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We present the novel concept of a combined drilling and melting probe for subsurface ice research. This probe, named “IceMole”, is currently developed, built, and tested at the FH Aachen University of Applied Sciences’ Astronautical Laboratory. Here, we describe its first prototype design and report the results of its field tests on the Swiss Morteratsch glacier. Although the IceMole design is currently adapted to terrestrial glaciers and ice shields, it may later be modified for the subsurface in-situ investigation of extraterrestrial ice, e.g., on Mars, Europa, and Enceladus. If life exists on those bodies, it may be present in the ice (as life can also be found in the deep ice of Earth).
Evaluation of fragility curves for a three-storey-reinforced-concrete mock-up of SMART 2013 project
(2016)
Architecture for platform- and hardware-independent mesh networks : how to unify the channels
(2013)
This paper will prove that mesh networks among different platforms and hardware channels can help to channel valuable information even if public telecommunication infrastructure is not available due to arbitrary reasons. Therefore, results of a simulation for mesh networks on mass events will be provided, followed by the developed architecture and an outlook on future research. The developed architecture is currently being implemented and field tested on mass events.
Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures.
The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.
The paper deals with the development of the probabilistic approach to the assessment of risk due to lightning. Sources of damage, types of damage and types of loss are defined and, accordingly, the procedure for risk analysis and the way of assessment of different risk components is proposed. The way to evaluate the influence of different protection measures (lightning protection system; shielding of structure, cables and equipment; routing of internal wiring; surge protective device) in reducing such probabilities is considered. The paper has been prepared within the framework of the activity of IEC TC81-WG9/CLC TC81-WG4 directed to prepare the draft IEC 62305-2 Risk Management, in cooperation with the Secretary of IEC/CLC TC81.
In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
Funktionsprinzip Emissionsrechtehandel, Betroffene Anlagen und Branchen, Erstverteilung der Emissionsrechte, Bereits erbrachte Emissionsreduktionen (early actions), Ausstieg von betroffenen Unternehmen (opt-out), Teilnahme von nicht betroffenen Unternehmen, Einsatz von Biobrennstoffen, Erfassung und Dokumentation der Emissionen
Ausgangslage, Funktionsprinzip des virtuellen Kraftwerkes, Energiemanagementsysteme (EMS), Einsatzgebiete, Anlagesysteme eines VKW's, Einsatzbereich der verschiedenen dezentralen Energieanlagen, Vorteile des virtuellen Kraftwerkes, Auswirkungen auf das elektrische Netz, Wirtschaftliche Aspekte, Beispielprojekte
A melting probe equipped with autofluorescence-based detection system combined with a light scattering unit, and, optionally, with a microarray chip would be ideally suited to probe icy environments like Europa’s ice layer as well as the polar ice layers of Earth and Mars for recent and extinct live.
Mechanical stimulation of the cells resulted in evident changes in the cell morphology, protein composition and gene expression. Microscopically, additional formation of stress fibers accompanied by cell re-arrangements in a monolayer was observed. Also, significant activation of p53 gene was revealed as compared to control. Interestingly, the use of CellTech membrane coating induced cell death after mechanical stress had been applied. Such an effect was not detected when fibronectin had been used as an adhesion substrate.
Recently, SHARP corporation has developed the world’s first “Plasma Cluster Ions (PCI)” air purification technology, which uses plasma discharge to generate cluster ions. The new plasma cluster device releases into the air positive and negative ions, which are harmless to humans and are able to decompose and deactivate airborne substances by chemical reactions. A lot of phenomenological tests of the PCI air purification technology on microbial cells have been conducted. And, in most cases, it has been shown that PCI demonstrate strongly pronounced killing effect. Although, the particular mechanisms of PCI action are still not evident. We studied variations in resistance to PCI among gram-positive airborne microorganisms, as well as some dose-dependent, spatial, cultural and biochemical properties of PCI action in respect of Staphylococcus spp, Enterococcus spp, Micrococcus spp.
Recently, the SHARP Corporation, Japan, has developed the world’s first "Plasma Cluster Ions (PCI)" air purification technology using plasma discharge to generate cluster ions. The new plasma cluster device releases positive and negative ions into the air, which are able to decompose and deactivate harmful airborne substances by chemical reactions. Because cluster ions consist of positive and negative ions that normally exist in the natural world, they are completely harmless and safe to humans. The amount of ozone generated by cluster ions is less than 0.01 ppm, which is significantly less than the 0.05-ppm standard for industrial operations and consumer electronics. This amount, thus, has no harming effects whatsoever on the human body. But particular properties and chemical processes in PCI treatment are still under study. It has been shown that PCI in most cases show strongly pronounced irreversible killing effects in respect of airborne microflora due to free-radical induced reactions and can be considered as a potent technology to disinfect both home, medical and industrial appliances.
Summary and Conclusions PCIs were clearly effective in terms of their antibacterial effects with the strains tested. This efficacy increased with the time the bacteries were exposed to PCIs. The bactericidal action has proved to be irreversible. PCIs were significantly less effective in shadowed areas. PCI exposure caused multiple protein damages as observed in SDS PAGE studies. There was no single but multiple molecular mechanism causing the bacterial death.
Recently, SHARP corporation has developed the world’s first "Plasma Cluster Ions® (PCI)" air purification technology, which uses plasma discharge to generate cluster ions. The new Plasma Cluster Device releases positive and negative ions into the air, which are harmless to humans and are able to decompose and deactivate airborne substances by chemical reactions. In the past, phenomenological tests on the efficacy of the PCI air purification technology on microbial cells have been conducted. In most cases, it has been shown that PCI demonstrated strongly pronounced killing effects on microorganisms. However, the particular mechanisms of PCI action still have to be uncovered.
Composite improvement of textile reinforced concrete by polymeric impregnation of the textiles
(2006)
Application of polymers in textile reinforced concrete : from the interface to construction elements
(2006)
With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Competence Developing Games (CDGs) are a new concept of how to think about games with serious intentions. In order to emphasize on this topic, a new framework has been developed. It basically relies on learning and motivation theories. This ‘motivational Competence Developing Game Framework’ demonstrates how it is possible to use these theories in a CDG development process. The theoretical derivation and use of the framework is explained in this paper.
Untersuchungen zur Tragfähigkeit und Steifigkeit eines neuartigen Wandelements in Holzbauweisen
(2018)
We present first results from a newly developed monitoring station for a closed loop geothermal heat pump test installation at our campus, consisting of helix coils and plate heat exchangers, as well as an ice-store system. There are more than 40 temperature sensors and several soil moisture content sensors distributed around the system, allowing a detailed monitoring under different operating conditions.In the view of the modern development of renewable energies along with the newly concepts known as Internet of Things and Industry 4.0 (high-tech strategy from the German government), we created a user-friendly web application, which will connect the things (sensors) with the open network (www). Besides other advantages, this allows a continuous remote monitoring of the data from the numerous sensors at an arbitrary sampling rate.Based on the recorded data, we will also present first results from numerical simulations, taking into account all relevant heat transport processes.The aim is to improve the understanding of these processes and their influence on the thermal behavior of shallow geothermal systems in the unsaturated zone. This will in turn facilitate the prediction of the performance of these systems and therefore yield an improvement in their dimensioning when designing a specific shallow geothermal installation.
Plasma-Spritzen
(1991)
Thematisch widmet sich das Projekt Coolplan- AIR der Fortentwicklung und Feldvalidierung eines Berechnungs- und Auslegungstools zur energieeffizienten Kühlung von Gebäuden mit luftgestützten Systemen. Neben dem Aufbau und der Weiterentwicklung von Simulationsmodellen erfolgen Vermessungen der Gesamtsysteme anhand von Praxisanlagen im Feld. Der Schwerpunkt des Projekts liegt auf der Vermessung, Simulation und Integration rein luftgestützter Kühltechnologien. Im Bereich der Kälteerzeugung wurden Luft‐ Luft‐ Wärmepumpen, Anlagen zur adiabaten Kühlung bzw. offene Kühltürme und VRF‐ Multisplit‐ Systeme (Variable Refrigerant Flow) im Feld bzw. auf dem Teststand der HSD vermessen. Die Komponentenmodelle werden in die Matlab/Simulink‐ Toolbox CARNOT integriert und anschließend auf Basis der zuvor erhaltenen Messdaten validiert.
Einerseits erlauben die Messungen das Betriebsverhalten von Anlagenkomponenten zu analysieren. Andererseits soll mit der Vermessung im Feld geprüft werden, inwieweit die Simulationsmodelle, welche im Vorgängerprojekt aus Prüfstandmessungen entwickelt wurden, auch für größere Geräteleistungen Gültigkeit besitzen. Die entwickelten und implementierten Systeme, bestehend aus verschiedensten Anlagenmodellen und Regelungskomponenten, werden geprüft und dahingehend qualifiziert, dass sie in Standard- Auslegungstools zuverlässig verwendet werden können.
Zusätzlich wird ein energetisches Monitoring eines Hörsaalgebäudes am Campus Jülich durchgeführt, das u. a. zur Validierung der Kühllastberechnungen in gängigen Simulationsmodelle genutzt werden kann.
New coupled finite-infinite element approach for wave propagation simulation of unbounded soil media
(2014)
Digital start-ups are perceived as an engine for innovation and job promotor. While success factors for non-IT start-ups have already been extensively researched, this study sheds light on digital entrepreneurs, whose business model relies primarily on services based on digital technologies. Applying the Grounded Theory method, we identify relevant environmental success factors for digital entrepreneurs. The study’s research contribution is threefold. First, we provide 16 relevant and less relevant environmental success factors, which enables a comparison with prior identified factors. We found out that several prior environmental success factors, such as accessibility to transportation or the availability of land and facilities are less relevant for a digital entrepreneur. Second, we derive and discuss hypotheses for the influence of these factors on digital start-up success. Third, we present a theoretical model that lays the foundation for explaining the environmental influence on digital
entrepreneurship success.
Process mining gets more and more attention even outside large enterprises and can be a major benefit for small and medium sized enterprises (SMEs) to gain competitive advantages. Applying process mining is challenging, particularly for SMEs because they have less resources and process maturity. So far, IS researchers analyzed process mining challenges with a focus on larger companies. This paper investigates the application of process mining by means of a case study and sheds light into the particular challenges of an IT SME. The results reveal 13 SME process mining challenges and seven guidelines to address them. In this way, the paper contributes to the understanding of process mining application in SME and shows similarities and differences to larger companies.
Gamification and gamified information systems (GIS) apply video game elements to encourage the work on boring and everyday tasks. Meanwhile, several research works provide evidence that gamification increases efficiency and effectivity of such tasks. The paper at hand investigates the health care sector, which is challenged with cost pressure and suffers in process efficiency. We hypothesize that GIS may improve the efficiency and quality of care processes. By applying an interview-based content analysis, the paper at hand evaluates gamification elements in an assisted living environment and provides three research contributions. First, insights into relevant GIS affordances and application examples for assisted living facilities are given. Second, assisted living experts evaluate GIS design guidelines. Both the relevant affordances and design principles comprise a basis for the development of a GIS for social workers in assisted living facilities. Third, potential adoption barriers and design guidelines for GIS in assisted living are presented.
A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived.
Generating synthetic LiDAR point cloud data for object detection using the Unreal Game Engine
(2024)
Object detection based on artificial intelligence is ubiquitous in today’s computer vision research and application. The training of the neural networks for object detection requires large and high-quality datasets. Besides datasets based on image data, datasets derived from point clouds offer several advantages. However, training datasets are sparse and their generation requires a lot of effort, especially in industrial domains. A solution to this issue offers the generation of synthetic point cloud data. Based on the design science research method, the work at hand proposes an approach and its instantiation for generating synthetic point cloud data based on the Unreal Engine. The point cloud quality is evaluated by comparing the synthetic cloud to a real-world point cloud. Within a practical example the applicability of the Unreal Game engine for synthetic point cloud generation could be successfully demonstrated.
Integrated voice assistants (IVA) receive more and more attention and are widespread for entertainment use cases, such as radio hearing or web searches. At the same time, the health care segment suffers in process inefficiency and missing staff, whereas the usage of IVA has the potential to improve caring processes and patient satisfaction. By applying a design science approach and based on a qualitative study, we identify IVA requirements, barriers and design guidelines for the health care sector. The results reveal three important IVA functions: the ability to set appointments with care service staff, the documentation of health history and the communication with service staff. Integration, system stability and volume control are the most important nonfunctional requirements. Based on the interview results and project experiences, six design and implementation guidelines are derived.
The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores.
Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.
Laser-based Additive Manufacturing (AM) processes for the use of metals out of the powder bed have been investigated profusely and are prevalent in industry. Although there is a broad field of application, Laser Powder Bed Fusion (LPBF), also known as Selective Laser Melting (SLM) of glass is not fully developed yet. The material properties of glass are significantly different from the investigated metallic material for LPBF so far. As such, the process cannot be transferred, and the parameter limits and the process sequence must be redefined for glass. Starting with the characterization of glass powders, a parameter field is initially confined to investigate the process parameter of different glass powder using LPBFprocess. A feasibility study is carried out to process borosilicate glass powder. The effects of process parameters on the dimensional accuracy of fabricated parts out of borosilicate and hints for the post-processing are analysed and presented in this paper.
In this paper, we present the structure, the simulation the operation of a multi-stage, hybrid solar desalination system (MSDH), powered by thermal and photovoltaic (PV) (MSDH) energy. The MSDH system consists of a lower basin, eight horizontal stages, a field of four flat thermal collectors with a total area of 8.4 m2, 3 Kw PV panels and solar batteries. During the day the system is heated by thermal energy, and at night by heating resistors, powered by solar batteries. These batteries are charged by the photovoltaic panels during the day. More specifically, during the day and at night, we analyse the temperature of the stages and the production of distilled water according to the solar irradiation intensity and the electric heating power, supplied by the solar batteries. The simulations were carried out in the meteorological conditions of the winter month (February 2020), presenting intensities of irradiance and ambient temperature reaching 824 W/m2 and 23 °C respectively. The results obtained show that during the day the system is heated by the thermal collectors, the temperature of the stages and the quantity of water produced reach 80 °C and 30 Kg respectively. At night, from 6p.m. the system is heated by the electric energy stored in the batteries, the temperature of the stages and the quantity of water produced reach respectively 90 °C and 104 Kg for an electric heating power of 2 Kw. Moreover, when the electric power varies from 1 Kw to 3 Kw the quantity of water produced varies from 92 Kg to 134 Kg. The analysis of these results and their comparison with conventional solar thermal desalination systems shows a clear improvement both in the heating of the stages, by 10%, and in the quantity of water produced by a factor of 3.
Design and Development of a Hot S-Parameter Measurement System for Plasma and Magnetron Applications
(2020)
This paper presents the design, development and calibration procedures of a novel hot S-parameter measurement system for plasma and magnetron applications with power level up to 6 kW. Based on a vector network analyzer, a power amplifier and two directional couplers, the input matching hotS 11 and transmission hotS 21 of the device under test are measured at 2.45 GHz center frequency and 300MHz bandwidth, while the device is driven by the magnetron. This measurement system opens a new horizon to develop many new industrial applications such as microwave plasma jets, dryer systems, dryers and so forth. Furthermore, the developing, controlling and monitoring a 2kW 2.45GHz plasma jet and a dryer system using the measurement system are presented and explained.
Tool supported requirements analysis for the user centered development of mobile enterprise software
(2008)
A user centered development method has proved satisfactory for the development of mobile enterprise software. To make use of this method, detailed information about the user and the place where the user interacts with his mobile device is required. This article describes how both can be modeled by a stereotypical and conceptual extended UML extension. Finally, a software tool is presented that supports the developed UML extension.
This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images.
In der Vergangenheit basierten große Systemintegrationsprojekte in der Regel auf Individualentwicklungen für einzelne Kunden. Getrieben durch Kostendruck steigt aber der Bedarf nach standardisierten Lösungen, die gleichzeitig die individuellen Anforderungen des jeweiligen Umfelds berücksichtigen. T-Systems GEI GmbH wird beiden Anforderungen mit Produktkerneln gerecht. Neben den technischen Aspekten der Kernelentwicklung spielen besonders organisatorische Aspekte eine Rolle, um Kernel effizient und qualitativ hochwertig zu entwickeln, ohne deren Funktionalitäten ins Uferlose wachsen zu lassen. Umgesetzt hat T-Systems dieses Konzept für Flughafeninformationssysteme. Damit kann dem wachsenden Bedarf der Flughafenbetreiber nach einer effizienten und kostengünstigen Softwarelösung zur Unterstützung Ihrer Geschäftsprozesse entsprochen werden.
This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand.
Der Erfolg eines Softwarenentwicklungsprojektes insbesondere eines Systemintegrationsprojektes wird mit der Erfüllung des „Teufelsdreiecks“, „In-Time“, „In-Budget“, „In-Quality“ gemessen. Hierzu ist die Kenntnis der Software- und Prozessqualität essenziell, um die Einhaltung der Qualitätskriterien festzustellen, aber auch, um eine Vorhersage hinsichtlich Termin- und Budgettreue zu treffen. Zu diesem Zweck wurde in der T-Systems Systems Integration ein System aus verschiedenen Key Performance Indikatoren entworfen und in der Organisation implementiert, das genau das leistet und die Kriterien für CMMI Level 3 erfüllt.
In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
This paper introduces a hardware setup to measure efficiency maps of low-power electric motors and their associated inverters. Here, the power of the device under test (DUT) ranges from some Watts to a few hundred Watts. The torque and speed of the DUT are measured independent of voltage and current in multiple load points. A Matlab-based software approach in combination with an open Texas-Instruments (TI) hardware setup ensures flexibility. Exemplarily, the efficiency field of a Permanent Magnet Synchronous Machine (PMSM) is measured to proof the concept. Brushless-DC (BLDC) motors can be tested as well. The nomenclature in this paper is based on the new European standard DIN EN 50598. Special attention is paid to the calculation of the measurement error.
Electromicrobial engineering is an emerging, highly interdisciplinary research area linking bioprocesses with electrochemistry. In this work, microbial electrosynthesis (MES) of biobutanol is carried out during acetone-butanol-ethanol (ABE) fermentations with Clostridium acetobutylicum. A constant electric potential of −600mV (vs. Ag/AgCl) with simultaneous addition of the soluble redox mediator neutral red is used in order to study the electron transfer between the working electrode and the bacterial cells. The results show an earlier initiation of solvent production for all fermentations with applied potential compared to the conventional ABE fermentation. The f inal butanol concentration can be more than doubled by the application of a negative potential combined with addition of neutral red. Moreover a higher biofilm formation on the working electrode compared to control cultivations has been observed. In contrast to previous studies, our results also indicate that direct electron transfer (DET) might be possible with C. acetobutylicum. The presented results make microbial butanol production economically attractive and therefore support the development of sustainable production processes in the chemical industry aspired by the “Centre for resource-efficient chemistry and raw material change” as well as the the project “NanoKat” working on nanostructured catalysts in Kaiserslautern.
Mit freundlicher Genehmigung der Autoren und des Oldenbourg Industrieverlags https://www.oldenbourg-industrieverlag.de/de/9783835633223-33223 erschienen als Beitrag im Tagungsband zur AALE-Tagung 2012. 9. Fachkonferenz 4.-5. Mai 2012, Aachen, Fachhochschule. ISBN 9783835633223 S 2-1 S. 37-46 Original-Abstract der Autoren: "Dieser Artikel beschreibt eine universelle Programmierschnittstelle zur Entwicklung von Motion-Logic Applikationen für industrielle Motion-Controller. Sie ermöglicht die Entwicklung von Software mit modernen Hochsprachen, wie C/C++. Visual Basic, C#, Java, Objective-Cund visuellen Programmiersprachen, wie LabVIEW in Koexistenz mit klassischen Programmiersprachen für speicherprogrammierbare Steuerungen nach IEC 61131-3. Daraus ergeben sich neue Möglichkeiten industrielle Antriebs- und Steuerungssysteme mit ihrem IT-Umfeld zu verbinden."
Mit freundlicher Genehmigung der Autoren und des Oldenbourg Industrieverlags https://www.oldenbourg-industrieverlag.de/de/9783835633223-33223 erschienen als Beitrag im Tagungsband zur AALE-Tagung 2012. 9. Fachkonferenz 4.-5. Mai 2012, Aachen, Fachhochschule. ISBN 9783835633223 S 6-2. S. 165-174 Zusammenfassung der Autoren: "Abschließend kann festgehalten werden, dass die gesamten durchgeführten Überlegungen von den Messergebnissen der Inbetriebnahme positiv bestätigt werden. Es wird durch diese Topologie eine maximale Systemverfügbarkeit garantiert und die Zellen werden optimal betrieben. Ein Blick in die Zukunft für dieses Projekt zeigt viele Erweiterungs- und Optimierungsaufgaben. So muss der DC/DC-Wandler für einen bidirektionalen Betrieb erweitert werden, um einen Rekuperationsbetrieb zu gewährleisten bzw. die Zellen laden zu können. Dadurch können gleichzeitig die Gleichrichterdioden im Sekundärleistungsteil durch IGBTs oder MOSFETs ersetzt werden. Die voll funktionsfähige Version des DC/DC-Wandlers könnte höchstwahrscheinlich direkt auf die Anschlusspole der Zelle montiert werden, wodurch das Gewicht gesenkt wird. Durch die verringerte Verlustleistung in den Zuleitungen könnte der Wirkungsgrad noch einmal gesteigert werden.
This article describes the functionality of a MATLAB® library that can be used to develop motion-logic applications in MATLAB programming language for industrial drive and control systems using the well known sercos automation bus. Therewith MATLAB's functionality is extended to designing automation applications from single axis machines up to multi-kinematic robots.
Dipl.-Ing. Ralf Engels - DHI Wasser und Umwelt GmbH, Syke. 24 S. (S. 70-93) Beitrag zum 1. Aachener Softwaretag in der Wasserwirtschaft <1,2007, Aachen> Einleitung [des Autors] Die hydrodynamische Kanalnetzmodellierung ist ein Standardwerkzeug für die Bemessung von Kanalnetzen. Neben der Berechnung der hydrologischen und hydraulischen Gegebenheiten in einem städtischen Einzugsgebiet gehören auch weiterführende Technologien mittlerweile zum Standard. So können alle steuerbaren Elemente eines Kanalnetzes dynamisch so optimiert werden, dass die Leistungsfähigkeit des Kanalnetzes zusätzlich gesteigert werden kann. Automatische Werkzeuge zur dynamischen hydraulischen Schmutzfrachtberechnung ermöglichen die Erweiterung der Steuerung – insbesondere von Entlastungsanlagen – im Hinblick auf die entlasteten Schmutzfrachten und geben darüber hinaus detaillierte Informationen für den Betrieb der Kläranlage. Weiterführende biologische Prozessmodellierungen ergänzen dieses Themenfeld. GIS Werkzeuge können bei der räumlich differenzierten Modellierung von Kanalnetzen wertvolle Dienste leisten. Die detaillierte Betrachtung einzelner Haltungsflächen in ihrem räumlichen Zusammenhang ist damit ebenso möglich wie eine komplette Verwaltung aller für die Kanalnetzmodellierung notwendigen Daten in einem übersichtlichen grafischen Menü. Die Grenzen der Kanalnetzmodellierung lagen in früheren Zeiten an dessen Rand. Detaillierte Informationen über die Wege des Wassers auf der Geländeoberfläche, an der Schnittstelle zu Vorflutern und in der Interaktion mit Grundwasser waren bisher nicht modelltechnisch bewertbar. Eine dynamische Kopplung verschiedener Modelle zur Darstellung aller relevanten hydraulischen Prozesse ermöglicht eine integrative Betrachtung aller möglichen Wege, die das Wasser in der Stadt nehmen kann (Mark & Djordjevic, 2006). Dieser Beitrag präsentiert den Stand der Technik für die integrierte Modellierung städtischer Überschwemmungen mit Hilfe der Modellkopplung von Oberflächenmodellen und Kanalnetzmodellen.
A new method for improved autoclave loading within the restrictive framework of helicopter manufacturing is proposed. It is derived from experimental and numerical studies of the curing process and aims at optimizing tooling positions in the autoclave for fast and homogeneous heat-up. The mold positioning is based on two sets of information. The thermal properties of the molds, which can be determined via semi-empirical thermal simulation. The second information is a previously determined distribution of heat transfer coefficients inside the autoclave. Finally, an experimental proof of concept is performed to show a cycle time reduction of up to 31% using the proposed methodology.