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Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of WDS, i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the
resilience of WDS
The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example
system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient
system behaviour.
The transition within transportation towards battery electric vehicles can lead to a more sustainable future. To account for the development goal ‘climate action’ stated by the United Nations, it is mandatory, within the conceptual design phase, to derive energy-efficient system designs. One barrier is the uncertainty of the driving behaviour within the usage phase. This uncertainty is often addressed by using a stochastic synthesis process to derive representative driving cycles and by using cycle-based optimization. To deal with this uncertainty, a new approach based on a stochastic optimization program is presented. This leads to an optimization model that is solved with an exact solver. It is compared to a system design approach based on driving cycles and a genetic algorithm solver. Both approaches are applied to find efficient electric powertrains with fixed-speed and multi-speed transmissions. Hence, the similarities, differences and respective advantages of each optimization procedure are discussed.
The course Physics for Electrical Engineering is part of the curriculum of the
bachelor program Electrical Engineering at University of Applied Science Aachen.
Before covid-19 the course was conducted in a rather traditional way with all parts
(lecture, exercise and lab) face-to-face. This teaching approach changed
fundamentally within a week when the covid-19 limitations forced all courses to
distance learning. All parts of the course were transformed to pure distance learning
including synchronous and asynchronous parts for the lecture, live online-sessions
for the exercises and self-paced labs at home. Using these methods, the course was
able to impart the required knowledge and competencies. Taking the teacher’s
observations of the student’s learning behaviour and engagement, the formal and
informal feedback of the students and the results of the exams into account, the new
methods are evaluated with respect to effectiveness, sustainability and suitability for
competence transfer. Based on this analysis strong and weak points of the concept
and countermeasures to solve the weak points were identified. The analysis further
leads to a sustainable teaching approach combining synchronous and asynchronous
parts with self-paced learning times that can be used in a very flexible manner for
different learning scenarios, pure online, hybrid (mixture of online and presence
times) and pure presence teaching.
Adapting Augmented Reality Systems to the users’ needs using Gamification and error solving methods
(2021)
Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
Inhaltsverzeichnis
1. Die ordentliche Kündigung chronisch Kranker im Anwendungsbereich des
KSchG
– Nora Trümpener 3-56
2. Die Legitimationswirkung der Gesellschafterliste -
Erfolg trotz Grenzen?
– Jan Peters 57-112
3. Marktmanipulation – Arten, Abgrenzung und gesetzliche Handhabe
– Manuel Herzel 113-170
4. Die Zulässigkeit der Verdachtskündigung im Arbeitsverhältnis
– Alina Vollmann 171-248
5. Praxisorientierter Arbeitgeberleitfaden zur rechtssicheren Einführung von
Homeoffice im Arbeitsverhältnis
– Gina Breuer 249-304
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
The recently discovered first hyperbolic objects passing through the Solar System, 1I/’Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects. In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system. In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology. We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition. Their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy. These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
Geochemical characterisation of hypersaline waters is difficult as high concentrations of salts hinder the analysis of constituents at low concentrations, such as trace metals, and the collection of samples for trace metal analysis in natural waters can be easily contaminated. This is particularly the case if samples are collected by non-conventional techniques such as those required for aquatic subglacial environments. In this paper we present the first analysis of a subglacial brine from Taylor Valley, (~ 78°S), Antarctica for the trace metals: Ba, Co, Mo, Rb, Sr, V, and U. Samples were collected englacially using an electrothermal melting probe called the IceMole. This probe uses differential heating of a copper head as well as the probe’s sidewalls and an ice screw at the melting head to move through glacier ice. Detailed blanks, meltwater, and subglacial brine samples were collected to evaluate the impact of the IceMole and the borehole pump, the melting and collection process, filtration, and storage on the geochemistry of the samples collected by this device. Comparisons between melt water profiles through the glacier ice and blank analysis, with published studies on ice geochemistry, suggest the potential for minor contributions of some species Rb, As, Co, Mn, Ni, NH4+, and NO2−+NO3− from the IceMole. The ability to conduct detailed chemical analyses of subglacial fluids collected with melting probes is critical for the future exploration of the hundreds of deep subglacial lakes in Antarctica.
To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.
Inhaltsverzeichnis
1. Die Haftung des GmbH-Geschäftsführers in der Insolvenz - Grundsätze
und Modifikationen infolge der Covid-19 Pandemie
– Franziska Tings 3-61
2. Disquotale Gewinnausschüttung in der Organschaft – Die Neuregelung des
§ 14 Abs. 2 KStG und die Auslegung durch die Finanzverwaltung
– Julian Lehner 62-149
3. Auswirkungen des Mauracher Entwurfs auf die Gesellschaft bürgerlichen
Rechts – Neuerfindung oder bloße Korrektur des
Personengesellschaftsrechts?
– Elena Hoß 150-209
4. Befristung von Arbeitsverhältnissen - Rechtliche Rahmenbedingungen und
arbeitsmarktpolitische Chancen und Risiken
– Franziska Gotzens 210-270
5. Die Rolle der psychischen Gesundheit am Arbeitsplatz Entwicklung
exemplarischer Handlungsempfehlungen für den ganzheitlichen Umgang
mit psychischen Belastungen im Homeoffice
– Marie-Sophie Creutz 271-346
6. Tokenisierung von illiquiden Vermögenswerten – Wie Blockchain die
Immobilienwirtschaft verändern kann
– Nils Christ 347-404
Concentrating Solar Power
(2021)
The focus of this chapter is the production of power and the use of the heat produced from concentrated solar thermal power (CSP) systems.
The chapter starts with the general theoretical principles of concentrating systems including the description of the concentration ratio, the energy and mass balance. The power conversion systems is the main part where solar-only operation and the increase in operational hours.
Solar-only operation include the use of steam turbines, gas turbines, organic Rankine cycles and solar dishes. The operational hours can be increased with hybridization and with storage.
Another important topic is the cogeneration where solar cooling, desalination and of heat usage is described.
Many examples of commercial CSP power plants as well as research facilities from the past as well as current installed and in operation are described in detail.
The chapter closes with economic and environmental aspects and with the future potential of the development of CSP around the world.
Test-retest reliability of the internal shoulder rotator muscles' stretch reflex in healthy men
(2021)
Until now the reproducibility of the short latency stretch reflex of the internal rotator muscles of the glenohumeral joint has not been identified. Twenty-three healthy male participants performed three sets of external shoulder rotation stretches with various pre-activation levels on two different dates of measurement to assess test-retest reliability. All stretches were applied with a dynamometer acceleration of 104°/s2 and a velocity of 150°/s. Electromyographical response was measured via surface EMG. Reflex latencies showed a pre-activation effect (ƞ2 = 0,355). ICC ranged from 0,735 to 0,909 indicating an overall “good” relative reliability. SRD 95% lay between ±7,0 to ±12,3 ms.. The reflex gain showed overall poor test-retest reproducibility. The chosen methodological approach presented a suitable test protocol for shoulder muscles stretch reflex latency evaluation. A proof-of-concept study to validate the presented methodical approach in shoulder involvement including subjects with clinically relevant conditions is recommended.
One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.
Microbial diversity studies regarding the aquatic communities that experienced or are experiencing environmental problems are essential for the comprehension of the remediation dynamics. In this pilot study, we present data on the phylogenetic and ecological structure of microorganisms from epipelagic water samples collected in the Small Aral Sea (SAS). The raw data were generated by massive parallel sequencing using the shotgun approach. As expected, most of the identified DNA sequences belonged to Terrabacteria and Actinobacteria (40% and 37% of the total reads, respectively). The occurrence of Deinococcus-Thermus, Armatimonadetes, Chloroflexi in the epipelagic SAS waters was less anticipated. Surprising was also the detection of sequences, which are characteristic for strict anaerobes—Ignavibacteria, hydrogen-oxidizing bacteria, and archaeal methanogenic species. We suppose that the observed very broad range of phylogenetic and ecological features displayed by the SAS reads demonstrates a more intensive mixing of water masses originating from diverse ecological niches of the Aral-Syr Darya River basin than presumed before.
Conventional EEG devices cannot be used in everyday life and
hence, past decade research has been focused on Ear-EEG for mobile,
at-home monitoring for various applications ranging from
emotion detection to sleep monitoring. As the area available for
electrode contact in the ear is limited, the electrode size and location
play a vital role for an Ear-EEG system. In this investigation, we
present a quantitative study of ear-electrodes with two electrode
sizes at different locations in a wet and dry configuration. Electrode
impedance scales inversely with size and ranges from 450 kΩ to
1.29 MΩ for dry and from 22 kΩ to 42 kΩ for wet contact at 10 Hz.
For any size, the location in the ear canal with the lowest impedance
is ELE (Left Ear Superior), presumably due to increased contact
pressure caused by the outer-ear anatomy. The results can be used
to optimize signal pickup and SNR for specific applications. We
demonstrate this by recording sleep spindles during sleep onset
with high quality (5.27 μVrms).
Multi-attribute relation extraction (MARE): simplifying the application of relation extraction
(2021)
Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.
We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts.
Determinants of earnings forecast error, earnings forecast revision and earnings forecast accuracy
(2012)
Earnings forecasts are ubiquitous in today’s financial markets. They are essential indicators of future firm performance and a starting point for firm valuation. Extremely inaccurate and overoptimistic forecasts during the most recent financial crisis have raised serious doubts regarding the reliability of such forecasts. This thesis therefore investigates new determinants of forecast errors and accuracy. In addition, new determinants of forecast revisions are examined. More specifically, the thesis answers the following questions: 1) How do analyst incentives lead to forecast errors? 2) How do changes in analyst incentives lead to forecast revisions?, and 3) What factors drive differences in forecast accuracy?
Communication via serial bus systems, like CAN, plays an important role for all kinds of embedded electronic and mechatronic systems. To cope up with the requirements for functional safety of safety-critical applications, there is a need to enhance the safety features of the communication systems. One measure to achieve a more robust communication is to add redundant data transmission path to the applications. In general, the communication of real-time embedded systems like automotive applications is tethered, and the redundant data transmission lines are also tethered, increasing the size of the wiring harness and the weight of the system. A radio link is preferred as a redundant transmission line as it uses a complementary transmission medium compared to the wired solution and in addition reduces wiring harness size and weight. Standard wireless links like Wi-Fi or Bluetooth cannot meet the requirements for real-time capability with regard to bus communication. Using the new dual-mode radio enables a redundant transmission line meeting all requirements with regard to real-time capability, robustness and transparency for the data bus. In addition, it provides a complementary transmission medium with regard to commonly used tethered links. A CAN bus system is used to demonstrate the redundant data transfer via tethered and wireless CAN.
Kleidung ist ein Kommunikationsmedium. Im Projekt wird Bekleidung als Informationsträger genutzt, um über die verschiedenen Abschnitte im Zyklus eines Kleidungsstücks sowie die Missstände in der Bekleidungsindustrie zu informieren. Entstanden sind 6 Kleidungsstücke, jeweils eins pro Abschnitt im Zyklus, vom Baumwollanbau über Spinnereien, Produktionsfabriken, dem Einzelhandel und Gebrauch bis zur Entsorgung.
Die einfach gehaltenen Kleidungsstücke besitzen Aufdrucke. Über eine Augmented-Reality-App können die Kleidungsstücke gescannt werden. In Kombination mit der digitalen Ebene werden die Aufdrucke zu Informationsgrafiken. So wird unter anderem über die grausamen Arbeitsumstände in der Produktion informiert oder darüber, dass wir unsere Kleidungsstücke durchschnittlich nur 4x anziehen. Immer geht es darum, den Betrachter dazu anzuregen, seine Konsumentscheidungen zu überdenken.
Temporärer, mobiler Lebensraum: ein Wohnkonzept für Tinyhouses aus alten, ungenutzten Bahnwaggons
(2021)
Das Olympiagelände in München wurde im Jahre 1972 durch die Münchener S-Bahn erreichbar. Nach der Nutzung während der Olympischen Spiele wurde die Strecke weiterhin von der Linie S3angefahren, aber schließlich 1988 stillgelegt und steht seither unter Denkmalschutz. Das umfassende Gelände ist bis heute gut ausgebaut und bietet viel Raum für Freizeitaktivitäten. Nun bietet sich dieser Standort für ein neues Wohnkonzept an. Aus alten, nicht mehr nutzbaren Bahnwaggons entstehen Tinyhouse-Module. Aus dem alten Olympiabahnhof der S3 wird ein neues Viertel für junge Leute, Studenten und alle anderen, die sich vorstellen können in einem Tinyhouse zu wohnen.
Monitoring-System für die Luftrettung: ergonomisches Designkonzept für den medizinischen Anwender
(2021)
Bei einem Luftrettungseinsatz hat die Herstellung der Transportfähigkeit des Patienten Priorität. Im Anschluss erfolgt das Monitoring während des Fluges.
Das Problem dabei ist: Es gibt keine einheitliche Basis zur ergonomischen Nutzung und Datenverwertung der medizinischen Geräte. Kabel, Positionierung und individuelle Displays beeinträchtigen die Anwendenden. Dies kann im schlimmsten Fall die erfolgreiche Patientenbehandlung gefährden und die Übergabe des Patienten verzögern.
Im Konzept wurden die Geräte drahtlos gestaltet. Mittels Knopfdruck am Gerät werden Daten an den Monitor übertragen. Schnell und sicher können EKG, Blutdruck, SPO2 und Temperatur gemessen und Stethoskop, Ultraschall und Videolaryngoskop verwendet werden. Ein Barcode-Scanner dokumentiert Medikamente und verbrauchte Materialien. Im Anschluss wird ein Zielkrankenhaus ausgewählt, die Ankunftszeit angezeigt und Daten protokolliert und übertragen.
Das Projekt bezieht sich auf das globale Konsumverhalten gegenüber Spielwaren unter den Bedingungen des Gender-Marketings im Hinblick auf die nachteiligen Bedingungen für die Entwicklung des Kindes und der Umwelt.
Gestaltet wurde ein Baukastensystem, das sich keiner geschlechtsspezifischen Zuweisung bedient, und so verhindert, dass Kinder, die sich im binären Rollenbild nicht wiederfinden, ausgegrenzt werden. Das Stecksystem ohne Vorgabe einer Anleitung ermöglicht freie Entfaltung beim Spiel und die Förderung der spielerischen und didaktischen Entwicklung eines Kindes.
Spielen ist eine Art des Kindes sich und seine Umwelt zu begreifen und sich dazu auszudrücken. Es werden nicht nur Fähigkeiten erprobt, sondern auch Verhaltensweisen angeeignet und Identitätsmerkmale definiert. Dadurch erhält das Spielzeug eine Vorbildfunktion. Dieser Vorbildfunktion soll das entworfene Produkt gerecht werden.
Biological Cocoon: Gestaltung des künstlichen Frühgeborenenuterus unter Aspekt der User Experience
(2021)
Vor der 37. Schwangerschaftswoche geborene Babys gelten als Frühgeborene, was Stand 2010 weltweit auf jedes zehnte Neugeborene zutrifft. Komplikationen führten 2015 zu einer Million Todesfälle. Die Überlebenden leiden trotz medizinischer Versorgung an den direkten oder späten Folgen. Weltweit wird an einem künstlichen Uterus geforscht. Biological Cocoon ist - basierend auf neuestem Forschungsstand und bei Betreuung im Perinatalzentrum - für Frühgeborene ab der 22. bis 35. Schwangerschaftswoche konzipiert.
Durch Nachahmung natürlicher Gegebenheiten wird die Entwicklung deutlich verbessert, wie zum Beispiel durch das Abspielen der Geräusche im Mutterleib. Die Eltern werden mit einbezogen und fördern die Weiterentwicklung besonders durch Interaktion mit ihrem Frühgeborenen vor Ort und auf Distanz per App.
Biological Cocoon macht die Behandlung angenehm. Spätfolgen beim Neugeborenen werden vermieden.
Die Fast-Fashion-Industrie produziert am laufenden Band neue Kleidung und so schnell wie sie gekauft wird, wird sie auch wieder entsorgt. Das Altkleidersystem ist allerdings an seiner Kapazitätsgrenze angekommen und die sich zuspitzende Lage verlangt nach einer neuen innovativen Lösung. „VABRIC“ ersetzt die herkömmlichen Altkleidercontainer in den Städten und verlängert den Lebenszyklus von Textilien. Durch eine gezielte Vorsortierung entsteht die Möglichkeit Kleidung weiterzuverteilen und in bestehende oder ganz neue Nutzungskreisläufe zu integrieren. Für die Nutzenden wird die Textilspende durch das hochwertige Erscheinungsbild, die zentralen Standorte und die Aufklärung zu einer positiven Erfahrung. „VABRIC“ verkörpert, am Beispiel von Textilien, die Vision, wie wir in Zukunft mit vermeintlichem Abfall umgehen und den wahren Wert von Ressourcen hervorheben und nutzbar machen.
„Printen“ ist ein Multifunktionsdrucksystem, welches dem Nutzer ermöglicht, es zu reparieren.
Das Elektroschrottaufkommen der Welt steigt, deshalb legte die EU neue Maßnahmen zum Ökodesign fest. Diese sollen die Reparierbarkeit von Produkten fördern und geplante Obsoleszenz unterbinden. Ein Vorzeigebeispiel für geplanten Obsoleszenz ist der Drucker.
Das System besteht aus einem Drucker und Scanner, an dem der Nutzer Reparaturen vornehmen kann. Dadurch soll eine stärkere Bindung zum selbst reparierten Gerät entstehen und die Lebensdauer verlängert werden. Durch ein öffnungsfähiges Gehäuse wird die Reparatur ermöglicht. Eine Farbcodierung im Inneren erleichtert die Orientierung und visualisiert zusammengehörende Elemente. Außerdem wurde der Aufbau des Druckers aufgeräumt und vereinfacht. So können einzelne Komponenten problemlos ausgetauscht werden. Ganz nach der Devise: Einfach printen!
Das Ziel des Bibliothekskonzeptes ist es, Hybridbibliotheken als Symbiose aus zukunftsweisender Medientechnologie und klassischer Funktionalität in Modulbauweise in Bestandsarchitektur zu integrieren. Der Lösungsansatz liegt in einer kostengünstigen dynamischen Modularität, welche als Plug-In, Add-On, Single oder Mobilkonzept nutzbar ist. Das modulare System setzt hierbei auf Grundmodule, welche für unterschiedlichste räumliche Gegebenheiten skaliert werden können. Somit können Einrichtungen neue Funktionalitäten integrieren oder auf temporäre Anforderungen strategisch reagieren. Durch die einfache Montage und Transportfähigkeit lassen sich sehr schnell zeitbegrenzte oder dauerhafte Raumkonzepte umsetzen. Das System nimmt die Dynamik des sich verändernden Bedarfs auf und passt sich flexibel den Zielgruppen an, was im Gegensatz dazu bei statischen Systemen nicht der Fall ist.
Ein naturbelassenes System oder systematisch Natur? In der Bachelorarbeit COFFEE TO STAY entstand das modulare Seating-System REGROW. Sitzlandschaften für kurze Pausen, zwischen Kommen und Gehen, zwischen Begegnungen und Verabschiedungen – REGROW steht für die Entschleunigung im Alltag. Mit Material und Oberflächen, die von der Natur inspiriert sind, bietet REGROW Zufluchtsorte in urbanen Städten, geprägt von Beton und Asphalt. Ein Stück Natur, das sich dem räumlichen Kontext anpassen kann: Dank seiner flexiblen Modularität kann REGROW auf kleine und auf große Räume reagieren. Die Kollektion besteht aus Sitzelementen, die sich durch Rückenlehnen und Armlehnen ergänzen lassen. Mit den Beistelltischen lassen sich Sitzmodule miteinander im 45 oder 90 Grad Winkel verbinden.
Der Wunsch nach Gesundheit und Individualisierung der eigenen Freizeit als Ausgleich zum Alltag ist heute in der Gesellschaft so ausgeprägt wie noch nie. Dabei sind die positiven Auswirkungen körperlicher Aktivität auf das Immunsystem, die Lebenserwartung und die Leistungsfähigkeit immer bekannter. Diese Abschlussarbeit greift die erkannte Entwicklung und den wachsenden Wunsch der Nutzenden nach individuellem Fitnesstraining im Freien auf. Das entstandene Outdoor-Trainingssystem „TREICK“ ermöglicht ein mobiles, orts- und zeitunabhängiges Training der eigenen Fitness. Durch „TREICK“ kann der Sportler physiologisch sinnvolle Eigengewichtsübungen in einer selbst gewählten Umgebung ausführen, wodurch das Wohlbefinden und damit die Gesundheit gefördert werden kann. Das System kann als Rucksack oder Fahrradtasche transportiert werden, wobei die Trainingsmatte als Verpackung dient.
Living Books ist ein in Aachen stationiertes Event der Buchhandlungskette Mayersche, welches Kinder und Jugendliche zum Lesen animieren soll, indem Technik und Unterhaltungsmedien mit dem Buch verbunden werden. Hierzu werden die Möglichkeiten der virtuellen Realität genutzt sowie einzigartige Marketingstrategien, die sich ebenfalls neuartiger Technik bedienen, um das Interesse und die Neugierde junger Menschen zu wecken. Vor Ort wird man zum ersten Mal mit dem Buch konfrontiert. Bis dahin wirkt das Event schlichtweg wie ein Fantreffen zu Buchverfilmungen. Nacheinander betreten die jungen Besucher mithilfe einer VR-Brille eine Welt, die einem Buch entstammt, um ihnen die Geschichte spielerisch näherzubringen. Mithilfe der neuen Welt und einem plötzlichen Ende soll Neugierde für das Buch geweckt werden. Das Interesse für die Geschichte soll am Ende größer sein als die Abneigung gegen das Lesen.
Da die Gesellschaft in Deutschland immer älter wird, steigt auch die Nachfrage nach Gehhilfen wie beispielsweise einem Rollator. Im Alter steigt das Erkrankungsrisiko für Krankheiten, die die Mobilität erschweren können. An diesem Punkt setzt der Rollator MORO an und bietet wieder Sicherheit beim Gehen.
Für den MORO sind Hindernisse wie Bordsteinkanten kein Problem, da er sie mit speziellen Rädern spielend überwinden kann. Zusätzlich bietet er ergonomische Handgriffe, die entsprechend der jeweiligen Krankheit angepasst und ausgetauscht werden können sowie einen Sitz und eine Rückenlehne. Da der MORO aus Carbon hergestellt wird, ist er leicht in der Handhabung und somit wird die Mitnahme im Auto oder Bus und Bahn erleichtert. Durch seine verbesserte Ergonomie, individueller Anpassung und Leichtigkeit kann man wieder selbstständig durch die Welt gehen.