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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.
Germany is a frontrunner in setting frameworks for the transition to a low-carbon system. The mobility sector plays a significant role in this shift, affecting different people and groups on multiple levels. Without acceptance from these stakeholders, emission targets are out of reach. This research analyzes how the heterogeneous preferences of various stakeholders align with the transformation of the mobility sector, looking at the extent to which the German transformation paths are supported and where stakeholders are located.
Under the research objective of comparing stakeholders' preferences to identify which car segments require additional support for a successful climate transition, a status quo of stakeholders and car performance criteria is the foundation for the analysis. Stakeholders' hidden preferences hinder the derivation of criteria weightings from stakeholders; therefore, a ranking from observed preferences is used. This study's inverse multi-criteria decision analysis means that weightings can be predicted and used together with a recalibrated performance matrix to explore future preferences toward car segments.
Results show that stakeholders prefer medium-sized cars, with the trend pointing towards the increased potential for alternative propulsion technologies and electrified vehicles. These insights can guide the improved targeting of policy supporting the energy and mobility transformation. Additionally, the method proposed in this work can fully handle subjective approaches while incorporating a priori information. A software implementation of the proposed method completes this work and is made publicly available.
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.
Optical Fibers as Dosimeter Detectors for Mixed Proton/Neutron Fields - A Biological Dosimeter
(2023)
In recent years, proton therapy has gained importance as a cancer treatment modality due to its conformality with the tumor and the sparing of healthy tissue. However, in the interaction of the protons with the beam line elements and patient tissues, potentially harmful secondary neutrons are always generated. To ensure that this neutron dose is as low as possible, treatment plans could be created to also account for and minimize the neutron dose. To monitor such a treatment plan, a compact, easy to use, and inexpensive dosimeter must be developed that not only measures the physical dose, but which can also distinguish between proton and neutron contributions. To that end, plastic optical fibers with scintillation materials (Gd₂O₂S:Tb, Gd₂O₂S:Eu, and YVO₄:Eu) were irradiated with protons and neutrons. It was confirmed that sensors with different scintillation materials have different sensitivities to protons and neutrons. A combination of these three scintillators can be used to build a detector array to create a biological dosimeter.
High aerodynamic efficiency requires propellers with high aspect ratios, while propeller sweep potentially reduces noise. Propeller sweep and high aspect ratios increase elasticity and coupling of structural mechanics and aerodynamics, affecting the propeller performance and noise. Therefore, this paper analyzes the influence of elasticity on forward-swept, backward-swept, and unswept propellers in hover conditions. A reduced-order blade element momentum approach is coupled with a one-dimensional Timoshenko beam theory and Farassat's formulation 1A. The results of the aeroelastic simulation are used as input for the aeroacoustic calculation. The analysis shows that elasticity influences noise radiation because thickness and loading noise respond differently to deformations. In the case of the backward-swept propeller, the location of the maximum sound pressure level shifts forward by 0.5 °, while in the case of the forward-swept propeller, it shifts backward by 0.5 °. Therefore, aeroacoustic optimization requires the consideration of propeller deformation.
Today’s society is undergoing a paradigm shift driven by the megatrend of sustainability. This undeniably affects all areas of Western life. This paper aims to find out how the luxury industry is dealing with this change and what adjustments are made by the companies. For this purpose, interviews were conducted with managers from the luxury industry, in which they were asked about specific measures taken by their companies as well as trends in the industry. In a subsequent evaluation, the trends in the luxury industry were summarized for the areas of ecological, social, and economic sustainability. It was found that the area of environmental sustainability is significantly more focused than the other sub-areas. Furthermore, the need for a customer survey to validate the industry-based measures was identified.
Using scenarios is vital in identifying and specifying measures for successfully transforming the energy system. Such transformations can be particularly challenging and require the support of a broader set of stakeholders. Otherwise, there will be opposition in the form of reluctance to adopt the necessary technologies. Usually, processes for considering stakeholders' perspectives are very time-consuming and costly. In particular, there are uncertainties about how to deal with modifications in the scenarios. In principle, new consulting processes will be required. In our study, we show how multi-criteria decision analysis can be used to analyze stakeholders' attitudes toward transition paths. Since stakeholders differ regarding their preferences and time horizons, we employ a multi-criteria decision analysis approach to identify which stakeholders will support or oppose a transition path. We provide a flexible template for analyzing stakeholder preferences toward transition paths. This flexibility comes from the fact that our multi-criteria decision aid-based approach does not involve intensive empirical work with stakeholders. Instead, it involves subjecting assumptions to robustness analysis, which can help identify options to influence stakeholders' attitudes toward transitions.
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
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.
The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.