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Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
68Ga-radiopharmaceuticals are common in the field of Nuclear Medicine to visualize receptor-mediated processes. In contrast to straightforward labeling procedures for clinical applications, preclinical in vitro and in vivo applications are hampered for reasons like e.g. volume
restriction, activity concentration, molar activity and osmolality. Therefore, we developed a semiautomatic system specifically to overcome these problems. A difficulty appeared unexpectedly, as intrinsic trace metals derived from eluate (Zn, Fe and Cu) are concentrated as well in amounts that influence radiochemical yield and thus lower molar activity.
Comparison of different training algorithms for the leg extension training with an industrial robot
(2018)
In the past, different training scenarios have been developed and implemented on robotic research platforms, but no systematic analysis and comparison have been done so far. This paper deals with the comparison of an isokinematic (motion with constant velocity) and an isotonic (motion against constant weight) training algorithm. Both algorithms are designed for a robotic research platform consisting of a 3D force plate and a high payload industrial robot, which allows leg extension training with arbitrary six-dimensional motion trajectories. In the isokinematic as well as the isotonic training algorithm, individual paths are defined i n C artesian s pace by sufficient s upport p oses. I n t he i sotonic t raining s cenario, the trajectory is adapted to the measured force as the robot should only move along the trajectory as long as the force applied by the user exceeds a minimum threshold. In the isotonic training scenario however, the robot’s acceleration is a function of the force applied by the user. To validate these findings, a simulative experiment with a simple linear trajectory is performed. For this purpose, the same force path is applied in both training scenarios. The results illustrate that the algorithms differ in the force dependent trajectory adaption.
During rapid deceleration of the body, tendons buffer part of the elongation of the muscle-tendon unit (MTU), enabling safe energy dissipation via eccentric muscle contraction. Yet, the influence of changes in tendon stiffness within the physiological range upon these lengthening contractions is unknown. This study aimed to examine the effect of training-induced stiffening of the Achilles tendon on triceps surae muscle-tendon behavior during a landing task. Twenty-one male subjects were assigned to either a 10-week resistance-training program consisting of single-leg isometric plantarflexion (n = 11) or to a non-training control group (n = 10). Before and after the training period, plantarflexion force, peak Achilles tendon strain and stiffness were measured during isometric contractions, using a combination of dynamometry, ultrasound and kinematics data. Additionally, testing included a step-landing task, during which joint mechanics and lengths of gastrocnemius and soleus fascicles, Achilles tendon, and MTU were determined using synchronized ultrasound, kinematics and kinetics data collection. After training, plantarflexion strength and Achilles tendon stiffness increased (15 and 18%, respectively), and tendon strain during landing remained similar. Likewise, lengthening and negative work produced by the gastrocnemius MTU did not change detectably. However, in the training group, gastrocnemius fascicle length was offset (8%) to a longer length at touch down and, surprisingly, fascicle lengthening and velocity were reduced by 27 and 21%, respectively. These changes were not observed for soleus fascicles when accounting for variation in task execution between tests. These results indicate that a training-induced increase in tendon stiffness does not noticeably affect the buffering action of the tendon when the MTU is rapidly stretched. Reductions in gastrocnemius fascicle lengthening and lengthening velocity during landing occurred independently from tendon strain. Future studies are required to provide insight into the mechanisms underpinning these observations and their influence on energy dissipation.
The Dry-Low-NOx (DLN) Micromix combustion technology has been developed as low emission combustion principle for industrial gas turbines fueled with hydrogen or syngas. The combustion process is based on the phenomenon of jet-in-crossflow-mixing (JICF). Fuel is injected perpendicular into the air-cross-flow and burned in a multitude of miniaturized, diffusion-like flames. The miniaturization of the flames leads to a significant reduction of NOx emissions due to the very short residence time of reactants in the flame. In the Micromix research approach, computational fluid dynamics (CFD) analyses are validated toward experimental results. The combination of numerical and experimental methods allows an efficient design and optimization of DLN Micromix combustors concerning combustion stability and low NOx emissions. The paper presents a comparison of several numerical combustion models for hydrogen and hydrogen-rich syngas. They differ in the complexity of the underlying reaction mechanism and the associated computational effort. The performance of a hybrid eddy-break-up (EBU) model with a one-step global reaction is compared to a complex chemistry model and a flamelet generated manifolds (FGM) model, both using detailed reaction schemes for hydrogen or syngas combustion. Validation of numerical results is based on exhaust gas compositions available from experimental investigation on DLN Micromix combustors. The conducted evaluation confirms that the applied detailed combustion mechanisms are able to predict the general physics of the DLN-Micromix combustion process accurately. The FGM method proved to be generally suitable to reduce the computational effort while maintaining the accuracy of detailed chemistry.
A capacitive electrolyte-insulator-semiconductor (EIS) field-effect biosensor for acetoin detection has been presented for the first time. The EIS sensor consists of a layer structure of Al/p-Si/SiO₂/Ta₂O₅/enzyme acetoin reductase. The enzyme, also referred to as butane-2,3-diol dehydrogenase from B. clausii DSM 8716T, has been recently characterized. The enzyme catalyzes the (R)-specific reduction of racemic acetoin to (R,R)- and meso-butane-2,3-diol, respectively. Two different enzyme immobilization strategies (cross-linking by using glutaraldehyde and adsorption) have been studied. Typical biosensor parameters such as optimal pH working range, sensitivity, hysteresis, linear concentration range and long-term stability have been examined by means of constant-capacitance (ConCap) mode measurements. Furthermore, preliminary experiments have been successfully carried out for the detection of acetoin in diluted white wine samples.
In recent years, many onshore wind turbines are erected in seismic active regions and on soils with poor load bearing capacity, where pile grids are inevitable to transfer the loads into the ground. In this contribution, a realistic multi pile grid is designed to analyze the dynamics of a wind turbine tower including frequency dependent soil-structure-interaction. It turns out that different foundations on varying soil configurations heavily influence the vibration response. While the vibration amplitude is mostly attenuated, certain unfavorable combinations of structure and soil parameters lead to amplification in the range of the system's natural frequencies. This testifies the need for overall dynamic analysis in the assessment of the dynamic stability and the holistic frequency tuning of the turbines.
The article presents the investigation of the seismic behaviour of a modern URM building located in the municipality of Finale Emilia in province of Modena, Northern Italy. The building is situated in the centre of the series of the 2012 Northern Italy earthquakes and has not suffered any damage during the earthquake series in 2012. The observed earthquake resistance of the building is compared with predicted resistances based on linear and nonlinear design approaches according to Eurocode. Furthermore, probabilistic analyses based on nonlinear calculation models taking into account scattering of the most relevant input parameters are carried out to identify their influence to the results and to derive fragility curves.
Purpose
In vivo, a loss of mesh porosity triggers scar tissue formation and restricts functionality. The purpose of this study was to evaluate the properties and configuration changes as mesh deformation and mesh shrinkage of a soft mesh implant compared with a conventional stiff mesh implant in vitro and in a porcine model.
Material and Methods
Tensile tests and digital image correlation were used to determine the textile porosity for both mesh types in vitro. A group of three pigs each were treated with magnetic resonance imaging (MRI) visible conventional stiff polyvinylidene fluoride meshes (PVDF) or with soft thermoplastic polyurethane meshes (TPU) (FEG Textiltechnik mbH, Aachen, Germany), respectively. MRI was performed with a pneumoperitoneum at a pressure of 0 and 15 mmHg, which resulted in bulging of the abdomen. The mesh-induced signal voids were semiautomatically segmented and the mesh areas were determined. With the deformations assessed in both mesh types at both pressure conditions, the porosity change of the meshes after 8 weeks of ingrowth was calculated as an indicator of preserved elastic properties. The explanted specimens were examined histologically for the maturity of the scar (collagen I/III ratio).
Results
In TPU, the in vitro porosity increased constantly, in PVDF, a loss of porosity was observed under mild stresses. In vivo, the mean mesh areas of TPU were 206.8 cm2 (± 5.7 cm2) at 0 mmHg pneumoperitoneum and 274.6 cm2 (± 5.2 cm2) at 15 mmHg; for PVDF the mean areas were 205.5 cm2 (± 8.8 cm2) and 221.5 cm2 (± 11.8 cm2), respectively. The pneumoperitoneum-induced pressure increase resulted in a calculated porosity increase of 8.4% for TPU and of 1.2% for PVDF. The mean collagen I/III ratio was 8.7 (± 0.5) for TPU and 4.7 (± 0.7) for PVDF.
Conclusion
The elastic properties of TPU mesh implants result in improved tissue integration compared to conventional PVDF meshes, and they adapt more efficiently to the abdominal wall. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 827–833, 2018.
New information regarding the influence of a stepped chute on the hydraulic performance of the United States Bureau of Reclamation (Reclamation) Type III hydraulic jump stilling basin is presented for design (steady) and adverse (decreasing tailwater) conditions. Using published experimental data and computational fluid dynamics (CFD) models, this paper presents a detailed comparison between smooth-chute and stepped-chute configurations for chute slopes of 0.8H:1V and 4H:1V and Froude numbers (F) ranging from 3.1 to 9.5 for a Type III basin designed for F = 8. For both stepped and smooth chutes, the relative role of each basin element was quantified, up to the most hydraulic extreme case of jump sweep-out. It was found that, relative to a smooth chute, the turbulence generated by a stepped chute causes a higher maximum velocity decay within the stilling basin, which represents an enhancement of the Type III basin’s performance but also a change in the relative role of the basin elements. Results provide insight into the ability of the CFD models [unsteady Reynolds-averaged Navier-Stokes (RANS) equations with renormalization group (RNG) k-ϵ turbulence model and volume-of-fluid (VOF) for free surface tracking] to predict the transient basin flow structure and velocity profiles. Type III basins can perform adequately with a stepped chute despite the effects steps have on the relative role of each basin element. It is concluded that the classic Type III basin design, based upon methodology by reclamation specific to smooth chutes, can be hydraulically improved for the case of stepped chutes for design and adverse flow conditions using the information presented herein.
In the present work an optical sensor in combination with a spectrally resolved detection device for in-line particle-size-monitoring for quality control in beer production is presented. The principle relies on the size and wavelength dependent backscatter of growing particles in fluids. Measured interference structures of backscattered light are compared with calculated theoretical values, based on Mie-Theory, and fitted with a linear least square method to obtain particle size distributions. For this purpose, a broadband light source in combination with a process-CCD-spectrometer (charge ? coupled device spectrometer) and process adapted fiber optics are used. The goal is the development of an easy and flexible measurement device for in-line-monitoring of particle size. The presented device can be directly installed in product fill tubes or vessels, follows CIP- (cleaning in place) and removes the need of sample taking. A proof of concept and preliminary results, measuring protein precipitation, are presented.
Vectrino profiler spatial filtering for shear flows based on the mean velocity gradient equation
(2018)
A new methodology is proposed to spatially filter acoustic Doppler velocimetry data from a Vectrino profiler based on the differential mean velocity equation. Lower and upper bounds are formulated in terms of physically based flow constraints. Practical implementation is discussed, and its application is tested against data gathered from an open-channel flow over a stepped macroroughness surface. The method has proven to detect outliers occurring all over the distance range sampled by the Vectrino profiler and has shown to remain applicable out of the region of validity of the velocity gradient equation. Finally, a statistical analysis suggests that physically obtained bounds are asymptotically representative.
In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents.
Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.
To train end users how to interact with digital systems is indispensable to ensure a strong computer security. 'Competence Developing Game'-based approaches are particularly suitable for this purpose because of their motivation-and simulation-aspects. In this paper the Competence Developing Game 'GHOST' for cybersecurity awareness trainings and its underlying patterns are described. Accordingly, requirements for an 'Competence Developing Game' based training are discussed. Based on these requirements it is shown how a game can fulfill these requirements. A supplementary game interaction design and a corresponding evaluation study is shown. The combination of training requirements and interaction design is used to create a 'Competence Developing Game'-based training concept. A part of these concept is implemented into a playable prototype that serves around one hour of play respectively training time. This prototype is used to perform an evaluation of the game and training aspects of the awareness training. Thereby, the quality of the game aspect and the effectiveness of the training aspect are shown.
An amperometric bi-enzyme biosensor based on substrate recycling principle for the amplification of the sensor signal has been developed for the detection of adrenaline in blood. Adrenaline can be used as biomarker verifying successful adrenal venous sampling procedure. The adrenaline biosensor has been realized via modification of a galvanic oxygen sensor with a bi-enzyme membrane combining a genetically modified laccase and a pyrroloquinoline quinone-dependent glucose dehydrogenase. The measurement conditions such as pH value and temperature were optimized to enhance the sensor performance. A high sensitivity and a low detection limit of about 0.5–1 nM adrenaline have been achieved in phosphate buffer at pH 7.4, relevant for measurements in blood samples. The sensitivity of the biosensor to other catecholamines such as noradrenaline, dopamine and dobutamine has been studied. Finally, the sensor has been successfully applied for the detection of adrenaline in human blood plasma.
On the flight performance impact of landing gear drag reduction methods for unmanned air vehicles
(2018)
The flight performance impact of three different landing gear configurations on a small, fixed-wing UAV is analyzed with a combination of RANS CFD calculations and an incremental flight performance algorithm. A standard fixed landing gear configuration is taken as a baseline, while the influence of retracting the landing gear or applying streamlined fairings is investigated. A retraction leads to a significant parasite drag reduction, while also fairings promise large savings. The increase in lift-to-drag ratio is reduced at high lift coefficients due to the influence of induced drag. All configurations are tested on three different design missions with an incremental flight performance algorithm. A trade-off study is performed using the retracted or faired landing gear's weight increase as a variable. The analysis reveals only small mission performance gains as the aerodynamic improvements are negated by weight penalties. A new workflow for decision-making is presented that allows to estimate if a change in landing gear configuration is beneficial for a small UAV.
A chip-based amperometric biosensor referring on using the bioelectrocatalytical amplification principle for the detection of low adrenaline concentrations is presented. The adrenaline biosensor has been prepared by modification of a platinum thin-film electrode with an enzyme membrane containing the pyrroloquinoline quinone-dependent glucose dehydrogenase and glutaraldehyde. Measuring conditions such as temperature, pH value, and glucose concentration have been optimized to achieve a high sensitivity and a low detection limit of about 1 nM adrenaline measured in phosphate buffer at neutral pH value. The response of the biosensor to different catecholamines has also been proven. Long-term stability of the adrenaline biosensor has been studied over 10 days. In addition, the biosensor has been successfully applied for adrenaline detection in human blood plasma for future biomedical applications. Furthermore, preliminary experiments have been carried to detect the adrenaline-concentration difference measured in peripheral blood and adrenal venous blood, representing the adrenal vein sampling procedure of a physician.
The presentation of enzymes on viral scaffolds has beneficial effects such as an increased enzyme loading and a prolonged reusability in comparison to conventional immobilization platforms. Here, we used modified tobacco mosaic virus (TMV) nanorods as enzyme carriers in penicillin G detection for the first time. Penicillinase enzymes were conjugated with streptavidin and coupled to TMV rods by use of a bifunctional biotin-linker. Penicillinase-decorated TMV particles were characterized extensively in halochromic dye-based biosensing. Acidometric analyte detection was performed with bromcresol purple as pH indicator and spectrophotometry. The TMV-assisted sensors exhibited increased enzyme loading and strongly improved reusability, and higher analysis rates compared to layouts without viral adapters. They extended the half-life of the sensors from 4 - 6 days to 5 weeks and thus allowed an at least 8-fold longer use of the sensors. Using a commercial budget-priced penicillinase preparation, a detection limit of 100 µM penicillin was obtained. Initial experiments also indicate that the system may be transferred to label-free detection layouts.
Impact of electric propulsion technology and mission requirements on the performance of VTOL UAVs
(2018)
One of the engineering challenges in aviation is the design of transitioning vertical take-off and landing (VTOL) aircraft. Thrust-borne flight implies a higher mass fraction of the propulsion system, as well as much increased energy consumption in the take-off and landing phases. This mass increase is typically higher for aircraft with a separate lift propulsion system than for aircraft that use the cruise propulsion system to support a dedicated lift system. However, for a cost–benefit trade study, it is necessary to quantify the impact the VTOL requirement and propulsion configuration has on aircraft mass and size. For this reason, sizing studies are conducted. This paper explores the impact of considering a supplemental electric propulsion system for achieving hovering flight. Key variables in this study, apart from the lift system configuration, are the rotor disk loading and hover flight time, as well as the electrical systems technology level for both batteries and motors. Payload and endurance are typically used as the measures of merit for unmanned aircraft that carry electro-optical sensors, and therefore the analysis focuses on these particular parameters.