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In this thesis, a model of the dynamics during the landing phase of an interplanetary lander mission is developed in a 3 DOF approach with the focus lying on landing by propulsive means. Based on this model, a MATLAB simulation was developed with the goal of enabling an estimation of the performance and especially the required fuel amount of a propulsive landing system on Venus. This landing system is modeled to be able to control its descent using thrusters and to perform a stable landing at a specified target location. Using this simulation, the planetary environments of Mars and Venus can be simulated and the impact of wind, atmospheric density and gravity as well as of using different thrusters on the fuel consumption and landing abilities of the simulated landing system can be investigated. The comparability of these results with the behavior of real landing systems is validated in this thesis by simulating the Powered Descent Phase of the Mars 2020 mission and comparing the results to the data the Mars 2020 descent stage has collected during this phase of its landing. Further, based on the simulation, the minimal necessary fuel amount for a successful landing on Venus has been determined for different scenarios. The simulation along with these results are a contribution to the research of this thesis’s supervisor Clemens Riegler, M.Sc., who will use them for a comparison of different types of landing systems in the context of his doctoral thesis.
The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town or complex institutions like airports) with simulatively added previously named components. We, therefore, propose a novel digital twin of such an energy system based solely on a complete set of smart meter data including additional building data. Based on the additional geospatial data, the twin is intended to represent the addition of the abovementioned components as realistically as possible. Outputs of the twin can be used as a decision support for either system operators where to strengthen the system or for individual households where and how to install photovoltaic systems and batteries. Meanwhile, the first local energy system operators had such smart meter data of almost all residential consumers for several years. We acquire those of an exemplary operator and discuss a case study presenting some features of our digital twin and highlighting the value of the combination of smart meter and geospatial data.
Providing adaptive, independence-preserving and theory-guided support to students in dealing with real-world problems in mathematics lessons is a major challenge for teachers in their professional practice. This paper examines this challenge in the context of simulations and mathematical modelling with digital tools: in addition to mathematical difficulties when autonomously working out individual solutions, students may also experience challenges when using digital tools. These challenges need to be closely examined and diagnosed, and might – if necessary – have to be overcome by intervention in such a way that the students can subsequently continue working independently. Thus, if a difficulty arises in the working process, two knowledge dimensions are necessary in order to provide adapted support to students. For teaching simulations and mathematical modelling with digital tools, more specifically, these knowledge dimensions are: pedagogical content knowledge about simulation and modelling processes supported by digital tools (this includes knowledge about phases and difficulties in the working process) and pedagogical content knowledge about interventions during the mentioned processes (focussing on characteristics of suitable interventions as well as their implementation and effects on the students’ working process). The two knowledge dimensions represent cognitive dispositions as the basis for the conceptualisation and operationalisation of a so-called adaptive intervention competence for teaching simulations and mathematical modelling with digital tools. In our article, we present a domain-specific process model and distinguish different types of teacher interventions. Then we describe the design and content of a university course at two German universities aiming to promote this domain-specific professional adaptive intervention competence, among others. In a study using a quasi-experimental pre-post design (N = 146), we confirm that the structure of cognitive dispositions of adaptive intervention competence for teaching simulations and mathematical modelling with digital tools can be described empirically by a two-dimensional model. In addition, the effectiveness of the course is examined and confirmed quantitatively. Finally, the results are discussed, especially against the background of the sample and the research design, and conclusions are derived for possibilities of promoting professional adaptive intervention competence in university courses.
This work aims at elucidating chemical processes involving homogeneous catalysis and photo–physical relaxation of excited molecules in the solid state. Furthermore, compounds with supposedly small singlet–triplet gaps and therefore biradicaloid character are investigated with respect to their electro–chemical behavior. The work on hydroboration catalysis via a reduced 9,10–diboraanthracene (DBA) was preformed in collaboration with the Wagner group in Frankfurt, more specifically Dr. Sven Prey, who performed all laboratory experiments. The investigation of delayed luminescence properties in arylboronic esters in their solid state was conducted in collaboration with the Marder group in Würzburg. The author of this work took part in the synthesis of the investigated compounds while being supervised by Dr. Zhu Wu. The final project was a collaboration with the group of Anukul Jana from Hyderabad, India who provided the experimental data.
Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.
Background
Electrosurgical excisions are common procedures for treating cervical dysplasia and are often seen as minor surgeries. Yet, thorough training of this intervention is required, as there are considerable consequences of inadequate resections, e.g. preterm birth, the risk of recurrence, injuries and many more. Unfortunately, there is a lack of sufficiently validated possibilities of simulating electrosurgeries, which focus on high fidelity and patient safety.
Methods
A novel 3D printed simulator for examination and electrosurgical treatment of dysplastic areas of the cervix was compared with a conventional simulator. Sixty medical students experienced a seminar about cervical dysplasia. Group A underwent the seminar with the conventional and Group B with the novel simulator. After a theoretical introduction, the students were randomly assigned by picking a ticket from a box and went on to perform the hands-on training with their respective simulator. Each student first obtained colposcopic examination training. Then he or she performed five electrosurgical excisions (each). This was assessed with a validated score, to visualize their learning curve. Furthermore, adequate and inadequate resections and contacts between electrosurgical loop and vagina or speculum were counted. Both groups also assessed the seminar and their simulator with 18 questions (Likert-scales, 1–10, 1 = strongly agree / very good, 10 = strongly disagree / very bad). Group B additionally assessed the novel simulator with four questions (similar Likert-scales, 1–10).
Results
Nine of 18 questions showed statistically significant differences favoring Group B (p < 0.05). Group B also achieved more adequate R0-resections and less contacts between electrosurgical loop and vagina or speculum. The learning curves of the performed resections favored the novel simulator of Group B without statistically significant differences. The four questions focusing on certain aspects of the novel simulator indicate high appreciation of the students with a mean score of 1.6 points.
Conclusion
The presented novel simulator shows several advantages compared to the existing model. Thus, novice gynecologists can be supported with a higher quality of simulation to improve their training and thereby patient safety.
In this doctoral thesis we cover the performance evaluation of next generation data plane architectures, comprised of complex software as well as programmable hardware components that allow fine granular configuration. In the scope of the thesis we propose mechanisms to monitor the performance of singular components and model key performance indicators of software based packet processing solutions. We present novel approaches towards network abstraction that allow the integration of heterogeneous data plane technologies into a singular network while maintaining total transparency between control and data plane. Finally, we investigate a full, complex system consisting of multiple software-based solutions and perform a detailed performance analysis. We employ simulative approaches to investigate overload control mechanisms that allow efficient operation under adversary conditions. The contributions of this work build the foundation for future research in the areas of network softwarization and network function virtualization.
Virtual online training has emerged as one of the top 20 worldwide fitness trends for 2021 and continues to develop rapidly. Although this allows the cycling community to engage in virtual training and competition, critical evaluation of virtual training platforms is limited. Here, we discuss the strengths, weaknesses, opportunities and threats associated with virtual training technology and cycling in an attempt to enhance awareness of such aspects. Strengths include immersive worlds, innovative drafting mechanics, and versatility. Weaknesses include questionable data accuracy, inadequate strength and reliability of power-speed algorithms. Opportunities exist for expanding strategic partnerships with major cycling races, brands, and sponsors and improving user experience with the addition of video capture and “e-coaching.” Threats are present in the form of cheating during competition, and a lack of uptake and acceptance by a broader community.
Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.
After a large outbreak in Brazil, novel drugs against Zika virus became extremely necessary. Evaluation of virus-based pharmacological strategies concerning essential host factors brought us to the idea that targeting the Axl receptor by blocking its dimerization function could be critical for virus entry. Starting from experimentally validated compounds, such as RU-301, RU-302, warfarin, and R428, we identified a novel compound 2′ (R428 derivative) to be the most potent for this task amongst a number of alternative compounds and leads. The improved affinity of compound 2′ was confirmed by molecular docking as well as molecular dynamics simulation techniques using implicit solvation models. The current study summarizes a new possibility for inhibition of the Axl function as a potential target for future antiviral therapies.