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Hands-on-training in high technology areas is usually limited due to the high cost for lab infrastructure and equipment. One specific example is the field of MEMS, where investment and upkeep of clean rooms with microtechnology equipment is either financed by production or R&D projects greatly reducing the availability for education purposes. For efficient hands-on-courses a MEMS training foundry, currently used jointly by six higher education institutions, was established at FH Kaiserslautern. In a typical one week course, students manufacture a micromachined pressure sensor including all lithography, thin film and packaging steps. This compact and yet complete program is only possible because participants learn to use the different complex machines in advance via a Virtual Training Lab (VTL). In this paper we present the concept of the MEMS training foundry and the VTL preparation together with results from a scientific evaluation of the VTL over the last three years.
Recent analysis of scientific data from Cassini and earth-based observations gave evidence for a global ocean under a surrounding solid ice shell on Saturn's moon Enceladus. Images of Enceladus' South Pole showed several fissures in the ice shell with plumes constantly exhausting frozen water particles, building up the E-Ring, one of the outer rings of Saturn. In this southern region of Enceladus, the ice shell is considered to be as thin as 2 km, about an order of magnitude thinner than on the rest of the moon. Under the ice shell, there is a global ocean consisting of liquid water. Scientists are discussing different approaches the possibilities of taking samples of water, i.e. by melting through the ice using a melting probe. FH Aachen UAS developed a prototype of maneuverable melting probe which can navigate through the ice that has already been tested successfully in a terrestrial environment. This means no atmosphere and or ambient pressure, low ice temperatures of around 100 to 150K (near the South Pole) and a very low gravity of 0,114 m/s^2 or 1100 μg. Two of these influencing measures are about to be investigated at FH Aachen UAS in 2017, low ice temperature and low ambient pressure below the triple point of water. Low gravity cannot be easily simulated inside a large experiment chamber, though. Numerical simulations of the melting process at RWTH Aachen however are showing a gravity dependence of melting behavior. Considering this aspect, VIPER provides a link between large-scale experimental simulations at FH Aachen UAS and numerical simulations at RWTH Aachen. To analyze the melting process, about 90 seconds of experiment time in reduced gravity and low ambient pressure is provided by the REXUS rocket. In this time frame, the melting speed and contact force between ice and probes are measured, as well as heating power and a two-dimensional array of ice temperatures. Additionally, visual and infrared cameras are used to observe the melting process.
Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.
Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]–[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]–[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
The utilisation of vehicle-oriented gasoline in general aviation is very desirable for both ecological and economical reasons, as well as for general considerations of availability. As of today vehicle fuels may be used if the respective engine and cell are certified for such an operation. For older planes a supplementary technical certificate is provided for gasoline mixtures with less than 1 % v/v ethanol only, though. Larger admixtures of ethanol may lead to sudden engine malfunction and should be considered as considerable security risks. Major problems are caused by the partially ethanol non-withstanding materials, a necessarily changed stochiometric adjustment of the engine for varying ethanol shares and the tendency for phase separation in the presence of absorbed water. The concepts of the flexible fuel vehicles are only partially applicable in the view of air security.
The UN sets the goal to ensure access to water and sanitation for all people by 2030. To address this goal, we present a multidisciplinary approach for designing water supply networks for slums in large cities by applying mathematical optimization. The problem is modeled as a mixed-integer linear problem (MILP) aiming to find a network describing the optimal supply infrastructure. To illustrate the approach, we apply it on a small slum cluster in Dhaka, Bangladesh.
Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers’ actions. Game elements are selected according to the work task and users’ preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.