New simple method for the assessment of masonry arch bridges

The paper presents an approximation method for the assessment of the load carrying capacity of masonry arch railway bridges. The method is a simple semi-empirical tool for the initial level assessment that is considered to serve as a first sieve and provides conservative values for the load-carrying capacity and permissible axle load of single-span arches. The proposed method is based on results obtained by the RING 2.0 masonry arch bridge analysis software. The method uses a closed mathematical formula to calculate the carrying capacity and its input parameters can easily be determined by simple site inspections or using data from bridge files

Degradation of arouser by endosomal microautophagy is essential for adaptation to starvation in Drosophila

Hunger drives food-seeking behaviour and controls adaptation of organisms to nutrient availability and energy stores. Lipids constitute an essential source of energy in the cell that can be mobilised during fasting by autophagy. Selective degradation of proteins by autophagy is made possible essentially by the presence of LIR and KFERQ-like motifs. Using in silico screening of Drosophila proteins that contain KFERQ-like motifs, we identified and characterized the adaptor protein Arouser, which functions to regulate fat storage and mobilisation and is essential during periods of food deprivation. We show that hypomorphic arouser mutants are not satiated, are more sensitive to food deprivation, and are more aggressive, suggesting an essential role for Arouser in the coordination of metabolism and food-related behaviour. Our analysis shows that Arouser functions in the fat body through nutrient-related signalling pathways and is degraded by endosomal microautophagy. Arouser degradation occurs during feeding conditions, whereas its stabilisation during non-feeding periods is essential for resistance to starvation and survival. In summary, our data describe a novel role for endosomal microautophagy in energy homeostasis, by the degradation of the signalling regulatory protein Arouser

Engineering mit VINCENT - Der digitale Zwilling für die Entwicklungsphase

Trotz vielfältiger, unterschiedlicher Softwaretools, die den Entwurfsprozess bei komplexen Maschinen und Anlagen unterstützen, ist mit dem Übergang von Planungssystemen für Ablaufspezifikation und Entwurf in Simulationssysteme für die virtuelle Inbetriebnahme und realitätsbegleitende Simulation ein Bruch sowohl in Daten als auch in Systemen zu erkennen. Es wird im vorliegenden Beitrag dargestellt, wie mechanische Konstruktion und Elektrokonstruktion Hand in Hand arbeiten wobei der Übergang weitgehend automatisiert erfolgen kann. Weiterhin wird gezeigt, wie komplexe, multiphysikalische Zusammenhänge einfach beschrieben und sowohl in der Planungsphase zur Auslegung der Maschine als auch während der Inbetriebnahme durchgängig benutzt werden können

Integrierte Planung und virtuelle Inbetriebnahme von komplexen Fertigungsstrassen mit Roboterzellen

In komplexen Fertigungsstraßen werden Komponenten verschiedenster Art miteinander verknüpft, u.a. Roboter, Sondermaschinen und Handlingsysteme. Die Planung für das Zusammenspiel der unterschiedlichen Systeme sowie die Inbetriebnahme, sind aufwendig und zeitintensiv. Jede der Teilkomponenten hat ihre eigene hard- und softwarespezifische, in sich geschlossene Welt. In dieser müssen sie jeweils auf ihre Weise, einzeln für sich programmiert und getestet werden. Sollen die Komponenten zusammenarbeiten, müssen anschließend Brücken gebaut werden, welche die Welten verbinden. Diese Brücken werden in der Regel erst bei der Inbetriebnahme gebaut

Model-based energy recuperation of multi-axis machines

The peak power consumption of multi-axis production machinery (e.g. industrial robots) is determined by the forces during acceleration phases of continuous movements. The required high electric currents represent a cost factor in terms of the mains power supply. In this paper a new Modelica-based method is presented to save the mechanical braking energy of production machinery into a local flywheel-based energy recuperation system (ERS) for later utilization. An ERS has twofold advantages: on the one side it reduces the apparent power peaks from the mains power system. On the other side the overall energy consumption can also be reduced therewith. However; a mechanical ERS with a flywheel needs to be controlled in advance; as its internal inertia and the switched magnetic field introduce some dead time in the process. Therefore; the here presented approach uses an interdisciplinary Modelica model of the machinery to compute future power requirements prior execution of new movements. It is assumed that the machine program is known upfront in a textual form. The movement commands must be carried out with the virtual machine model first. The simulation computes the energy demand; according to which the stored amount of energy within the ERS (i.e. the angular velocity of its flywheel) must be controlled. The here computed reference angular velocity signal is put later also to the real controller; where the physical ERS is attached to as an extra motor. This paper presents the methodology along an example of a 3-axis robotic manipulator that is installed in the VDTC building of the Fraunhofer IFF; Magdeburg. This specific example has been used to validate the concept: 12% less power-consumption and 10% less power peaks were achieved during the operation