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Die gefährliche Wirkung von Kerben auf Konstruktionsteile bei Dauerbeanspruchungen ist dem Konstrukteur bekannt. Trotzdem sind viele in der Praxis beobachteten Schadensbilder an Passverzahnungen fast durchweg auf nicht genügend berücksichtigte Kerbwirkung infolge der konstruktiv bedingten Mehrfachkerben zurückzuführen. Die hohen Anforderungen vor allem an Drehmoment übertragende und hochbeanspruchte Konstruktionsteile zwingen uns, der Frage der Kerbwirkungen sowie Maßnahmen zu deren Milderung erhöhte Aufmerksamkeit zu widmen. Der vorliegende Beitrag beschreibt erste Untersuchungsergebnisse mit der Finite-Elemente-Methode (FEM) zur Ermittlung der Kerbwirkung an den Übergangsstellen für die nach DIN 5480 genormten Passverzahnungen mit freiem Auslauf bei Torsion und Biegung. Die rechnerisch abgeschätzten Form- und Kerbwirkungszahlen an Passverzahnungen werden mit experimentellen Kerbwirkungszahlen aus den Ermüdungsversuchen verglichen. Das Ziel ist es, den Stand der Technik hinsichtlich der Berechnung der Tragfähigkeit und Ermüdungsfestigkeit bei Passverzahnungen weiterzuentwickeln und die neu gewonnenen Form- und Kerbwirkungszahlen in die Berechnungsvorschriften DIN 743 und DIN 5466 einzubinden.
The Internet of Things (IoT) application has becoming progressively in-demand, most notably for the embedded devices (ED). However, each device has its own difference in computational capabilities, memory usage, and energy resources in connecting to the Internet by using Wireless Sensor Networks (WSNs). In order for this to be achievable, the WSNs that form the bulk of the IoT implementation requires a new set of technologies and protocol that would have a defined area, in which it addresses. Thus, IPv6 Low Power Area Network (6LoWPAN) was designed by the Internet Engineering Task Force (IETF) as a standard network for ED. Nevertheless, the communication between ED and 6LoWPAN requires appropriate routing protocols for it to achieve the efficient Quality of Service (QoS). Among the protocols of 6LoWPAN network, RPL is considered to be the best protocol, however its Energy Consumption (EC) and Routing Overhead (RO) is considerably high when it is implemented in a large network. Therefore, this paper would propose the HRPL to enchance the RPL protocol in reducing the EC and RO. In this study, the researchers would present the performance of RPL and HRPL in terms of EC, Control traffic Overhead (CTO) and latency based on the simulation of the 6LoWPAN network in fixed environment using COOJA simulator. The results show HRPL protocol achieves better performance in all the tested topology in terms of EC and CTO. However, the latency of HRPL only improves in chain topology compared with RPL. We found that further research is required to study the relationship between the latency and the load of packet transmission in order to optimize the EC usage.
In the last decade, IPv6 over Low power Wireless Personal Area Networks, also known as 6LoWPAN, has well evolved as a primary contender for short range wireless communication and holds the promise of an Internet of Things, which is completely based on the Internet Protocol. In the meantime, various 6LoWPAN implementations are available, be it open source or commercial. One of these implementations, which was developed by the authors' team, was tested on an Automated Physical Testbed for Wireless Systems at the Laboratory Embedded Systems and Communication Electronics of Offenburg University of Applied Sciences, which allows the flexible setup and full control of arbitrary topologies. It also supports time-varying topologies and thus helps to measure performance of the RPL implementation. The results of the measurements show a very good stability and short-term and long-term performance also under dynamic conditions. In addition, it can be proven that the performance predictions from other papers are consistent with real-life implementations.
The demand of wireless solutions in industrial applications increases since the early nineties. This trend is not only ongoing, it is further pushed by developments in the area of software stacks like the latest Bluetooth Low Energy Stack. It is also pushed by new chip-designs and powerful and highly integrated electronic hardware. The acceptance of wireless technologies as a possible solution for industrial applications, has overcome the entry barrier [1]. The first step to see wireless as standard for many industrial applications is almost accomplished. Nevertheless there is nearly none acceptance of wireless technology for Safety applications. One highly challenging and demanding requirement is still unsolved: The aspect safety and robustness. Those topics have been addressed in many cases but always in a similar manner. WirelessHART as an example addresses this topic with redundant so called multiple propagation paths and frequency hopping to handle with interferences and loss of network participants. So far the pure peer to peer link is rarely investigated and there are less safety solutions available. One product called LoRa™ can be seen as one possible solution to address this lack of safety within wireless links. This paper focuses on the safety performance evaluation of a modem-chip-design. The use of diverse and redundant wireless technologies like LoRa can lead to an increase acceptance of wireless in safety applications. Many measurements in real industrial application have been carried out to be able to benchmark the new chip in terms of the safety aspects. The content of this research results can help to raise the level of confidence in wireless. In this paper, the term “safety” is used for data transmission reliability.
The Paper presents the design and development of a blended learning concept for an engineering course in the field of color representation and display technologies. A suitable learning environment is crucial for the success of the teaching scenario. A mixture of theoretical lectures and hands-on activities with practical applications and experiments, combined with the advantages of modern digital media is the main topic of the paper. Blended learning describes the didactical change of attendance periods and online periods. The e-learning environment for the online period is designed toward an easy access and interaction. Present digital media extends the established teaching scenarios and enables the presentation of videos, animations and augmented reality (AR). Visualizations are effective tools to impart learning contents with lasting effect. The preparation and evaluation of the theoretical lectures and the hands-on activities are stimulated and affects positively the attendance periods. The tasks and experiments require the students to work independently and to develop individual solution strategies. This engages and motivates the students, deepens the knowledge. The authors will present their experience with the implemented blended learning scenario in this field of optics and photonics. All aspects of the learning environment will be introduced.
Due to a controversial enrollment policy in most engineering programs at German Universities of Applied Sciences (UAS), many freshmen show very low school grades in key subjects like Math and Physics. Nevertheless they expect to be entertained in the lectures and get demotivated easily. Despite initial reservations, a cheer-and-challenge approach was developed for teaching Mechanics to freshmen having very diverse school grades. When tested, it showed astonishing results.
The idea of this game is to use a flashcard system to create a short story in a foreign language. The story is developed by a group of people by exchanging sentences via a flashcard system. This way, people can learn from each other without fear of making mistakes because the group members are anonymous.
Seismic data has often missing traces due to technical acquisition or economical constraints. A compete dataset is crucial in several processing and inversion techniques. Deep learning algorithms, based on convolutional neural networks (CNNs), have shown alternative solutions that overcome limitation of traditional interpolation methods e.g. data regularity, linearity assumption, etc. There are two different paradigms of CNN methods for seismic interpolation. The first one, so-called deep prior interpolation (DPI), trains a CNN to map random noise to a complete seismic image using only the decimated image itself. The second one, referred as standard deep learning method, trains a CNN to map a decimated seismic image into a complete one using a dataset of complete and artificially decimated images. Within this research, we systematically compare the performance of both methods for different quantities of regular and irregular missing traces using 4 datasets. We evaluate the results of both methods using 5 well-known metrics. We found that DPI method performs better than the standard method if the percentage of missing traces is low (10%) and otherwise if the level of decimation is high (50%).