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Radio frequency (RF) power amplifiers (PA) are the most power consuming components of a mobile communications unit. They are used to convert the DC power from the battery into RF power delivered to the antenna. In a cell phone it becomes very important to use highly efficient power amplifiers, such as Class C and Class E PAs, to increase the talk time which is directly proportional to the battery life. On the other hand, these RF PAs are inherently nonlinear and produce spectral regrowth and other undesirable effects.
Model-based analysis of Electrochemical Pressure Impedance Spectroscopy (EPIS) for PEM Fuel Cells
(2019)
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products, in particular fuel cells, offer an additional observable, that is, the gas pressure. The dynamic coupling of current or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have previously introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. First EPIS experiments on PEM fuel cells have recently been shown [3].
We present a detailed modeling and simulation analysis of EPIS of a PEM fuel cell. We use a 1D+1D continuum model of a fuel/air channel pair with GDL and MEA. Backpressure is dynamically varied, and the resulting simulated oscillation in cell voltage is evaluated to yield the ▁Z_( V⁄p_ca ) EPIS signal. Results are obtained for different transport situations of the fuel cell, giving rise to very complex EPIS shapes in the Nyquist plot. This complexity shows the necessity of model-based interpretation of the complex EPIS shapes. Based on the simulation results, specific features in the EPIS spectra can be assigned to different transport domains (gas channel, GDL, membrane water transport).
Battery degradation is a complex physicochemical process that strongly depends on operating conditions and environment. We present a model-based analysis of lithium-ion battery degradation in smart microgrids, in particular, a single-family house and an office tract with photovoltaics generator. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including SEI formation as ageing mechanism. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics, inverter, power consumption profiles, grid interaction, and energy management system, fed with historic weather data. The behavior of the cell in terms of degradation propensity, performance, state of charge and other internal states is predicted over an annual operation cycle. As result, we have identified a peak in degradation rate during the battery charging process, caused by charging overpotentials. Ageing strongly depends on the load situation, where the predicted annual capacity fade is 1.9 % for the single-family house and only 1.3 % for the office tract.
Battery degradation is a complex physicochemical process that strongly depends on operating conditions. We present a model-based analysis of lithium-ion battery degradation in a stationary photovoltaic battery system. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including solid electrolyte interphase (SEI) formation. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics (PV), inverter, load, grid interaction, and energy management system, fed with historic weather data. Simulations are carried out for two load scenarios, a single-family house and an office tract, over annual operation cycles with one-minute time resolution. As key result, we show that the charging process causes a peak in degradation rate due to electrochemical charge overpotentials. The main drivers for cell ageing are therefore not only a high state of charge (SOC), but the charging process leading towards high SOC. We also show that the load situation not only influences system parameters like self-sufficiency and self-consumption, but also has a significant impact on battery ageing. We assess reduced charge cut-off voltage as ageing mitigation strategy.
The conversion of space heating for private households to climate-neutral energy sources is an essential component of the energy transition, as this sector as of 2018 was responsible for 9.4 % of Germany’s carbon dioxide emissions. In addition to reducing demand through better insulation, the use of heat pumps fed with electricity from renewable energy sources, such as on-site photovoltaics (PV) systems, is an important solution approach.
Advanced energy management and control can help to make optimal use of such heating systems. Optimal here can e.g. refer to maximizing self-consumption of self-generated PV power, extended component lifetime or a grid-friendly behavior that avoids load peaks. A powerful method for this is model predictive control (MPC), which calculates optimal schedules for the controllable influence variables based on models of the system dynamics, current measurements of system states and predictions of future external influence parameters.
In this paper, we will discuss three different use cases that show how artificial intelligence can contribute to the realization of such an MPC-based energy management and control system. This will be done using the example of a real inhabited single family home that has provided the necessary data for this purpose and where the methods are implemented and tested. The heating system consists of an air-water heat pump with direct condensation, a thermal stratified storage tank, a pellet burner and a heating rod and provides both heating and hot water. The house generates a significant portion of its electricity needs through a rooftop PV system.
Modelbasierte Zustandsschätzung elektrischer Betriebsmittel der Mittel- und Niederspannungsebenen
(2022)
Im Projekt MOBCOM wird ein neues Verfahren zur Zustandsüberwachung von elektrischen Betriebsmitteln in Niederspannungsnetzen und Anlagen entwickelt. Mittels PLC (power line communication) Technologie werden hochfrequente transiente Vorgänge auf dem Stromkanal und dessen Übertragungseigenschaften erfasst und bewertet.
In dem Abschlussbericht wird ein Prototyp für Powerline-Kommunikation zur Netzüberwachung beschrieben. Der Prototyp basiert auf einem PLC-Empfänger, welcher den Kanal misst, um so Informationen über den PLC-Kanal und den aktuellen Zustand des Stromnetzes zu erhaltet. Der PLC-Empfänger verwendet das Kommunikationssignal, um eine genaue Schätzung des Stromkanals zu erhalten und liefert Informationen zur Erkennung von Teilentladungen und anderen Anomalien im Netz. Diese Überwachung des Stromnetzes macht sich die bestehende PLC-Infrastruktur zunutze und verwendet die ohnehin übertragenen Datensignale, um eine Echtzeitmessung der Kanalübertragungsfunktion und des empfangenen Rauschsignals zu erhalten. Da dieses Signal im Vergleich zu einfacheren Messsensoren mit einer hohen Abtastrate abgetastet wird, enthält es wertvolle Informationen über mögliche Beeinträchtigungen im Netz, die behoben werden müssen. Während die Kanalmessungen auf einem empfangenen PLC-Signal beruhen, können Informationen über Teilentladungen oder andere Störquellen allein durch einen PLC-Empfänger gesammelt werden, d. h. ohne eine PLC-Übertragung. Es wurde ein Prototyp auf Basis von Software Defined Radio entwickelt, der die gleichzeitige Kommunikation und Erfassung für ein Stromnetz implementiert.
This article presents the development, parameterization, and experimental validation of a pseudo-three-dimensional (P3D) multiphysics model of a 350 mAh high-power lithium-ion pouch cell with graphite anode and lithium cobalt oxide/lithium nickel cobalt aluminum oxide (LCO/NCA) blend cathode. The model describes transport processes on three different scales: Heat transport on the macroscopic scale (cell), mass and charge transport on the mesoscopic scale (electrode pair), and mass transport on the microscopic scale (active material particles). A generalized description of electrochemistry in blend electrodes is developed, using the open-source software Cantera for calculating species source terms. Very good agreement of model predictions with galvanostatic charge/discharge measurements, electrochemical impedance spectroscopy, and surface temperature measurements is observed over a wide range of operating conditions (0.05C to 10C charge and discharge, 5°C to 35°C). The behavior of internal states (concentrations, potentials, temperatures) is discussed. The blend materials show a complex behavior with both intra-particle and inter-particle non-equilibria during cycling.
The internal crowdsourcing-based ideation within a company can be defined as an involvement of its staff, specialists, managers, and other employees, to propose solution ideas for a pre-defined problem. This paper addresses a question, how many participants of the company-internal ideation process are required to nearly reach the ideation limit for the problems with a finite number of workable solutions. To answer the research question, the author proposes a set of metrics and a non-linear ideation performance function with a positive decreasing slope and ideation limit for the closed-ended problems. Three series of experiments helped to explore relationships between the metric attributes and resulted in a mathematical model which allows companies to predict the productivity metrics of their crowdsourcing ideation activities such as quantity of different ideas and ideation limit as a function of the number of contributors, their average personal creativity and ideation efficiency of a contributors’ group.
Modeling and simulation play a key role in analyzing the complex electrochemical behavior of lithium-ion batteries. We present the development of a thermodynamic and kinetic modeling framework for intercalation electrochemistry within the open-source software Cantera. Instead of using equilibrium potentials and single-step Butler-Volmer kinetics, Cantera is based on molar thermodynamic data and mass-action kinetics, providing a physically-based and flexible means for complex reaction pathways. Herein, we introduce a new thermodynamic class for intercalation materials into the open-source software. We discuss the derivation of molar thermodynamic data from experimental half-cell potentials, and provide practical guidelines. We then demonstrate the new class using a single-particle model of a lithium cobalt oxide/graphite lithium-ion cell, implemented in MATLAB. With the present extensions, Cantera provides a platform for the lithium-ion battery modeling community both for consistent thermodynamic and kinetic models and for exchanging the required thermodynamic and kinetic parameters. We provide the full MATLAB code and parameter files as supplementary material to this article.
Modeling and Simulation the Influence of Solid Carbon Formation on SOFC Performance and Degradation
(2013)
In their famous work on prospect theory Kahneman and Tversky have presented a couple of examples where human decision making deviates from rational decision making as defined by decision theory. This paper describes the use of extended behavior networks to model human decision making in the sense of prospect theory. We show that the experimental findings of non-rational decision making described by Kahneman and Tversky can be reproduced using a slight variation of extended behavior networks.
Combined heat and power production (CHP) based on solid oxide fuel cells (SOFC) is a very promising technology to achieve high electrical efficiency to cover power demand by decentralized production. This paper presents a dynamic quasi 2D model of an SOFC system which consists of stack and balance of plant and includes thermal coupling between the single components. The model is implemented in Modelica® and validated with experimental data for the stack UI-characteristic and the thermal behavior. The good agreement between experimental and simulation results demonstrates the validity of the model. Different operating conditions and system configurations are tested, increasing the net electrical efficiency to 57% by implementing an anode offgas recycle rate of 65%. A sensitivity analysis of characteristic values of the system like fuel utilization, oxygen-to-carbon ratio and electrical efficiency for different natural gas compositions is carried out. The result shows that a control strategy adapted to variable natural gas composition and its energy content should be developed in order to optimize the operation of the system.
Radiation is an important means of heat transfer inside an electric arc furnace (EAF).
To gain insight into the complex processes of heat transfer inside the EAF vessel, not only radiation from the surfaces but also emission and absorption of the gas phase and the dust cloud need to be considered.
Furthermore, the radiative heat exchange depends on the geometrical configuration which is continuously changing throughout the process.
The present paper introduces a system model of the EAF which takes into account the radiative heat transfer between the surfaces
and the participating medium. This is attained by the development of a simplified geometrical model,
the use of a weighted-sum-of-gray-gases model, and a simplified consideration of dust radiation.
The simulation results were compared with the data of real EAF plants available in literature.
Modeling of Random Variations in a Switched Capacitor Circuit based Physically Unclonable Function
(2020)
The Internet of Things (IoT) is expanding to a wide range of fields such as home automation, agriculture, environmental monitoring, industrial applications, and many more. Securing tens of billions of interconnected devices in the near future will be one of the biggest challenges. IoT devices are often constrained in terms of computational performance, area, and power, which demand lightweight security solutions. In this context, hardware-intrinsic security, particularly physically unclonable functions (PUFs), can provide lightweight identification and authentication for such devices. In this paper, random capacitor variations in a switched capacitor PUF circuit are used as a source of entropy to generate unique security keys. Furthermore, a mathematical model based on the ordinary least square method is developed to describe the relationship between random variations in capacitors and the resulting output voltages. The model is used to filter out systematic variations in circuit components to improve the quality of the extracted secrets.
Im vorliegenden Beitrag wird ein Strommarktsimulationsmodell entwickelt, mit dessen Hilfe die Bereitstellung von Flexibilität auf dem Strom- und Regelleistungsmarkt in Deutschland modell-gestützt analysiert werden soll. Das Modell bildet dabei zwei parallel verlaufende, zentrale Wettbewerbsmärkte ab, an denen Akteure durch die individuelle Gebotsermittlung handeln können. Die entsprechend hierzu entwickelte Gebotslogik wird detailliert erläutert, wobei der Fokus auf der Flexibilität fossil-thermischer Kraftwerke liegt. In der anschließenden Gegen-überstellung mit realen Marktpreisen zeigt sich, dass die verwendete Methodik und die Ge-botslogik den bestehenden Markt und dessen Marktergebnis in geeigneter Form wiederspie-geln, wodurch zukünftig unterschiedlichste Flexibilitätsszenarien analysiert und Aussagen zu deren Auswirkungen auf den Markt und seine Akteure getroffen werden können.
Um den Prozess der Direktreduktion von Eisenerz computergestützt zu simulieren, werden mathematische Modelle, zur Beschreibung von Gas-Feststoff-Reaktionen, in Python implementiert. In der vorliegenden Arbeit wird ein einzelnes Pellet aus Eisenerz, welches sich in einem Gasstrom aus reinem Wasserstoff befindet, betrachtet. Es werden mehrere Modellansätze aus der Literatur miteinander verglichen und davon geeignete zur recheneffizienten Implementierung ausgewählt. Die entwickelte Simulationssoftware besitzt eine grafische Oberfläche und bietet die Auswahl aus drei Modellen mit unterschiedlichem Detaillierungsgrad. Diese sind vollständig parametriert und die meisten Parameter werden temperaturabhängig bestimmt oder sind frei wählbar. Die Durchführung von Parameterstudien ist über die lineare Variierung eines beliebigen Parameters möglich. Die Ergebnisse der Simulation können dann in Abhängigkeit der Zeit dargestellt oder im CSV-Format exportiert werden. Die Rechenmodelle sind in einem separaten Python-Modul zusammengefasst und können einfach in eine übergeordnete Modellierung eingebaut werden. Zur Validierung erfolgt ein Abgleich mit experimentellen Literaturdaten. Abschließend werden die Stärken und Schwächen der implementierten Modelle gegenübergestellt und bewertet.
Für langfaserverstärkte Thermoplaste (LFT) wird ein repräsentatives Volumenelement (RVE) für FEM-Simulationen generiert. Dies geschieht unter Berücksichtigung von mikrostrukturellen Kenngrößen wie Faserorientierungsverteilung, -volumengehalt und -längenverteilung, die für einen charakteristischen Werkstoffzustand experimentell ermittelt wurden. Mittels Mikrostruktursimulationen wird das Kriechverhalten von LFT untersucht. Das viskoelastische Verhalten der Matrix wird experimentell an Substanzproben aus Polypropylen ermittelt und in die RVE-Simulationen mit einem modifizierten Burgers-Modell implementiert. Schließlich werden die Rechnungen mit verschiedenen, fiktiven sowie experimentell ermittelten Faserlängenverteilungen mit Kriechversuchen am LFT verglichen. Es zeigt sich eine starke Abhängigkeit des Kriechverhaltens von der Faserlänge und eine hohe Prognosegüte der Simulationen, die die experimentell ermittelte Längenverteilung berücksichtigen.
Seit 1997 finden jährlich Weltmeisterschaften im Roboterfußball statt. Das Ziel ist es dabei, bis 2050 eine Mannschaft aus Robotern zu stellen, die gegen den menschlichen Fußballweltmeister gewinnt. Dazu müssen die Roboter in der Lage sein, das Verhalten ihrer menschlichen Gegner einzuschätzen und ihre Entscheidungen vorauszuahnen. Während die gängigen Verfahren zur Entscheidungsfindung in unsicheren Umgebungen in der Regel auf rationalen Entscheidungen nach der Entscheidungstheorie basieren, zeigt sich, dass menschliches Entscheiden teilweise nicht dieser Rationalität folgt. Daniel Kahneman und Amos Tversky zeigten das in vielen Studien und entwickelten daraus die bekannte Prospect Theory für die Kahneman 2002 den Wirtschaftsnobelpreis erhielt. In diesem Artikel wird beschrieben, wie Extended Behavior Networks (EBNs) auf einfache Weise erweitert werden können, um menschliches Entscheidungsverhalten auch in Situationen reproduzieren zu können, die von der rationalen Entscheidungstheorie abweichen.
Die vorliegende Bachelor-Thesis befasst sich mit der Thematik, eine drahtlose Energieübertragung mit Hilfe induktiv resonanter Kopplung zu simulieren und aufzubauen. Durch die in den letzten Jahren immer größer werdende Elektromobilität steigt auch das Interesse an einem drahtlosen Transfer von elektrischem Strom. Doch auch in kleineren Leistungsbereichen ist ein drahtloses Aufladen, wie z.B. bei Laptops und Handys, ein angesagtes Thema. Mit Hilfe von zwei resonanten Schwingkreisen wird ein Austausch an Energie zwischen Sender- und Empfängerschwingkreis demonstriert. Die Grundlagen der magnetischen Induktion wie auch die Grundlagen von elektrischen Schwingkreisen sind hierfür essentiell und werden in dem ersten Kapitel aufgegriffen. Durch das Aufstellen eines mathematischen Modells, im zweiten Kapitel, wird das Prinzip der magnetischen Kopplung und das Phänomen der Frequenzspaltung von gekoppelten Systemen ausführlich behandelt und aufgestellt. Spider-Web Spulen, welche schon in niedrigen Frequenzbereichen hohe Güten aufweisen können, werden für den folgenden Aufbau verwendet. In den darauf folgenden Kapiteln wird das über das Magnetfeld gekoppelte System ausführlich untersucht. Das System erzielt eine Leistungsübertragung von 20W über 30 cm mit einer Effizienz von ungefähr 52%. Des Weiteren konnte der Punkt der kritischen Kopplung, durch eine Verminderung der ohmschen Last im Sendeschwingkreis, auf 50 cm gelegt werden.
Ziel dieser Arbeit ist die Modellierung und Nutzung eines digitalen Zwillings am Beispiel eines realen Tiny-Houses. Dazu werden für die Komponenten der technischen Gebäudeausrüstung Wärmepumpe, thermische Speicher, thermoaktives Bauteilsystem, PVT-Kollektoren und Batterie als Grey-Box-Modelle modelliert und in der Python-Umgebung umgesetzt. In dieser Arbeit wird auf die physikalischen Hintergründe und mathematischen Formulierungen für jede Komponente eingegangen.
In einem automatisierten Programm werden die digitalen Komponenten mit Messwerten aus dem realen Anlagenbetrieb verknüpft. Dieses Skript wird zu Fehlererkennung verwendet. Dabei konnte ein fehlerhafter Betrieb der PVT-Kollektoren bewiesen werden.
Die Verknüpfung der einzelnen Komponenten zum digitalen Zwilling wird zur Betriebsoptimierung verwendet. Hierzu wird die Simulation des Ausgangszustands mit verschiedenen Optimierungsstrategien verglichen. Dabei konnte der Anlagenbetrieb hinsichtlich Komfortbedingungen und Energieeffizienz deutlich optimiert werden. Die finale Optimierungsstrategie basiert auf einereinfachen Wettervorhersage.
Mit der Modellierung und Nutzung eines digitalen Zwillings trägt diese Arbeit dazu bei, innovative Lösungen für die zukünftige Entwicklung und Gestaltung von Gebäuden sowie die Optimierung bereits bestehender Gebäude mithilfe digitaler Zwillinge voranzutreiben.
Hintergrund: Die Pulmonalvenenisolation (PVI) mit Hilfe von Kryoballonkathetern ist eine anerkannte Methode zur Behandlung von Vorhofflimmern (AF). Diese Methode bietet eine kürzere Behandlungsdauer als die klassische Therapie durch die Hochfrequenzablation (HF). Ziel dieser Studie war es, verschiedene Kryoballonkatheter, HF-Katheter und Ösophaguskatheter in ein Herzrhythmusmodell zu integrieren und mittels statischer und dynamischer Simulation elektrische und thermische Felder bei PVI unter Vorhofflimmern zu untersuchen.
Methodik: Die Modellierung und Simulation erfolgte mit der elektromagnetischen und thermischen Simulationssoftware CST (CST Darmstadt). Zwei Kryoballons, ein HF-Ablationskatheter und ein Ösophaguskatheter wurden auf der Grundlage der technischen Handbücher der Hersteller Medtronic und Osypka modelliert. Der 23 mm Kryoballon und ein kreisförmiger Mappingkatheter wurden in das Offenburger Herzrhythmusmodell integriert, insbesondere die left inferior pulmonary vein (LIPV) zur Simulation der thermischen Feldausbreitung während einer PVI. Die Simulation einer PVI mit HF-Energie wurde mit dem integrierten HF-Ablationskatheter in der Nähe der LIPV durchgeführt. Der im Herzrhythmusmodell platzierte TO8 Ösophaguskatheter ermöglichte die Ableitung linksatrialer elektrischer Felder bei AF und die Analyse thermischer Felder während PVI.
Ergebnisse: Elektrische Felder konnten bei Sinusrhythmus und AF mit einem AF-Fokus in der LIVP statisch und dynamisch im Herzen und Ösophagus simuliert werden. Bei einer simulierten 20 Sekunden Applikation eines Kryoballon-Katheters bei -50°C wurde eine Temperatur von -24°C in einer Tiefe von 0,5 mm im Myokard gemessen. In einer Tiefe von 1 mm betrug die Temperatur -3°C, bei 2 mm Tiefe 18°C und bei 3 mm Tiefe 29°C. Unter der 15 sekündigen Anwendung eines HF-Katheters mit einer 8-mm-Elektrode und einer Leistung von 5 W bei 420 kHz betrug die Temperatur an der Spitze der Elektrode 110°C. In einer Tiefe von 0,5 mm im Myokard betrug die Temperatur 75°C, in einer Tiefe von 1 mm 58°C, in einer Tiefe von 2 mm 45°C und in einer Tiefe von 3 mm 38°C. Im Ösophagus konnte bei den meisten Simulationen eine konstante Temperatur von 37°C gemessen und die Gefahr einer Ösophagus-Fistel ausgeschlossen werden. Bei Kryoablation der LIPV wurde eine Abkühlung des Ösophagus auf 30°C gemessen.
Schlussfolgerungen: Die Herzrhythmussimulation elektrischer und thermaler Felder ermöglichen mit Anwendung unterschiedlicher Herzkatheter eine statische und dynamische Simulation von PVI durch Kryoablation, HF-Ablation und Temperaturanalyse im Ösophagus. Unter Einbeziehung von MRT- oder CT-Daten können elektrische und thermale Simulationen möglicherweise zur Optimierung von PVIs genutzt werden.
Modelling and Simulation of Microscale Trigeneration Systems Based on Real- Life Experimental Data
(2017)
For the shift of the energy grid towards a smarter decentralised system flexible microscale trigeneration systems will play an important role due to their ability to support the demand side management in buildings. However to harness their potential modern control methods like model predictive control must be implemented for their optimal scheduling and control. To implement such supervisory control methods, first, simple analytical models representing the behaviour of the components need to be developed. At the Institute of Energy System Technologies in Offenburg we have built a real-life microscale trigeneration plant and present in this paper the models based on experimental data. These models are qualitatively validated and their application in the future for the optimal scheduling problem is briefly motivated.
Modelling detailed chemistry in lithium-ion batteries: Insight into performance, ageing and safety
(2018)
The paper is addressing the needs of the universities regarding qualification of students as future R&D specialists in efficient techniques for successfully running innovation process. In comparison with the engineers, the students often demonstrate lower motivation in learning systematic inventive techniques, like for example TRIZ methodology, and prefer random brainstorming for idea generation. The quality of obtained solutions also depends on the level of completeness of the problem analysis, which is more complex and time consuming in the case of interdisciplinary systems. The paper briefly describes one-semester-course of 60 hours in new product development with the Advanced Innovation Design Approach and TRIZ methodology, in which a typical industrial innovation process for one selected interdisciplinary mechatronic product is modelled.
Lithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis for the grey-box model. Unknown parameters and dependencies are then replaced by learnable parameters and neural networks. We use experimental full-cycle data and data from pulse tests of a lithium iron phosphate cell to train the model. Finally, we test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
Druckluft ist verdichtete atmosphärische Luft und wird in der Industrie sowie im Handwerk als Energieträger genutzt. Den vielfältigen Vorteilen stehen aber auch einige Nachteile gegenüber, wobei der wichtigste der Preis ist. Druckluft gilt als eine der teuersten Energieformen und die Energiekosten stellen den größten Kostenfaktor bei der Produktion dar. In der vorliegenden Arbeit soll eine modellprädiktive Regelung eines Druckluftsystems entworfen und implementiert werden. Das ökonomische Regelziel besteht darin, die Energiekosten bei der Erzeugung von Druckluft zu senken. Die Implementierung umfasst unterschiedliche Varianten eines Druckluftsystems. Dazu zählen folgende Auslegungsvarianten:
• Ein Druckluftsystem mit frequenzgeregeltem Kompressor
o Mit einem Schraubenkompressor
o Mit zwei Schraubenkompressoren
• Ein Druckluftsystem mit binärgeregeltem Kompressor
o Schraubenkompressor
o Kolbenkompressor
Basierend auf den erstellten Modellen wird ein modellprädiktiver Regler entworfen und implementiert. Die modellprädiktive Regelung leistet einen entscheidenden Beitrag zur Prozessoptimierung. Der Optimierungsalgorithmus erhöht bei niedrigen Strompreisen das Druckniveau im Behälter und profitiert bei hohen Preisen vom gespeicherten Luftvolumen. Die Flexibilität des Systems ist begrenzt. Mit zunehmender Behältergröße konvergieren die Kosten der Drucklufterzeugung gegen einen parameterabhängigen Wert des Systems. Außerdem bestimmen die Systemparameter die Lösbarkeit des Optimierungsproblems. Im Vergleich zu den frequenzgeregelten Kompressoren sind die binärgeregelten Kompressoren nur unter modifizierten Annahmen einsetzbar, ansonsten kann das Optimierungsproblem nicht gelöst werden.
Lithium‐ion battery cells are multiscale and multiphysics systems. Design and material parameters influence the macroscopically observable cell performance in a complex and nonlinear way. Herein, the development and application of three methodologies for model‐based interpretation and visualization of these influences are presented: 1) deconvolution of overpotential contributions, including ohmic, concentration, and activation overpotentials of the various cell components; 2) partial electrochemical impedance spectroscopy, allowing a direct visualization of the origin of different impedance features; and 3) sensitivity analyses, allowing a systematic assessment of the influence of cell parameters on capacity, internal resistance, and impedance. The methods are applied to a previously developed and validated pseudo‐3D model of a high‐power lithium‐ion pouch cell. The cell features a blend cathode. The two blend components show strong coupling, which can be observed and interpreted using the results of overpotential deconvolution, partial impedance spectroscopy, and sensitivity analysis. The presented methods are useful tools for model‐supported lithium‐ion cell research and development.
Modern Franciscan Leadership
(2020)
This article combines two important areas of practical theology: Monastic rules and leadership in a cloistral organisation, using the Rule of Saint Francis as a prominent example. The aim of this research is to examine how living Christian tradition in a monastic order affects leadership today, discovering how the Rule and Franciscan spirituality impact managing a convent. The research question is answered within this inductive research applying the methodology of the ‘theology in four voices.’ Based on the results, it is possible to build a coherent leadership system based on Biblical and Franciscan sources.
Thin-layer chromatography (TLC) is a well-established and widely used separation technique. Most undergraduate students of chemistry or food science used TLC as a primitive separation tool, which does not need more than small pieces of TLC plates, a glass jar and some solvents. TLC has evolved from a simple separation method of the past into an instrumental technique that offers automation, reproducibility and accurate quantification for a wide variety of applications [1]. The use of modern 10*10 cm TLC plates with narrow particle size distribution is called high performance thin layer chromatography (HPTLC), to distinguish the method from the use of traditional 20 20 cm TLC plates.
We tested the MOF framework Cu-BTC for natural gas (NG) storage. Adsorption isotherms of C1–C4 alkanes were simulated applying the Grand Canonical ensemble and the Monte Carlo algorithm in a classical molecular mechanics approach. Experimental monocomponent isotherm of the alkanes was used to validate the force field. We performed multicomponent adsorptions calculations for three different quaternary mixtures of C1–C4 alkanes, matching typical NG streams composition, and predicted theoretical storage capacities, efficiency and accumulation of the NG within that composition. Despite being one of the frameworks with greatest storage capacity of methane, we found that Cu-BTC presented great sensitivity to the variation of the heavier alkanes in NG composition. When we increase the percentage of butane from 0.1% to 0.7% in the mixture, the mass of components retained in the discharge pressure (1 bar) increases from 35 to 60%. We also perform siting and interaction energy investigations and compare the NG storage performance of the Cu-BTC with that of activated carbons. To our knowledge, this is the first study regarding the efficiency of the NG storage in Cu-BTC.
Titanium and stainless steel are commonly known as osteosynthesis materials with high strength and good biocompatibility. However, they have the big disadvantage that a second operation for hardware removal is necessary. Although resorbable systems made of polymers or magnesium are increasingly used, they show some severe adverse foreign body reactions or unsatisfying degradation behavior. Therefore, we started to investigate molybdenum as a potential new biodegradable material for osteosynthesis in craniomaxillofacial surgery. To characterize molybdenum as a biocompatible material, we performed in vitro assays in accordance with ISO Norm 10993-5. In four different experimental setups, we showed that pure molybdenum and molybdenum rhenium alloys do not lead to cytotoxicity in human and mouse fibroblasts. We also examined the degradation behavior of molybdenum by carrying out long-term immersion tests (up to 6 months) with molybdenum sheet metal. We showed that molybdenum has sufficient mechanical stability over at least 6 months for implants on the one hand and is subject to very uniform degradation on the other. The results of our experiments are very promising for the development of new resorbable osteosynthesis materials for craniomaxillofacial surgery based on molybdenum.
Monitoring of the molecular structure of lubricant oil using a FT-Raman spectrometer prototype
(2014)
The determination of the physical state of the lubricant materials in complex mechanical systems is highly critical from different points of view: operative, economical, environmental, etc. Furthermore, there are several parameters that a lubricant oil must meet for a proper performance inside a machine. The monitoring of these lubricants can represent a serious issue depending on the analytical approach applied. The molecular change of aging lubricant oils have been analyzed using an all-standard-components and self-designed FT-Raman spectrometer. This analytical tool allows the direct and clean study of the vibrational changes in the molecular structure of the oils without having direct contact with the samples and without extracting the sample from the machine in operation. The FT-Raman spectrometer prototype used in the analysis of the oil samples consist of a Michelson interferometer and a self-designed photon counter cooled down on a Peltier element arrangement. The light coupling has been accomplished by using a conventional 62.5/125μm multi-mode fiber coupler. The FT-Raman arrangement has been able to extract high resolution and frequency precise Raman spectra, comparable to those obtained with commercial FT-Raman systems, from the lubricant oil samples analyzed. The spectral information has helped to determine certain molecular changes in the initial phases of wearing of the oil samples. The proposed instrument prototype has no additional complex hardware components or costly software modules. The mechanical and thermal irregularities influencing the FT-Raman spectrometer have been removed mathematically by accurately evaluating the optical path difference of the Michelson interferometer. This has been achieved by producing an additional interference pattern signal with a λ= 632.8 nm helium-neon laser, which differs from the conventional zero-crossing sampling (also known as Connes advantage) commonly used by FT-devices. It enables the FT-Raman system to perform reliable and clean spectral measurements from the analyzed oil samples.
This study focuses on the autonomous navigation and mapping of indoor environments using a drone equipped only with a monocular camera and height measurement sensors. A visual SLAM algorithm was employed to generate a preliminary map of the environment and to determine the drone's position within the map. A deep neural network was utilized to generate a depth image from the monocular camera's input, which was subsequently transformed into a point cloud to be projected into the map. By aligning the depth point cloud with the map, 3D occupancy grid maps were constructed by using ray tracing techniques to get a precise depiction of obstacles and the surroundings. Due to the absence of IMU data from the low-cost drone for the SLAM algorithm, the created maps are inherently unscaled. However, preliminary tests with relative navigation in unscaled maps have revealed potential accuracy issues, which can only be overcome by incorporating additional information from the given sensors for scale estimation.
Montage Collage Komposition
(2014)
MonteVideo Soundscapes
(2016)
Morphological transition of a rod-shaped phase into a string of spherical particles is commonly observed in the microstructures of alloys during solidification (Ratke and Mueller, 2006). This transition phenomenon can be explained by the classic Plateau-Rayleigh theory which was derived for fluid jets based on the surface area minimization principle. The quintessential work of Plateau-Rayleigh considers tiny perturbations (amplitude much less than the radius) to the continuous phase and for large amplitude perturbations, the breakup condition for the rod-shaped phase is still a knotty issue. Here, we present a concise thermodynamic model based on the surface area minimization principle as well as a non-linear stability analysis to generalize Plateau-Rayleigh’s criterion for finite amplitude perturbations. Our results demonstrate a breakup transition from a continuous phase via dispersed particles towards a uniform-radius cylinder, which has not been found previously, but is observed in our phase-field simulations. This new observation is attributed to a geometric constraint, which was overlooked in former studies. We anticipate that our results can provide further insights on microstructures with spherical particles and cylinder-shaped phases.
Human interaction frequently includes decision-making processes during which interactants call on verbal and non-verbal resources to manage the flow of interaction. In 2017, Stevanovic et al. carried out pioneering work, analyzing the unfolding of moment-by-moment dynamics by investigating the behavioral matching during search and decision-making phases. By studying the similarities in the participant's body sway during a conversation task in Finnish, the authors showed higher behavioral matching during decision phases than during search phases. The purpose of this research was to investigate the whole-body sway and its coordination during joint search and decision-making phases as a replication of the study by Stevanovic et al. (2017) but based on a German population. Overall, 12 dyads participated in this study and were asked to decide on 8 adjectives, starting with a pre-defined letter, to describe a fictional character. During this joint-decision task (duration: 206.46 ± 116.08 s), body sway of both interactants was measured using a 3D motion capture system and center of mass (COM) accelerations were computed. Matching of body sway was calculated using a windowed cross correlation (WCC) of the COM accelerations. A total of 101 search and 101 decision phases were identified for the 12 dyads. Significant higher COM accelerations (5.4*10−3 vs. 3.7*10−3 mm/s2, p < 0.001) and WCC coefficients (0.47 vs. 0.45, p = 0.043) were found during decision-making phases than during search phases. The results suggest that body sway is one of the resources humans use to communicate the arrival at a joint decision. These findings contribute to a better understanding of interpersonal coordination from a human movement science perspective.
With our society moving towards Industry 4.0, an increasing number of tasks and procedures in manual workplaces are augmented with a digital component. While the research area of Internet-of-Things focuses on combining physical objects with their digital counterpart, the question arises how the interface to human workers should be designed in such Industry 4.0 environments. The project motionEAP focuses on using Augmented Reality for creating an interface between workers and digital products in interactive workplace scenarios. In this paper, we summarize the work that has been done in the motionEAP project over the run-time of 4 years. Further, we provide guidelines for creating interactive workplaces using Augmented Reality, based on the experience we gained.
Zielvereinbarungen sollen SMART formuliert werden, um die Leistungsbereitschaft von Mitarbeitern optimal zu fördern - so wird es zumindest in der praxisorientierten betriebswirtschaftlichen Literatur propagiert. Ob Zielvereinbarungen, die spezifisch, messbar, erreichbar, relevant für das Unternehmen und zeitlich terminiert sind, wirklich eine höhere Leistungsbereitschaft zur Folge haben, wird im Folgenden auf Basis einer empirischen Untersuchung überprüft.
MPC-Workshop Februar 2001
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MPC-Workshop Februar 2020
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MPC-Workshop Juni 2002
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Diese Bachelor Thesis behandelt das Thema MQTT 5, ein Anwendungsprotokoll im Internet der Dinge, das im Januar 2018 veröffentlicht wurde. MQTT 5 dient zur Kommunikation zwischen Geräten die mit dem Internet verbunden sind.
Innerhalb dieser Thesis werden die Neuerungen und Verbesserungen von MQTT 5 beschrieben.
Es wird untersucht, welche Mikrocontroller, SoC-Computer, Programmier-Frameworks und lattformdienste MQTT 5 unterstützen.
Anschließend wird die Entwicklung eines Smarthome-Szenarios beschrieben, das im "Interaktive Verteilte Systeme Labor" an der Hochschule Offenburg zur Anwendung kommt.
Um die Umgebung während der Durchführung von Laborversuchen zu verbessern,werden die Temperatur, Luftfeuchtigkeit, Luftqualität, Lautstärke und Lichtstärke im Labor gemessen.
Diese Werte werden anhand von Lichtern, die ihre Farbe ändern und einer Steckdose, die sich je ach Wert ein- und ausschaltet, visualisiert.
Correlation Clustering, also called the minimum cost Multicut problem, is the process of grouping data by pairwise similarities. It has proven to be effective on clustering problems, where the number of classes is unknown. However, not only is the Multicut problem NP-hard, an undirected graph G with n vertices representing single images has at most edges, thus making it challenging to implement correlation clustering for large datasets. In this work, we propose Multi-Stage Multicuts (MSM) as a scalable approach for image clustering. Specifically, we solve minimum cost Multicut problems across multiple distributed compute units. Our approach not only allows to solve problem instances which are too large to fit into the shared memory of a single compute node, but it also achieves significant speedups while preserving the clustering accuracy at the same time. We evaluate our proposed method on the CIFAR10 …
Muli-scale thermos-electrochemical modelling of aging mechanisms in an LFP/graphite lithium-ion cell
(2017)
Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term ‘agent’ exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.
With the surge in global data consumption with proliferation of Internet of Things (IoT), remote monitoring and control is increasingly becoming popular with a wide range of applications from emergency response in remote regions to monitoring of environmental parameters. Mesh networks are being employed to alleviate a number of issues associated with single-hop communication such as low area coverage, reliability, range and high energy consumption. Low-power Wireless Personal Area Networks (LoWPANs) are being used to help realize and permeate the applicability of IoT. In this paper, we present the design and test of IEEE 802.15.4-compliant smart IoT nodes with multi-hop routing. We first discuss the features of the software stack and design choices in hardware that resulted in high RF output power and then present field test results of different baseline network topologies in both rural and urban settings to demonstrate the deployability and scalability of our solution.
How can manufacturers or service companies provide better services with connected products, without having acquired a powerful IT infrastructure nor the competences for software development?
Today companies can appeal to a relocated-IT-infrastructure provider, which is called Cloud.
Consequently, they do not have to manage and take care of the safety/security aspect, the updates and the breakdown of the infrastructure internally, as those are all managed by the provider.
It is possible to outsource the development of the software of the connected product to an external company. However, the question now is how fast this company can juggle from one Cloud to another in order to fulfil their clients wishes?
neverMind offers a solution based on a multi-protocols-platform linking the different connected products to a multitude of Clouds without having to redesign the whole communication stack/building block for each change in the Cloud-solution. This is the object of my thesis.
The development follows the V-Model, the first steps to understand the complexity of the project were the realisation of the product technical and architectural specifications. The last step before the Implementation was to design in details the progress and the process of every parts of the platform.
The outcome of the requirements analysis led me to divide the project in two parts:
• a “General Interface” acting as a gateway between the Client-application and “Cloud-modules”
• the “Cloud-modules” themselves.
So far, the specifications are drown up; the General Interface and a client example are coded, as well as a first Cloud-module template.
Lithium-ion batteries show a complex thermo-electrochemical performance and aging behavior. This paper presents a modeling and simulation framework that is able to describe both multi-scale heat and mass transport and complex electrochemical reaction mechanisms. The transport model is based on a 1D + 1D + 1D (pseudo-3D or P3D) multi-scale approach for intra-particle lithium diffusion, electrode-pair mass and charge transport, and cell-level heat transport, coupled via boundary conditions and homogenization approaches. The electrochemistry model is based on the use of the open-source chemical kinetics code CANTERA, allowing flexible multi-phase electrochemistry to describe both main and side reactions such as SEI formation. A model of gas-phase pressure buildup inside the cell upon aging is added. We parameterize the model to reflect the performance and aging behavior of a lithium iron phosphate (LiFePO4, LFP)/graphite (LiC6) 26650 battery cell. Performance (0.1–10 C discharge/charge at 25, 40 and 60°C) and calendaric aging experimental data (500 days at 30°C and 45°C and different SOC) from literature can be successfully reproduced. The predicted internal cell states (concentrations, potential, temperature, pressure, internal resistances) are shown and discussed. The model is able to capture the nonlinear feedback between performance, aging, and temperature.
Phosphate-based inorganic–organic hybrid nanoparticles (IOH-NPs) with the general composition [M]2+[Rfunction(O)PO3]2– (M = ZrO, Mg2O; R = functional organic group) show multipurpose and multifunctional properties. If [Rfunction(O)PO3]2– is a fluorescent dye anion ([RdyeOPO3]2–), the IOH-NPs show blue, green, red, and near-infrared fluorescence. This is shown for [ZrO]2+[PUP]2–, [ZrO]2+[MFP]2–, [ZrO]2+[RRP]2–, and [ZrO]2+[DUT]2– (PUP = phenylumbelliferon phosphate, MFP = methylfluorescein phosphate, RRP = resorufin phosphate, DUT = Dyomics-647 uridine triphosphate). With pharmaceutical agents as functional anions ([RdrugOPO3]2–), drug transport and release of anti-inflammatory ([ZrO]2+[BMP]2–) and antitumor agents ([ZrO]2+[FdUMP]2–) with an up to 80% load of active drug is possible (BMP = betamethason phosphate, FdUMP = 5′-fluoro-2′-deoxyuridine 5′-monophosphate). A combination of fluorescent dye and drug anions is possible as well and shown for [ZrO]2+[BMP]2–0.996[DUT]2–0.004. Merging of functional anions, in general, results in [ZrO]2+([RdrugOPO3]1–x[RdyeOPO3]x)2– nanoparticles and is highly relevant for theranostics. Amine-based functional anions in [MgO]2+[RaminePO3]2– IOH-NPs, finally, show CO2 sorption (up to 180 mg g–1) and can be used for CO2/N2 separation (selectivity up to α = 23). This includes aminomethyl phosphonate [AMP]2–, 1-aminoethyl phosphonate [1AEP]2–, 2-aminoethyl phosphonate [2AEP]2–, aminopropyl phosphonate [APP]2–, and aminobutyl phosphonate [ABP]2–. All [M]2+[Rfunction(O)PO3]2– IOH-NPs are prepared via noncomplex synthesis in water, which facilitates practical handling and which is optimal for biomedical application. In sum, all IOH-NPs have very similar chemical compositions but can address a variety of different functions, including fluorescence, drug delivery, and CO2 sorption.
The central purpose of this paper is to present a novel framework supporting the specification, the implementation and retrieval of media streaming services. It provides an integrated service development environment comprising of a streaming service model, a service specification language and several implementation and retrieval tools. Our approach is based on a clear separation of a streaming service specification, and its implementation by a distributed application and can be used for different streaming paradigms, e.g. push and pull services.
Due to the increasing aging of the population, the number of elderly people requiring care is growing in most European countries. However, the number of caregivers working in nursing homes and on daily care services is declining in countries like Germany or Italy. This limits the time for interpersonal communication. Furthermore, as a result of the Covid-19 pandemic, social distancing during contact restrictions became more important, causing an additional reduction of personal interaction. This social isolation can strongly increase emotional stress. Robotic assistance could contribute to addressing this challenge on three levels: (1) supporting caregivers to respond individually to the needs of patients and residents in nursing homes; (2) observing patients’ health and emotional state; (3) complying with high hygiene standards and minimizing human contact if required. To further the research on emotional aspects and the acceptance of robotic assistance in care, we conducted two studies where elderly participants interacted with the social robot Misa. Facial expression and voice analysis were used to identify and measure the emotional state of the participants during the interaction. While interpersonal contact plays a major role in elderly care, the findings reveal that robotic assistance generates added value for both caregivers and patients and that they show emotions while interacting with them.
The energy system of the future will transform from the current centralised fossil based to a decentralised, clean, highly efficient, and intelligent network. This transformation will require innovative technologies and ideas like trigeneration and the crowd energy concept to pave the way ahead. Even though trigeneration systems are extremely energy efficient and can play a vital role in the energy system, turning around their deployment is hindered by various barriers. These barriers are theoretically analysed in a multiperspective approach and the role decentralised trigeneration systems can play in the crowd energy concept is highlighted. It is derived from an initial literature research that a multiperspective (technological, energy-economic, and user) analysis is necessary for realising the potential of trigeneration systems in a decentralised grid. And to experimentally quantify these issues we are setting up a microscale trigeneration lab at our institute and the motivation for this lab is also briefly introduced.