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We introduce a new way to measure the forecast effort that analysts devote to their earnings forecasts by measuring the analyst's general effort for all covered firms. While the commonly applied effort measure is based on analyst behaviour for one firm, our measure considers analyst behaviour for all covered firms. Our general effort measure captures additional information about analyst effort and thus can identify accurate forecasts. We emphasise the importance of investigating analyst behaviour in a larger context and argue that analysts who generally devote substantial forecast effort are also likely to devote substantial effort to a specific firm, even if this effort might not be captured by a firm-specific measure. Empirical results reveal that analysts who devote higher general forecast effort issue more accurate forecasts. Additional investigations show that analysts' career prospects improve with higher general forecast effort. Our measure improves on existing methods as it has higher explanatory power regarding differences in forecast accuracy than the commonly applied effort measure. Additionally, it can address research questions that cannot be examined with a firm-specific measure. It provides a simple but comprehensive way to identify accurate analysts.
The ATM technology for high speed serial transmission provides a new quality of communication by introducing novel features in a LAN environment, especially support of real time communication, of both LAN and WAN communication and of multimedia streams. In order to evaluate ATM for future DAQ systems and remote control systems as well as for a high speed picture archiving and communications system for medical images, Forschungszentrum Julich has build up a pilot system for the evaluation of ATM and standard low cost multimedia systems. It is a heterogeneous multivendor system containing a variety of switches and desktop solutions, employing different protocol options of ATM. The tests conducted in the pilot system revealed major difficulties regarding stability, interoperability and performance. The paper presents motivations, layout and results of the pilot system. Discussion of results concentrates on performance issues relevant for realistic applications, e.g., connection to a RAID system via NFS over ATM
An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.
Elastic transmission eigenvalues and their computation via the method of fundamental solutions
(2020)
A stabilized version of the fundamental solution method to catch ill-conditioning effects is investigated with focus on the computation of complex-valued elastic interior transmission eigenvalues in two dimensions for homogeneous and isotropic media. Its algorithm can be implemented very shortly and adopts to many similar partial differential equation-based eigenproblems as long as the underlying fundamental solution function can be easily generated. We develop a corroborative approximation analysis which also implicates new basic results for transmission eigenfunctions and present some numerical examples which together prove successful feasibility of our eigenvalue recovery approach.
The hot spots conjecture is only known to be true for special geometries. This paper shows numerically that the hot spots conjecture can fail to be true for easy to construct bounded domains with one hole. The underlying eigenvalue problem for the Laplace equation with Neumann boundary condition is solved with boundary integral equations yielding a non-linear eigenvalue problem. Its discretization via the boundary element collocation method in combination with the algorithm by Beyn yields highly accurate results both for the first non-zero eigenvalue and its corresponding eigenfunction which is due to superconvergence. Additionally, it can be shown numerically that the ratio between the maximal/minimal value inside the domain and its maximal/minimal value on the boundary can be larger than 1 + 10− 3. Finally, numerical examples for easy to construct domains with up to five holes are provided which fail the hot spots conjecture as well.
Interior transmission eigenvalue problems for the Helmholtz equation play an important role in inverse wave scattering. Some distribution properties of those eigenvalues in the complex plane are reviewed. Further, a new scattering model for the interior transmission eigenvalue problem with mixed boundary conditions is described and an efficient algorithm for computing the interior transmission eigenvalues is proposed. Finally, extensive numerical results for a variety of two-dimensional scatterers are presented to show the validity of the proposed scheme.
As part of a novel approach to automatic sewer inspection, this paper presents a robust algorithm for automatic flow line detection. A large image repository is obtained from about 50,000 m sewers to represent the high variability of real world sewer systems. Automatic image processing combines Canny edge detection, Hough transform for straight lines and cost minimization using Dijkstra's shortest path algorithm. Assuming that flow lines are mostly smoothly connected horizontal structures, piecewise flow line delineation is reduced to a process of selecting adjacent line candidates. Costs are derived from the gap between adjacent candidates and their reliability. A single parameter α enables simple control of the algorithm. The detected flow line may precisely follow the segmented edges (α = 0.0) or minimize gaps at joints (α = 1.0). Both, manual and ground truth-based analysis indicate that α = 0.8 is optimal and independent of the sewer's material. The algorithm forms an essential step to further automation of sewer inspection.
The field of Cognitive Robotics aims at intelligent decision making of autonomous robots. It has matured over the last 25 or so years quite a bit. That is, a number of high-level control languages and architectures have emerged from the field. One concern in this regard is the action language GOLOG. GOLOG has been used in a rather large number of applications as a high-level control language ranging from intelligent service robots to soccer robots. For the lower level robot software, the Robot Operating System (ROS) has been around for more than a decade now and it has developed into the standard middleware for robot applications. ROS provides a large number of packages for standard tasks in robotics like localisation, navigation, and object recognition. Interestingly enough, only little work within ROS has gone into the high-level control of robots. In this paper, we describe our approach to marry the GOLOG action language with ROS. In particular, we present our architecture on inte grating golog++, which is based on the GOLOG dialect Readylog, with the Robot Operating System. With an example application on the Pepper service robot, we show how primitive actions can be easily mapped to the ROS ActionLib framework and present our control architecture in detail.
Various models have been proposed for the prediction of the necessary support pressure at the face of a shallow tunnel. To assess their quality, the collapse of a tunnel face was modelled with small-scale model tests at single gravity. The development of the failure mechanism and the support force at the face in dry sand were investigated. The observed displacement patterns show a negligible influence of overburden on the extent and evolution of the failure zone. The latter is significantly influenced, though, by the initial density of the sand: in dense sand a chimney-wedge-type collapse mechanism developed, which propagated towards the soil surface. Initially, loose sand did not show any discrete collapse mechanism. The necessary support force was neither influenced by the overburden nor the initial density. A comparison with quantitative predictions by several theoretical models showed that the measured necessary support pressure is overestimated by most of the models. Those by Vermeer/Ruse and Léca/Dormieux showed the best agreement to the measurements.
For the sterilisation of aseptic food packages it is taken advantage of the microbicidal properties of hydrogen peroxide (H2O2). Especially, when applied in vapour phase, it has shown high potential of microbial inactivation. In addition, it offers a high environmental compatibility compared to other chemical sterilisation agents, as it decomposes into oxygen and water, respectively. Due to a lack in sensory detection possibilities, a continuous monitoring of the H2O2 concentration was recently not available. Instead, the sterilisation efficacy is validated using microbiological tests. However, progresses in the development of calorimetric gas sensors during the last 7 years have made it possible to monitor the H2O2 concentration during operation. This chapter deals with the fundamentals of calorimetric gas sensing with special focus on the detection of gaseous hydrogen peroxide. A sensor principle based on a calorimetric differential set-up is described. Special emphasis is given to the sensor design with respect to the operational requirements under field conditions. The state-of-the-art regarding a sensor set-up for the on-line monitoring and secondly, a miniaturised sensor for in-line monitoring are summarised. Furthermore, alternative detection methods and a novel multi-sensor system for the characterisation of aseptic sterilisation processes are described.
Characterisation of polymeric materials as passivation layer for calorimetric H2O2 gas sensors
(2012)
Calorimetric gas sensors for monitoring the H₂O₂ concentration at elevated temperatures in industrial sterilisation processes have been presented in previous works. These sensors are built up in form of a differential set-up of a catalytically active and passive temperature-sensitive structure. Although, various types of catalytically active dispersions have been studied, the passivation layer has to be established and therefore, chemically as well as physically characterised. In the present work, fluorinated ethylene propylene (FEP), perfluoralkoxy (PFA) and epoxy-based SU-8 photoresist as temperature-stable polymeric materials have been investigated for sensor passivation in terms of their chemical inertness against H₂O₂, their hygroscopic properties as well as their morphology. The polymeric materials were deposited via spin-coating on the temperature-sensitive structure, wherein spin-coated FEP and PFA show slight agglomerates. However, they possess a low absorption of humidity due to their hydrophobic surface, whereas the SU-8 layer has a closed surface but shows a slightly higher absorption of water. All of them were inert against gaseous H₂O₂ during the characterisation in H₂O₂ atmosphere that demonstrates their suitability as passivation layer for calorimetric H₂O₂ gas sensors.
A wireless sensor system based on the industrial ZigBee standard for low-rate wireless networking was developed that enables real-time monitoring of gaseous H2O2 during the package sterilization in aseptic food processes. The sensor system consists of a remote unit connected to a calorimetric gas sensor, which was already established in former works, and an external base unit connected to a laptop computer. The remote unit was built up by an XBee radio frequency (RF) module for data communication and a programmable system-on-chip controller to read out the sensor signal and process the sensor data, whereas the base unit is a second XBee RF module. For the rapid H2O2 detection on various locations inside the package that has to be sterilized, a novel read-out strategy of the calorimetric gas sensor was established, wherein the sensor response is measured within the short sterilization time and correlated with the present H2O2 concentration. In an exemplary measurement application in an aseptic filling machinery, the suitability of the new, wireless sensor system was demonstrated, wherein the influence of the gas velocity on the H2O2 distribution inside a package was determined and verified with microbiological tests.
In the present work, a novel method for monitoring sterilisation processes with gaseous H2O2 in combination with heat activation by means of a specially designed calorimetric gas sensor was evaluated. Therefore, the sterilisation process was extensively studied by using test specimens inoculated with Bacillus atrophaeus spores in order to identify the most influencing process factors on its microbicidal effectiveness. Besides the contact time of the test specimens with gaseous H2O2 varied between 0.2 and 0.5 s, the present H2O2 concentration in a range from 0 to 8% v/v (volume percent) had a strong influence on the microbicidal effectiveness, whereas the change of the vaporiser temperature, gas flow and humidity were almost negligible. Furthermore, a calorimetric H2O2 gas sensor was characterised in the sterilisation process with gaseous H2O2 in a wide range of parameter settings, wherein the measurement signal has shown a linear response against the H2O2 concentration with a sensitivity of 4.75 °C/(% v/v). In a final step, a correlation model by matching the measurement signal of the gas sensor with the microbial inactivation kinetics was established that demonstrates its suitability as an efficient method for validating the microbicidal effectiveness of sterilisation processes with gaseous H2O2.
Realization of a calorimetric gas sensor on polyimide foil for applications in aseptic food industry
(2010)
Realisation of a calorimetric gas sensor on polyimide foil for applications in aseptic food industry
(2012)
A calorimetric gas sensor is presented for the monitoring of vapour-phase H2O2 at elevated temperature during sterilisation processes in aseptic food industry. The sensor was built up on a flexible polyimide foil (thickness: 25 μm) that has been chosen due to its thermal stability and low thermal conductivity. The sensor set-up consists of two temperature-sensitive platinum thin-film resistances passivated by a layer of SU-8 photo resist and catalytically activated by manganese(IV) oxide. Instead of an active heating structure, the calorimetric sensor utilises the elevated temperature of the evaporated H2O2 aerosol. In an experimental test rig, the sensor has shown a sensitivity of 4.78 °C/(%, v/v) in a H2O2 concentration range of 0%, v/v to 8%, v/v. Furthermore, the sensor possesses the same, unchanged sensor signal even at varied medium temperatures between 210 °C and 270 °C of the gas stream. At flow rates of the gas stream from 8 m3/h to 12 m3/h, the sensor has shown only a slightly reduced sensitivity at a low flow rate of 8 m3/h. The sensor characterisation demonstrates the suitability of the calorimetric gas sensor for monitoring the efficiency of industrial sterilisation processes.
IASSE-2004 - 13th International Conference on Intelligent and Adaptive Systems and Software Engineering eds. W. Dosch, N. Debnath, pp. 245-250, ISCA, Cary, NC, 1-3 July 2004, Nice, France We introduce a UML-based model for conceptual design support in civil engineering. Therefore, we identify required extensions to standard UML. Class diagrams are used for elaborating building typespecific knowledge: Object diagrams, implicitly contained in the architect’s sketch, are validated against the defined knowledge. To enable the use of industrial, domain-specific tools, we provide an integrated conceptual design extension. The developed tool support is based on graph rewriting. With our approach architects are enabled to deal with semantic objects during early design phase, assisted by incremental consistency checks.
This paper presents the results of an eigenvalue analysis of the Fatih Sultan Mehmet Bridge. A high-resolution finite element model was created directly from the available design documents. All physical properties of the structural components were included in detail, so no calibration to the measured data was necessary. The deck and towers were modeled with shell elements. A nonlinear static analysis was performed before the eigenvalue calculation. The calculated natural frequencies and corresponding mode shapes showed good agreement with the available measured ambient vibration data. The calculation of the effective modal mass showed that nine modes had single contributions higher than 5 % of the total mass. They were in a frequency range up to 1.2 Hz. The comparison of the results for the torsional modes especially demonstrated the advantage of using thin shell finite elements over the beam modeling approach.
The ClearPET™ Neuro is the first full ring scanner within the Crystal Clear Collaboration (CCC). It consists of 80 detector modules allocated to 20 cassettes. LSO and LuYAP:Ce crystals in phoswich configuration in combination with position sensitive photomultiplier tubes are used to achieve high sensitivity and realize the acquisition of the depth of interaction (DOI) information. The complete system has been tested concerning the mechanical and electronical stability and interplay. Moreover, suitable corrections have been implemented into the reconstruction procedure to ensure high image quality. We present first results which show the successful operation of the ClearPET™ Neuro for artefact free and high resolution small animal imaging. Based on these results during the past few months the ClearPET™ Neuro System has been modified in order to optimize the performance.
We are developing an X-ray computed tomography (CT) system which will be combined with a high resolution animal PET system. This permits acquisition of both molecular and anatomical images in a single machine. In particular the CT will also be utilized for the quantification of the animal PET data by providing accurate data for attenuation correction. A first prototype has been built using a commercially available plane silicon diode detector. A cone-beam reconstruction provides the images using the Feldkamp algorithm. First measurements with this system have been performed on a mouse. It could be shown that the CT setup fulfils all demands for a high quality image of the skeleton of the mouse. It is also suited for soft tissue measurements. To improve contrast and resolution and to acquire the X-ray energy further development of the system, especially the use of semiconductor detectors and iterative reconstruction algorithms are planned.
This study has been performed to design the combination of the new ClearPET TM (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal Positron Emission Tomography (PET) system, with a microComputed Tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material.
This study has been performed to design the combination of the new ClearPET (ClearPET is a trademark of the Crystal Clear Collaboration), a small animal positron emission tomography (PET) system, with a micro-computed tomography (microCT) scanner. The properties of different microCT systems have been determined by simulations based on GEANT4. We will demonstrate the influence of the detector material and the X-ray spectrum on the obtained contrast. Four different detector materials (selenium, cadmium zinc telluride, cesium iodide and gadolinium oxysulfide) and two X-ray spectra (a molybdenum and a tungsten source) have been considered. The spectra have also been modified by aluminum filters of varying thickness. The contrast between different tissue types (water, air, brain, bone and fat) has been simulated by using a suitable phantom. The results indicate the possibility to improve the image contrast in microCT by an optimized combination of the X-ray source and detector material.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
The possibility of using the atomic-force microscopy as a method for detection of the analytical signal from plasticized polymeric sensor membranes was analyzed. The surfaces of cadmium-selective membranes based on two polymeric matrices were examined. The digital images were processed with multivariate image analysis techniques. A correlation was found between the surface profile of an ion-selective membrane and the concentration of the ion in solution.
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
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.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.
Zero energy solutions for multifunctional steel intensive commercial buildings (ZEMUSIC) - EUR 27627
(2015)
The broad commercial objective of this project was the sustainable value creation in steel building technology by addressing the ways in which significant energy reductions can be made in the operation phase of multi-storey commercial buildings. A review on energy efficient commercial buildings in Europe has been carried out consisting of several case studies from different countries. The project included development of zero-energy concepts for reducing energy demand as well as concepts for heating, cooling and ventilation systems by utilising renewable energy sources in three different climates. Also alternative structural frame solutions were developed and analyzed in respect of structural and MEP (mechanical, electrical and plumbing solutions) features. An innovative long span floor system with integrated MEP routings promises a cost effective alternative for sophisticated ventilation distribution and radiant heating and cooling systems, allowing for high energy efficiency and high quality interior climate. The report includes also review of best architectural practices for integrated renewable energy solutions including different design strategies for building facades of zero energy buildings. Interesting results and design basis are also presented for steel energy pile concept, where structural foundation piles are utilized for ground energy harvesting. Life cycle cost calculations for near zero energy office building based on developed technologies show that a near zero energy construction is also profitable. The results and work methods of the project have been summarized in the form of design guidance that offers designers the knowledge gained in a form that can be easily understood.
Different analytical approaches exist to describe the structural substance or wear reserve of sewer systems. The aim is to convert engineering assessments of often complex defect patterns into computational algorithms and determine a substance class for a sewer section or manhole. This analytically determined information is essential for strategic rehabilitation planning processes up to network level, as it corresponds to the most appropriate rehabilitation type and can thus provide decision-making support. Current calculation methods differ clearly from each other in parts, so that substance classes determined by the different approaches are only partially comparable with each other. The objective of the German R&D cooperation project ‘SubKanS’ is to develop a methodology for classifying the specific defect patterns resulting from the interaction of all the individual defects, and their severities and locations. The methodology takes into account the structural substance of sewer sections and manholes, based on real data and theoretical considerations analogous to the condition classification of individual defects. The result is a catalogue of defect patterns and characteristics, as well as associated structural substance classifications of sewer systems (substance classes). The methodology for sewer system substance classification is developed so that the classification of individual defects can be transferred into a substance class of the sewer section or manhole, eventually taking into account further information (e.g. pipe material, nominal diameter, etc.). The result is a validated methodology for automated sewer system substance classification.
Shielding effectiveness of reinforced concrete cable ducts carrying partial lightning currents
(1998)
Comparison of single point and equipotential bonding for I&C systems of large-area industrial sites
(1994)
The longitudinal voltage of cable tubes with a screening mesh caused by partial lightning currents
(1989)
Lightning protection design of a renewable energy hybrid-system without power mains connection
(2001)
Lightning protection design of a renewable energy hybrid-system without power mains connection
(2001)
In the year 2000 a direct lightning strike to the hybridsystem without power mains connection VATALI on the Greek island Crete results in the destruction and damage of some mechanical and electrical components. The hybrid-system VATALI was not lightning protected at that time. The hardware damage costs are approx. 60,000 €. The exposed site of the hybrid-system on top of a mountain was and still is the reason for a high risk of lightning strikes. Also in the future further lightning strikes have to be taken into consideration. In the paper a fundamental lightning protection design concept for renewable energy hybrid-systems without power mains connection and protection measures against direct strikes and overvoltages are shown in detail. The design concept was realized exemplarily for the hybrid-system VATALI. The hardware costs for the protection measures were about 15,000 €. About 50% of the costs are due to protection measures against direct strikes, 50% are due to overvoltage protection. Future extensions, new installations, or modifications have to be included into the lightning protection design concept of the hybrid-system.
In the paper a lightning protection design concept for renewable energy hybrid-systems without power mains connection is described. Based on a risk analysis protection measures against direct strikes and overvoltages are shown in an overview. The design concept is realized exemplarily for the hybrid-system VATALI on the Greek island Crete. VATALI, not lightning protected at that time, was a victim of a lightning strike in the year 2000 causing destructions and damages of some mechanical and electrical components with costs of approx. 60.000 €. The hardware costs for the protection measures were about 15.000 €: about 50% of the costs are due to protection measures against direct strikes, 50% are due to overvoltage protection.
For typical cases of non-isolated lightning protection systems (LPS) the impulse currents are investigated which may flow through a human body directly touching a structural part of the LPS. Based on a basic LPS model with conventional down-conductors especially the cases of external and internal steel columns and metal façades are considered and compared. Numerical simulations of the line quantities voltages and currents in the time domain are performed with an equivalent circuit of the entire LPS.
As a result it can be stated that by increasing the number of conventional down-conductors and external steel columns the threat for a human being can indeed be reduced, but not down to an acceptable limit. In case of internal steel columns used as natural down-conductors the threat can be reduced sufficiently, depending on the low-resistive connection of the steel columns to the lightning equipotential bonding or the earth termination system, resp. If a metal façade is used the threat for human beings touching is usually very low, if the façade is sufficiently interconnected and multiply connected to the lightning equipotential bonding or the earth termination system, resp.
In the paper the results obtained from experiments at a modelled reinforced building in case of a direct lightning strike are compared with calculations. The comparison includes peak values of the magnetic field Hmax, its derivative (dH/dt)max and of induced voltages umax in typical cable routings. The experiments are performed at a 1:6 scaled building and the results are extrapolated using the similarity relations theory. The calculations are based on the approximate formulae given in IEC 62305-4 and have to be supplemented by a rough estimation of the additional shielding effect of a second reinforcement layer. The comparison shows, that the measured peak values of the magnetic field and its derivative are mostly lower than the calculated. The induced voltages are in good agreement. Hence, calculations of the induced voltages based on IEC 62305-4 are a good method for lightning protection studies of buildings, where the reinforcement is used as a grid-like electromagnetic shield.
In the presented paper data collected from the field related to damage statistics of electrical and electronic apparatus in household are reported and investigated. These damages (total number approx. 74000 cases), registered by five German insurance companies in 2005 and 2006, were adviced by customers as caused by lightning overvoltages. With the use of stochastical methods it is possible, to reasses the collected data and to distinguish between cases, which are with high probability caused by lightning overvoltages, and those, which are not. If there was an indication for a direct strike, this case was excluded, so the focus was only on indirect lightning flashes, i.e. only flashes to ground near the structure and flashes to or nearby an incoming service line were investigated. The data from the field contain the location of damaged apparatus (residence of the policy holder) and the distances of the nearest cloud-to-ground stroke to the location of the damage registered by the German lightning location network BLIDS at the date of damage. The statistical data along with some complementary numerical simulations allow to verify the correspondence of the Standards rules used for IEC 62305-2 with the field data and to define some correction needs. The results could lead to a better understanding whether a damage reported to an insurance company is really caused by indirect lightning, or not.
Risk management for structures with a risk of explosion should be considered very carefully when performing a risk analysis according to IEC 62305-2. In contrast to the 2006 edition of the standard, the 2010 edition describes the topic “Structures with a risk of explosion” in more detail. Moreover, in Germany separate procedures and parameters are defined for the risk analysis of structures with a risk of explosion (Supplement 3 of the German DIN EN 62305-2 standard). This paper describes the contents and the relevant calculations of this Supplement 3, together with a numerical example.
Simulation and measurement of melting effects on metal sheets caused by direct lightning strikes
(1991)
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.
The downsizing of spark ignition engines in conjunction with turbocharging is considered to be a promising method for reducing CO₂ emissions. Using this concept, FEV has developed a new, highly efficient drivetrain to demonstrate fuel consumption reduction and drivability in a vehicle based on the Ford Focus ST. The newly designed 1.8L turbocharged gasoline engine incorporates infinitely variable intake and outlet control timing and direct fuel injection utilizing piezo injectors centrally located. In addition, this engine uses a prototype FEV engine control system, with software that was developed and adapted entirely by FEV. The vehicle features a 160 kW engine with a maximum mean effective pressure of 22.4 bar and 34 % savings in simulated fuel consumption. During the first stage, a new electrohydraulically actuated hybrid transmission with seven forward gears and one reverse gear and a single dry starting clutch will be integrated. The electric motor of the hybrid is directly connected to the gear set of the transmission. Utilizing the special gear set layout, the electric motor can provide boost during a change of gears, so that there is no interruption in traction. Therefore, the transmission system combines the advantages of a double clutch controlled gear change (gear change without an interruption in traction) with the efficient, cost-effective design of an automated manual transmission system. Additionally, the transmission provides a purely electric drive system and the operation of an air-conditioning compressor during the engine stop phases. One other alternative is through the use of CAI (Controlled Auto Ignition), which incorporates a process developed by FEV for controlled compression ignition.
SHEMAT-Suite: An open-source code for simulating flow, heat and species transport in porous media
(2020)
SHEMAT-Suite is a finite-difference open-source code for simulating coupled flow, heat and species transport in porous media. The code, written in Fortran-95, originates from geoscientific research in the fields of geothermics and hydrogeology. It comprises: (1) a versatile handling of input and output, (2) a modular framework for subsurface parameter modeling, (3) a multi-level OpenMP parallelization, (4) parameter estimation and data assimilation by stochastic approaches (Monte Carlo, Ensemble Kalman filter) and by deterministic Bayesian approaches based on automatic differentiation for calculating exact (truncation error-free) derivatives of the forward code.
The development and operation of hybrid or purely electrically powered aircraft in regional air mobility is a significant challenge for the entire aviation sector. This technology is expected to lead to substantial advances in flight performance, energy efficiency, reliability, safety, noise reduction, and exhaust emissions. Nevertheless, any consumed energy results in heat or carbon dioxide emissions and limited electric energy storage capabilities suppress commercial use. Therefore, the significant challenges to achieving eco-efficient aviation are increased aircraft efficiency, the development of new energy storage technologies, and the optimization of flight operations. Two major approaches for higher eco-efficiency are identified: The first one, is to take horizontal and vertical atmospheric motion phenomena into account. Where, in particular, atmospheric waves hold exciting potential. The second one is the use of the regeneration ability of electric aircraft. The fusion of both strategies is expected to improve efficiency. The objective is to reduce energy consumption during flight while not neglecting commercial usability and convenient flight characteristics. Therefore, an optimized control problem based on a general aviation class aircraft has to be developed and validated by flight experiments. The formulated approach enables a development of detailed knowledge of the potential and limitations of optimizing flight missions, considering the capability of regeneration and atmospheric influences to increase efficiency and range.
Humanized UGT2 and CYP3A transchromosomic rats for improved prediction of human drug metabolism
(2019)
Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.
Enzyme-based logic gates and circuits - analytical applications and interfacing with electronics
(2017)
The paper is an overview of enzyme-based logic gates and their short circuits, with specific examples of Boolean AND and OR gates, and concatenated logic gates composed of multi-step enzyme-biocatalyzed reactions. Noise formation in the biocatalytic reactions and its decrease by adding a “filter” system, converting convex to sigmoid response function, are discussed. Despite the fact that the enzyme-based logic gates are primarily considered as components of future biomolecular computing systems, their biosensing applications are promising for immediate practical use. Analytical use of the enzyme logic systems in biomedical and forensic applications is discussed and exemplified with the logic analysis of biomarkers of various injuries, e.g., liver injury, and with analysis of biomarkers characteristic of different ethnicity found in blood samples on a crime scene. Interfacing of enzyme logic systems with modified electrodes and semiconductor devices is discussed, giving particular attention to the interfaces functionalized with signal-responsive materials. Future perspectives in the design of the biomolecular logic systems and their applications are discussed in the conclusion.
Hydrophobic magnetic nanoparticles (NPs) consisting of undecanoate-capped magnetite (Fe3O4, average diameter ca. 5 nm) are used to control quantized electron transfer to surface-confined redox units and metal NPs. A two-phase system consisting of an aqueous electrolyte solution and a toluene phase that includes the suspended undecanoatecapped magnetic NPs is used to control the interfacial properties of the electrode surface. The attracted magnetic NPs form a hydrophobic layer on the electrode surface resulting in the change of the mechanisms of the surface-confined electrochemical processes. A quinone-monolayer modified Au electrode demonstrates an aqueous-type of the electrochemical process (2e-+2H+ redox mechanism) for the quinone units in the absence of the hydrophobic magnetic NPs, while the attraction of the magnetic NPs to the surface results in the stepwise single-electron transfer mechanism characteristic of a dry nonaqueous medium. Also, the attraction of the hydrophobic magnetic NPs to the Au electrode surface modified with Au NPs (ca. 1.4 nm) yields a microenvironment with a low dielectric constant that results in the single-electron quantum charging of the Au NPs.