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In this article, we describe the structure, the functioning, and the tests of parabolic trough solar thermal cooker (PSTC). This oven is designed to meet the needs of rural residents, including Urban, which requires stable cooking temperatures above 200 °C. The cooking by this cooker is based on the concentration of the sun's rays on a glass vacuum tube and heating of the oil circulate in a big tube, located inside the glass tube. Through two small tubes, associated with large tube, the heated oil, rise and heats the pot of cooking pot containing the food to be cooked (capacity of 5 kg). This cooker is designed in Germany and extensively tested in Morocco for use by the inhabitants who use wood from forests.
During a sunny day, having a maximum solar radiation around 720 W/m2 and temperature ambient around 26 °C, maximum temperatures recorded of the small tube, the large tube and the center of the pot are respectively: 370 °C, 270 °C and 260 °C. The cooking process with food at high (fries, ..), we show that the cooking oil temperature rises to 200 °C, after 1 h of heating, the cooking is done at a temperature of 120 °C for 20 min. These temperatures are practically stable following variations and decreases in the intensity of irradiance during the day. The comparison of these results with those of the literature shows an improvement of 30–50 % on the maximum value of the temperature with a heat storage that could reach 60 min of autonomy. All the results obtained show the good functioning of the PSTC and the feasibility of cooking food at high temperature (>200 °C).
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
Objective
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Method
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Result
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
Conclusion
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
The enantioselective synthesis of α-hydroxy ketones and vicinal diols is an intriguing field because of the broad applicability of these molecules. Although, butandiol dehydrogenases are known to play a key role in the production of 2,3-butandiol, their potential as biocatalysts is still not well studied. Here, we investigate the biocatalytic properties of the meso-butanediol dehydrogenase from Bacillus licheniformis DSM 13T (BlBDH). The encoding gene was cloned with an N-terminal StrepII-tag and recombinantly overexpressed in E. coli. BlBDH is highly active towards several non-physiological diketones and α-hydroxyketones with varying aliphatic chain lengths or even containing phenyl moieties. By adjusting the reaction parameters in biotransformations the formation of either the α-hydroxyketone intermediate or the diol can be controlled.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.
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.
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.
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 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.
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.
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.
There is a broad international discussion about rethinking engineering education in order to educate engineers to cope with future challenges, and particularly the sustainable development goals. In this context, there is a consensus about the need to shift from a mostly technical paradigm to a more holistic problem-based approach, which can address the social embeddedness of technology in society. Among the strategies suggested to address this social embeddedness, design thinking has been proposed as an essential complement to engineering precisely for this purpose. This chapter describes the requirements for integrating the design thinking approach in engineering education. We exemplify the requirements and challenges by presenting our approach based on our course experiences at RWTH Aachen University. The chapter first describes the development of our approach of integrating design thinking in engineering curricula, how we combine it with the Sustainable Development Goals (SDG) as well as the role of sustainability and social responsibility in engineering. Secondly, we present the course “Expanding Engineering Limits: Culture, Diversity, and Gender” at RWTH Aachen University. We describe the necessity to theoretically embed the method in social and cultural context, giving students the opportunity to reflect on cultural, national, or individual “engineering limits,” and to be able to overcome them using design thinking as a next step for collaborative project work. The paper will suggest that the successful implementation of design thinking as a method in engineering education needs to be framed and contextualized within Science and Technology Studies (STS).
Implementation of gender and diversity perspectives in transport development plans in germany
(2020)
As mobility should ensure the accessibility to and participation in society, transport planning has to deal with a variety of gender and diversity categories affecting users’ mobility needs and patterns. Exemplified by an analysis of an instrument of transport development processes – German Transport Development Plans (TDPs) – we investigated to what extent diverse target groups and their mobility requirements are implemented in transport strategy papers. Research results illustrate a still-prevalent neglect of several relevant gender and diversity categories while prioritizing and focusing on eco-friendly topics. But how sustainable can transport be without facing the diversification of life circumstances?
A research framework for human aspects in the internet of production: an intra-company perspective
(2020)
Digitalization in the production sector aims at transferring concepts and methods from the Internet of Things (IoT) to the industry and is, as a result, currently reshaping the production area. Besides technological progress, changes in work processes and organization are relevant for a successful implementation of the “Internet of Production” (IoP). Focusing on the labor organization and organizational procedures emphasizes to consider intra-company factors such as (user) acceptance, ethical issues, and ergonomics in the context of IoP approaches. In the scope of this paper, a research approach is presented that considers these aspects from an intra-company perspective by conducting studies on the shop floor, control level and management level of companies in the production area. Focused on four central dimensions—governance, organization, capabilities, and interfaces—this contribution presents a research framework that is focused on a systematic integration and consideration of human aspects in the realization of the IoP.
Insbesondere im wirtschaftlichen Kontext wird die Diversität von Belegschaften zunehmend als ein kritischer Erfolgsfaktor gesehen. Neben dem Potenzial, welches sich laut Studien aus einem vielfältigen Team ergibt, werden jedoch ebenfalls die aus menschlicher Diversität resultierenden Herausforderungen thematisiert und wissenschaftlich untersucht. Sowohl aus dem Potenzial als auch aus den Herausforderungen ergibt sich dabei die Notwendigkeit der Implementierung eines organisationsspezifischen Diversity Managements, welches die Gewinnung neuer Mitarbeiter*innen einerseits und das Management der vorhandenen Vielfalt andererseits gleichermaßen unterstützt. In der psychologischen, sozial- und wirtschaftswissenschaftlichen Literatur gibt es unterschiedliche Definitionen von Diversität, woraus sich verschiedene Perspektiven auf das Vorgehen bei der Gestaltung und Umsetzung eines Diversity Management Ansatzes ergeben. Insbesondere vor dem Hintergrund der Komplexität des Organisationsumfeldes und der steigenden Anforderungen an die organisationsinterne Agilität besteht die Notwendigkeit, Diversität in Organisationen stärker zu reflektieren und systemspezifische Ansätze zu entwickeln. Dies erfordert die Berücksichtigung organisationsspezifischer Strukturen und Prozesse sowie die Reflexion des Wandels der Organisationskultur durch die Umsetzung eines Diversity Management Ansatzes, der die gegebene Komplexität aufgreift und bewältigen kann. Darüber hinaus sind die psychologischen Auswirkungen solcher Veränderungen auf die Mitarbeiter*innen zu berücksichtigen, um Reaktanzen zu vermeiden und eine nachhaltige Umsetzung von Diversity Management zu ermöglichen. In Ermangelung entsprechender Ansätze im Rahmen öffentlich finanzierter, komplexer Forschungsorganisationen, ist das Ziel dieser Dissertation die Entwicklung und Erprobung eines Forschungsdesigns, welches die Ansätze des Diversity- und Change Managements mit der Organisationskultur verknüpft, indem es eine systemtheoretische Perspektive einnimmt. Dabei wird das Forschungsdesign auf eine komplexe wissenschaftliche Organisation angewendet. Als Basis dient die in Teil A durchgeführte Betrachtung des aktuellen Forschungsstandes aus einer interdisziplinären Perspektive und die damit einhergehende umfassende Einführung in das Forschungsfeld. Im Zuge dessen wird detailliert auf die begriffliche Definition von Diversität eingegangen, bevor dann die psychologischen Konzepte im Diversitätskontext den Übergang zu einer differenzierten Auseinandersetzung mit dem Konzept des Diversity Managements bilden. Auf dieser Grundlage werden das Forschungsdesign sowie die daraus resultierenden Forschungsphasen abgeleitet. Teil A stellt somit die theoretische Grundlage für die in Teil B präsentierten Fachaufsätze dar. Jeder Fachaufsatz beleuchtet dabei in chronologischer Reihenfolge die unterschiedlichen Forschungsphasen. Fachaufsatz I präsentiert den sechsstufigen Forschungsansatz und beleuchtet die besonderen Rahmenbedingungen des Forschungsobjektes aus einer theoretischen Perspektive. Im Anschluss werden die Ergebnisse der Organisationsanalyse, welche zugleich Phase I und II des Forschungskonzeptes darstellen, vorgestellt. Aufbauend auf diesen Forschungsergebnissen fokussiert Forschungsaufsatz II die Darlegung der Ergebnisse aus Forschungsphase III, der Befragung der Führungsebene. Die Befragung thematisierte dabei die Wahrnehmung von Diversity und Diversity Management auf Führungsebene, die Verknüpfung von Diversität mit Innovation sowie die Reflexion des eigenen Führungsstils. Als Ergebnis der Befragung konnten sechs Typen identifiziert werden, die das Führungsverständnis im Diversitätskontext widerspiegeln und somit den Ansatzpunkt für eine top-down gerichtete Diversity Management Strategie darstellen. Darauf aufbauend wird in Forschungsphase IV die Mitarbeiter*innenebene beforscht. Im Zentrum der quantitativen Befragung standen die vorherrschenden Einstellungen zum Themenkomplex Diversity und Diversity Management, die Wahrnehmung von Diversität sowie die Untersuchung des Einflusses der Führungsebene auf die Mitarbeiter*innenebene. Forschungsaufsatz III präsentiert erste Ergebnisse dieser Untersuchung. Die Analyse weist auf eine unterschiedliche Gewichtung der verschiedenen Diversitätskategorien hinsichtlich der Verknüpfung mit Innovationen und somit der Reflexion des Kontextes zwischen Diversität und Innovationen hin. Vergleichbar mit den identifizierten Typen auf der Führungsebene, deutet die Analyse auf die Existenz unterschiedlicher Reflexionsgrade auf Mitarbeiter*innenebene hin. Auf Basis dessen wird im Rahmen von Forschungsaufsatz IV eine nähere Untersuchung des Reflexionsgrades auf Mitarbeiter*innenebene präsentiert und der Diversity Management Ansatz mit Elementen des Change Managements kombiniert. Besondere Berücksichtigung findet als Schlussfolgerung einer theoretischen Analyse die Organisationskultur als zentrales Element bei der Entwicklung und Einführung eines Diversity Management Ansatzes in eine komplexe Forschungsorganisation in Deutschland. Die Analyse zeigt, dass die Wahrnehmung von Diversität heterogen aber zunächst losgelöst vom individuellen Hintergrund ist (im Rahmen dieser Analyse lag der Fokus auf den Diversitätskategorien Gender und Herkunft). Hinsichtlich der Wertschätzung von Diversität zeigt sich dabei ebenfalls ein heterogenes Bild. In der Gesamtbetrachtung stimmen lediglich 17% der Mitarbeiter*innen zu, dass Diversitätskategorien wie Gender, Herkunft oder auch Alter einen Mehrwert darstellen können. Zugleich bewertet diese Gruppe die dem Thema beigemessene Wichtigkeit im CoE als ausreichend. Zusammengefasst lassen sich folgende Erkenntnisse im Rahmen dieser Dissertation ableiten und dienen somit als Grundlage für die Entwicklung eines Diversity Management Ansatzes: (1) Die Entwicklung eines bedarfsorientierten Diversity Management Ansatzes erfordert einen systemtheoretischen Prozess, der sowohl organisationsinterne als auch externe Einflussfaktoren berücksichtigt. Der im Rahmen des Forschungsprojektes entwickelte sechsstufige Forschungsprozess hat sich dabei als geeignetes Instrument erwiesen. (2)Im Rahmen öffentlicher Forschungseinrichtungen lassen sich dabei drei zentrale Faktoren identifizieren: die individuelle Reflexionsebene, die Organisationskultur sowie extern beeinflusste Organisationsstrukturen, Prozesse und Systeme.(3)Vergleichbar mit privatwirtschaftlichen Unternehmen hat auch in wissenschaftlichen Organisationen die Führungsebene einen maßgeblichen Einfluss auf die Wahrnehmung von Diversität und somit einen Einfluss auf die Umsetzung einer Diversity Management Strategie. Daher ist auch im wissenschaftlichen Kontext, bedingt durch die rechtlichen Rahmenbedingungen des Hochschulsystems, ein top-down Ansatz für eine nachhaltige Implementierung erforderlich. (4) Diversity Management steht in einem engen Zusammenhang mit einem organisationalen Wandel, was die Reflexion von Veränderungsprozesse aus einer psychologischen Perspektive erfordert und eine Verknüpfung von Diversity und Change Management bedingt. Aufbauend auf den im Rahmen des entwickelten Forschungskonzeptes gewonnenen zentralen Erkenntnissen wird ein Ansatz entwickelt, der die Ableitung theoretischer Implikationen sowie Implikationen für das Management ermöglicht. Insbesondere vor dem Hintergrund der Reflexion der besonderen Rahmenbedingungen öffentlich finanzierter Forschungsorganisationen werden darüber hinaus politische Implikationen abgeleitet, die auf die Veränderung struktureller Dimensionen abzielen.
Purpose
The aim of this study was to compare several osteosynthesis techniques (intramedullary headless compression screws, T-plates, and Kirschner wires) for distal epiphyseal fractures of proximal phalanges in a human cadaveric model.
Methods
A total of 90 proximal phalanges from 30 specimens (index, ring, and middle fingers) were used for this study. After stripping off all soft tissue, a transverse distal epiphyseal fracture was simulated at the proximal phalanx. The 30 specimens were randomly assigned to 1 fixation technique (30 per technique), either a 3.0-mm intramedullary headless compression screw, locking plate fixation with a 2.0-mm T-plate, or 2 oblique 1.0-mm Kirschner wires. Displacement analysis (bending, distraction, and torsion) was performed using optical tracking of an applied random speckle pattern after osteosynthesis. Biomechanical testing was performed with increasing cyclic loading and with cyclic load to failure using a biaxial torsion-tension testing machine.
Results
Cannulated intramedullary compression screws showed significantly less displacement at the fracture site in torsional testing. Furthermore, screws were significantly more stable in bending testing. Kirschner wires were significantly less stable than plating or screw fixation in any cyclic load to failure test setup.
Conclusions
Intramedullary compression screws are a highly stable alternative in the treatment of transverse distal epiphyseal phalangeal fractures. Kirschner wires seem to be inferior regarding displacement properties and primary stability.
Clinical relevance
Fracture fixation of phalangeal fractures using plate osteosynthesis may have the advantage of a very rigid reduction, but disadvantages such as stiffness owing to the more invasive surgical approach and soft tissue irritation should be taken into account. Headless compression screws represent a minimally invasive choice for fixation with good biomechanical properties.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition.
In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon.
To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.