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Is part of the Bibliography
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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.
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.
In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.
Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed.
Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging
(2020)
Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented.
Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft
(2020)
As battery technologies advance, electric propulsion concepts are on the edge of disrupting aviation markets. However, until electric energy storage systems are ready to allow fully electric aircraft, the combination of combustion engine and electric motor as a hybrid-electric propulsion system seems to be a promising intermediate solution. Consequently, the design space for future aircraft is expanded considerably, as serial-hybrid-, parallel-hybrid-, fully-electric, and conventional propulsion systems must all be considered. While the best propulsion system depends on a multitude of requirements and considerations, trends can be observed for certain types of aircraft and certain types of missions. This paper provides insight into some factors that drive a new design towards either conventional or hybrid propulsion systems. General aviation aircraft, VTOL air taxis, transport aircraft, and UAVs are chosen as case studies. Typical missions for each class are considered, and the aircraft are analyzed regarding their take-off mass and primary energy consumption. For these case studies, a high-level approach is chosen, using an initial sizing methodology. Results indicate that hybrid-electric propulsion systems should be considered if the propulsion system is sized by short-duration power constraints (e.g. take-off, climb). However, if the propulsion system is sized by a continuous power requirement (e.g. cruise), hybrid-electric systems offer hardly any benefit.
Impact of Battery Performance on the Initial Sizing of Hybrid-Electric General Aviation Aircraft
(2020)
Studies suggest that hybrid-electric aircraft have the potential to generate fewer emissions and be inherently quieter when compared to conventional aircraft. By operating combustion engines together with an electric propulsion system, synergistic benefits can be obtained. However, the performance of hybrid-electric aircraft is still constrained by a battery’s energy density and discharge rate. In this paper, the influence of battery performance on the gross mass for a four-seat general aviation aircraft with a hybrid-electric propulsion system is analyzed. For this design study, a high-level approach is chosen, using an innovative initial sizing methodology to determine the minimum required aircraft mass for a specific set of requirements and constraints. Only the peak-load shaving operational strategy is analyzed. Both parallel- and serial-hybrid propulsion configurations are considered for two different missions. The specific energy of the battery pack is varied from 200 to 1,000 W⋅h/kg, while the discharge time, and thus the normalized discharge rating (C-rating), is varied between 30 min (2C discharge rate) and 2 min (30C discharge rate). With the peak-load shaving operating strategy, it is desirable for hybrid-electric aircraft to use a light, low capacity battery system to boost performance. For this case, the battery’s specific power rating proved to be of much higher importance than for full electric designs, which have high capacity batteries. Discharge ratings of 20C allow a significant take-off mass reduction aircraft. The design point moves to higher wing loadings and higher levels of hybridization if batteries with advanced technology are used.