Article
Refine
Year of publication
- 2020 (99) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (44)
- IfB - Institut für Bioengineering (25)
- Fachbereich Luft- und Raumfahrttechnik (15)
- Fachbereich Chemie und Biotechnologie (9)
- INB - Institut für Nano- und Biotechnologien (9)
- Fachbereich Energietechnik (7)
- Fachbereich Wirtschaftswissenschaften (7)
- Fachbereich Elektrotechnik und Informationstechnik (6)
- Fachbereich Maschinenbau und Mechatronik (6)
- ECSM European Center for Sustainable Mobility (5)
Has Fulltext
- no (99) (remove)
Language
- English (99) (remove)
Document Type
- Article (99) (remove)
Keywords
- rebound-effect (2)
- sustainability (2)
- Adaptive control (1)
- Brownian Pillow (1)
- Conservation laws (1)
- Crámer–von-Mises distance (1)
- Dimensional splitting (1)
- Entropy solution (1)
- Experimental validation (1)
- Exponential time differencing (1)
Is part of the Bibliography
- no (99)
This paper presents a novel method for airfoil drag estimation at Reynolds numbers between 4×10⁵ and 4×10⁶. The novel method is based on a systematic study of 40 airfoils applying over 600 numerical simulations and considering natural transition. The influence of the airfoil thickness-to-chord ratio, camber, and freestream Reynolds number on both friction and pressure drag is analyzed in detail. Natural transition significantly affects drag characteristics and leads to distinct drag minima for different Reynolds numbers and thickness-to-chord ratios. The results of the systematic study are used to develop empirical correlations that can accurately predict an airfoil drag at low-lift conditions. The new approach estimates a transition location based on airfoil thickness-to-chord ratio, camber, and Reynolds number. It uses the transition location in a mixed laminar–turbulent skin-friction calculation, and corrects the skin-friction coefficient for separation effects. Pressure drag is estimated separately based on correlations of thickness-to-chord ratio, camber, and Reynolds number. The novel method shows excellent accuracy when compared with wind-tunnel measurements of multiple airfoils. It is easily integrable into existing aircraft design environments and is highly beneficial in the conceptual design stage.
The paper presents an aerodynamic investigation of 70 different streamlined bodies with fineness ratios ranging from 2 to 10. The bodies are chosen to idealize both unmanned and small manned aircraft fuselages and feature cross-sectional shapes that vary from circular to quadratic. The study focuses on friction and pressure drag in dependency of the individual body’s fineness ratio and cross section. The drag forces are normalized with the respective body’s wetted area to comply with an empirical drag estimation procedure. Although the friction drag coefficient then stays rather constant for all bodies, their pressure drag coefficients decrease with an increase in fineness ratio. Referring the pressure drag coefficient to the bodies’ cross-sectional areas shows a distinct pressure drag minimum at a fineness ratio of about three. The pressure drag of bodies with a quadratic cross section is generally higher than for bodies of revolution. The results are used to derive an improved form factor that can be employed in a classic empirical drag estimation method. The improved formulation takes both the fineness ratio and cross-sectional shape into account. It shows superior accuracy in estimating streamlined body drag when compared with experimental data and other form factor formulations of the literature.
This paper analyzes the drag characteristics of several landing gear and turret configurations that are representative of unmanned aircraft tricycle landing gears and sensor turrets. A variety of these components were constructed via 3D-printing and analyzed in a wind-tunnel measurement campaign. Both turrets and landing gears were attached to a modular fuselage that supported both isolated components and multiple components at a time. Selected cases were numerically investigated with a Reynolds-averaged Navier-Stokes approach that showed good accuracy when compared to wind-tunnel data. The drag of main gear struts could be significantly reduced via streamlining their cross-sectional shape and keeping load carrying capabilities similar. The attachment of wheels introduced interference effects that increased strut drag moderately but significantly increased wheel drag compared to isolated cases. Very similar behavior was identified for front landing gears. The drag of an electro-optical and infrared sensor turret was found to be much higher than compared to available data of a clean hemisphere-cylinder combination. This turret drag was merely influenced by geometrical features like sensor surfaces and the rotational mechanism. The new data of this study is used to develop simple drag estimation recommendations for main and front landing gear struts and wheels as well as sensor turrets. These recommendations take geometrical considerations and interference effects into account.
Experience has shown that a priori created static resource allocation plans are vulnerable to runtime deviations and hence often become uneconomic or highly exceed a predefined soft deadline. The assumption of constant task execution times during allocation planning is even more unlikely in a cloud environment where virtualized resources vary in performance. Revising the initially created resource allocation plan at runtime allows the scheduler to react on deviations between planning and execution. Such an adaptive rescheduling of a many-task application workflow is only feasible, when the planning time can be handled efficiently at runtime. In this paper, we present the static low-complexity resource allocation planning algorithm (LCP) applicable to efficiently schedule many-task scientific application workflows on cloud resources of different capabilities. The benefits of the presented algorithm are benchmarked against alternative approaches. The benchmark results show that LCP is not only able to compete against higher complexity algorithms in terms of planned costs and planned makespan but also outperforms them significantly by magnitudes of 2 to 160 in terms of required planning time. Hence, LCP is superior in terms of practical usability where low planning time is essential such as in our targeted online rescheduling scenario.
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
We discuss the testing problem of homogeneity of the marginal distributions of a continuous bivariate distribution based on a paired sample with possibly missing components (missing completely at random). Applying the well-known two-sample Crámer–von-Mises distance to the remaining data, we determine the limiting null distribution of our test statistic in this situation. It is seen that a new resampling approach is appropriate for the approximation of the unknown null distribution. We prove that the resulting test asymptotically reaches the significance level and is consistent. Properties of the test under local alternatives are pointed out as well. Simulations investigate the quality of the approximation and the power of the new approach in the finite sample case. As an illustration we apply the test to real data sets.
The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.
The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
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.
Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft
(2020)
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-electric, parallel hybrid-electric, 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 toward either conventional or hybrid propulsion systems. General aviation aircraft, regional transport aircraft vertical takeoff and landing air taxis, and unmanned aerial vehicles are chosen as case studies. Typical missions for each class are considered, and the aircraft are analyzed regarding their takeoff mass and primary energy consumption. For these case studies, a high-level approach is chosen, using an initial sizing methodology. Only parallel-hybrid-electric powertrains are taken into account. Aeropropulsive interaction effects are neglected. Results indicate that hybrid-electric propulsion systems should be considered if the propulsion system is sized by short-duration power constraints. However, if the propulsion system is sized by a continuous power requirement, hybrid-electric systems offer hardly any benefit.
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.
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.
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.
In this article, we describe the structure, the functioning, and the tests of parabolic trough solar thermal cooker (PSTC). This oven is designed to meet the needs of rural residents, including Urban, which requires stable cooking temperatures above 200 °C. The cooking by this cooker is based on the concentration of the sun's rays on a glass vacuum tube and heating of the oil circulate in a big tube, located inside the glass tube. Through two small tubes, associated with large tube, the heated oil, rise and heats the pot of cooking pot containing the food to be cooked (capacity of 5 kg). This cooker is designed in Germany and extensively tested in Morocco for use by the inhabitants who use wood from forests.
During a sunny day, having a maximum solar radiation around 720 W/m2 and temperature ambient around 26 °C, maximum temperatures recorded of the small tube, the large tube and the center of the pot are respectively: 370 °C, 270 °C and 260 °C. The cooking process with food at high (fries, ..), we show that the cooking oil temperature rises to 200 °C, after 1 h of heating, the cooking is done at a temperature of 120 °C for 20 min. These temperatures are practically stable following variations and decreases in the intensity of irradiance during the day. The comparison of these results with those of the literature shows an improvement of 30–50 % on the maximum value of the temperature with a heat storage that could reach 60 min of autonomy. All the results obtained show the good functioning of the PSTC and the feasibility of cooking food at high temperature (>200 °C).
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
Nacre-mimetic nanocomposites based on high fractions of synthetic high-aspect-ratio nanoclays in combination with polymers are continuously pushing boundaries for advanced material properties, such as high barrier against oxygen, extraordinary mechanical behavior, fire shielding, and glass-like transparency. Additionally, they provide interesting model systems to study polymers under nanoconfinement due to the well-defined layered nanocomposite arrangement. Although the general behavior in terms of forming such layered nanocomposite materials using evaporative self-assembly and controlling the nanoclay gallery spacing by the nanoclay/polymer ratio is understood, some combinations of polymer matrices and nanoclay reinforcement do not comply with the established models. Here, we demonstrate a thorough characterization and analysis of such an unusual polymer/nanoclay pair that falls outside of the general behavior. Poly(ethylene oxide) (PEO) and sodium fluorohectorite form nacre-mimetic, lamellar nanocomposites that are completely transparent and show high mechanical stiffness and high gas barrier, but there is only limited expansion of the nanoclay gallery spacing when adding increasing amounts of polymer. This behavior is maintained for molecular weights of PEO varied over four orders of magnitude and can be traced back to depletion forces. By careful investigation via X-ray diffraction and proton low-resolution solid-state NMR, we are able to quantify the amount of mobile and immobilized polymer species in between the nanoclay galleries and around proposed tactoid stacks embedded in a PEO matrix. We further elucidate the unusual confined polymer dynamics, indicating a relevant role of specific surface interactions.
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.