sequences). This cleaning protocol can help minimize contamination when working in remote field locations, support microbiological sampling of terrestrial subglacial environments using melting probes, and help inform planetary protection challenges for Ocean World analog mission concepts.