Open-Access-Journals @ Otto-von-Guericke-Universität Magdeburg
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Steric Effect Induced Heat Transfer for Electroosmotic Flow of Carreau Fluid through a Wavy Microchannel
No full textWe investigate the heat transfer and flow characteristics for an electroosmotic flow of Carreau fluid through a wavy microchannel, considering the finite size of ions i.e., steric effect. The flow of electrolytic liquid is considered steady, two-dimensional and incompressible. The modified Poisson-Boltzmann equation, Laplace equation, continuity equation, momentum equation, and energy equation are solved numerically using a finite element method-based solver. The computed flow and temperature fields are validated by comparison with published results. The flow and temperature fields and average Nusselt number are computed by varying the steric factor, Weissenberg number, dimensionless amplitude and Brinkman number in the following ranges: 0≤ υ ≤0.3, 0.01≤Wi ≤1, 0.1≤ α ≤ 0.5 and 10-5≤ Br ≤10-3, respectively. We found the locations of the local maxima and minima of Nusselt number at the convex and concave surfaces of the channel for a lower Brinkman number (=10-5). In contrast, the corresponding locations are swapped at higher Brinkman number (=10-3). The value of average Nusselt number increases with the increase in Weissenberg number and decreases with the steric factor for the smaller Brinkman number (=10-5). Whereas, it decreases with Wi for non-zero values the of steric factor with higher Brinkman number (=10-3). Moreover, the increase in amplitude enhances the average Nusselt number at higher Brinkman number (=10-3)
Wohnen, Wohnungspolitik und Nachhaltigkeit: Eine Einführung
No full textDiese Einführung erörtert grundsätzlich das Verständnis von Wohnen, nachhaltigem Wohnen, Wohnungspolitik und Wohnungspolitikforschung. Dabei werden verschiedene Perspektiven auf Wohnungspolitik (liberal, wohlfahrtsstaatlich, kritisch) skizziert und mit normativen sowie empirisch-analytischen Wissenschaftsverständnissen abgeglichen. Nachhaltige Wohnungspolitik kann sich dabei einerseits auf grüne Wachstumsparadigmen zur Energieeffizienz und Technologieorientierung beziehen oder andererseits einen Postwachstums-Ansatz vertreten, der auf Verhaltensänderungen unserer bisherigen Wohnroutinen abzielt und Suffizienz in den Fokus rückt.This introduction discusses the understanding of housing, sustainable housing, housing politics and housing politics research. It outlines various perspectives on housing policies (liberal, welfare state, critical) and discusses their nexus to normative as well as empirical-analytical scientific understandings. Moreover, sustainable housing policies either refer to the paradigm of Green Growth (energy efficiency, technology orientation), or they represent a Post-Growth approach that questions the behavior of our previous living routines and focuses on sufficiency
Optimal Service Time Windows
No full textBecause customers must usually arrange their schedules to be present for home services, they desire an accurate estimate of when the service will take place. However, even when firms quote large service time windows, they are often missed, leading to customer dissatisfaction. Wide time windows and frequent failures occur because time windows must be communicated to customers in the face of several uncertainties: future customer requests are unknown, final service plans are not yet determined, and when fulfillment is outsourced to a third party, the firm has limited control over routing procedures. Even when routing is performed in-house, time windows typically do not receive explicit consideration. In this paper, we show how companies can communicate reliable and narrow time windows to customers in the face of arrival time uncertainty. Under mild assumptions, our main result characterizes the optimal policy, identifying structure that reduces a high-dimensional stochastic non-linear optimization problem to a root-finding problem in one dimension. The result inspires a practice-ready heuristic for the more general case. Relative to the industry standard of communicating uniform time windows to all customers, and to other policies applied in practice, our method of quoting customer-specific time windows yields a substantial increase in customer convenience without sacrificing reliability of service, providing results that nearly achieve the lower bound on the optimal solution. Our results show that (i) time windows should be tailored to individual customers, (ii) time window sizes should be proportional to the service level, (iii) larger time windows should be assigned to earlier requests and smaller time windows to later requests, (iv) larger time windows should be assigned to customers further from the depot of operation and smaller time windows to closer customers, and (v) two time windows for one customer are helpful in some cases
Holistic approach for microgrid planning and operation for e-mobility infrastructure under consideration of multi-type uncertainties
No full textIntegrating renewable energys ources in sectors such as electricity, heat, and transportation must be structured in an economic, technological, and emission- efficient manner to address global environmental issues.Microgrids appear to be the solution for large-scale renewable energy integration in these sectors.The microgrid components must be optimally planned and operated to prevent high costs, technical issues, and emissions. Existing approaches for optimal microgrid planning and operation in the literature do not include a solution for e-mobility infrastructure. As a consequence, a compact e-mobility infrastructure metho- dology is provided.The development of e-mobility infrastructure has as sociated uncertainties (short and long-term). As a result, a new stochastic method re- ferred to as IGDM-DRO is proposed in this dissertation.The proposed method provides a risk-averse strategy for microgrid planning and operation by including long-term and short-term uncertainty related to e-mobility.The multi-cut ben- der decomposition is applied for IGDM-DRO to prevent the suggested method’s intractability.Finally, the deterministic and stochastic methodologies are com bined in an ovelholistic approach for microgrid design and operation in terms of cost and robustness.The proposed method ist ested on a new settlement area in Magdeburg, Germany, under three different EV development scenarios (nega- tive, trend, andpositive).The share for the number of electric vehicles reached 31 percent of conventional vehicles by the end of the planned horizon. As a result, the microgrid’s overall cost has been increased by 2.3 to 2.9 percent per electric vehicle.Three public electric vehicle charging stations will be required in the investigated settlement are a intrend 2031.The investigated settlement area will require a total cost of 127,029 € in the trend scenario.To achieve full robustness against long-term uncertainties,the cost of the microgrid needs to be increased by 80 percent
23. Dresdener Kreis Elektroenergieversorgung: Begleitband zum Workshop 2022 in Magdeburg
No full textIm Jahr 2022 war die Otto-von-Guericke-Universität Magdeburg Ausrichter des alljährlichen Treffens des „Dresdener Kreis“. Vom 15. bis zum 16. März nahmen neben dem LENA (Lehrstuhl für Elektrische Netze und Erneuerbare Energie) auch Mitarbeitende der Universitäten Dresden, Hannover und Duisburg-Essen am Doktorandenseminar teil
Artemis – der automatisierte Bogensch¨utze Roboter zum Treffen der Ziele
No full textW¨ahrend des j¨ahrlichen Projektseminars ”Elektrotechnik und Informationstechnik“ an der Otto-von-Guericke-Universit¨at war ein Bogensch¨utzen-Roboter aufzubauen, der durch den Einsatz der NXT-Steine die Kompetenz besaß, Ziele mit Pfeilen zu treffen. Im vorliegenden Bericht ist die Umsetzung des Roboters beschrieben. Hierbei werden insbesondere die Konstruktionsmerkmale, wichtige Programmteile und auftretende Probleme betrachtet
MTV - Magdeburg Tool for Videoconferences
No full textMTV is a software tool (citeware) for economic experiments facilitating researchers to gather video data from communication-based experiments in a way that these can be later used for automatic analysis through machine learning techniques. The browser-based tool comes with an easy user interface and can be easily integrated in z-Tree or oTree. It provides the experimenters control about several communication parameters (e.g., number of participants, duration), produces high-quality video data, and circumvents the Cocktail Party Problem by producing separate audio files. Using some of the recommended Voice-to-Text AI, the experimenters can transcribe individual audio files. MTV can merge these individual transcriptions to one conversation. This paper describes the underlying principles of the tool, technical requirements, possible areas of application, and current limitations
Adaptive stochastic lookahead policies for dynamic multi-period purchasing and inventory routing
No full textWe present a problem motivated by discussions with Colombian e-commerce platforms for agri-food products. In regular time intervals (periods), the platforms collect groceries from local farmers and stores them at a warehouse to distribute them to local customers. The supply quantities and prices per farmer and the cumulated customer demand can change from period to period. Thus, there is value in purchasing more than needed in one period to exploit cheap prices and consolidation opportunities, to hedge against future uncertainty, and to save routing cost in future periods. A careful balance between too much and not enough inventory needs to be found, especially, since inventory perishes over time. The resulting optimization problem is a stochastic dynamic multi-period routing problem with inventory and purchasing decisions. The decision space of the problem is vast as it combines purchasing, inventory, and routing decisions. Further, the value of a decisions is unknown since it depends on future developments and decisions. We propose solving the problem with a stochastic lookahead method. In every state, the method samples a set of future realizations and solves the resulting two-stage stochastic program. To cope with the complex decision space in first and second stage, we propose a “soft” decomposition where the inventory and purchasing decision are fully considered, but the routing decisions are simplified and their cost is approximated via a cost function approximation. As the routing cost also depends on future decisions, the approximated cost are learned iteratively via repeated simulation and adaption of the lookahead. We show that our method outperforms a large number of benchmark policies for a variety of instances. We further analyze the functionality of our method and investigate variation in the problem dimensions in a comprehensive analysis
Rule-based systems for leadership style selection
No full textIn personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, we assume that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice a wide range of models has been developed in the scientific literature, from which we want to pick out and focus on the so-called normative decision model by Vroom & Yetton (Vroom/Yetton 1973). While the original model is based on univocal rules, in this paper we develop a fuzzy rule system
Experimental economics for machine learning - a methodological contribution
No full textIn this paper, we investigate how technology has contributed to experimental economics in the past and illustrate how experimental economics can contribute to technological progress in the future. We argue that with machine learning (ML) a new technology is at hand, where for the first time experimental economics can contribute to enabling substantial improvement of technology. At the same time, ML opens up new questions for experimental research because it can generate observations that were previously impossible. To demonstrate this, we focus on algorithms trained to detect lies. Such algorithms are of high relevance for research in economics as they deal with the ability to retrieve otherwise private information. We deduce that most of the commonly applied data sets for the training of lie detection algorithms could be improved by applying the toolbox of experimental economics. To illustrate this, we replicate the “lies in disguise-experiment” (Fischbacher & Föllmi-Heusi, 2013) with a modification regarding monitoring. The modified setup guarantees a certain level of privacy from the experimenter yet allows to record the subjects as they lie to the camera. Our results indicate the same lying behavior as in the original experiment despite monitoring. Yet, our experiment allows for an individual- level analysis and provides a video data set that can be used for lie detection algorithms