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A laser-enhanced solar sail is a solar sail that is not solely propelled by solar radiation but additionally by a laser beam that illuminates the sail. This way, the propulsive acceleration of the sail results from the combined action of the solar and the laser radiation pressure onto the sail. The potential source of the laser beam is a laser satellite that coverts solar power (in the inner solar system) or nuclear power (in the outer solar system) into laser power. Such a laser satellite (or many of them) can orbit anywhere in the solar system and its optimal orbit (or their optimal orbits) for a given mission is a subject for future research. This contribution provides the model for an ideal laser-enhanced solar sail and investigates how a laser can enhance the thrusting capability of such a sail. The term ”ideal” means that the solar sail is assumed to be perfectly reflecting and that the laser beam is assumed to have a constant areal power density over the whole sail area. Since a laser beam has a limited divergence, it can provide radiation pressure at much larger solar distances and increase the radiation pressure force into the desired direction. Therefore, laser-enhanced solar sails may make missions feasible, that would otherwise have prohibitively long flight times, e.g. rendezvous missions in the outer solar system. This contribution will also analyze exemplary mission scenarios and present optimial trajectories without laying too much emphasis on the design and operations of the laser satellites. If the mission studies conclude that laser-enhanced solar sails would have advantages with respect to ”traditional” solar sails, a detailed study of the laser satellites and the whole system architecture would be the second next step
Despite the challenges of pioneering molten salt towers (MST), it remains the leading technology in central receiver power plants today, thanks to cost effective storage integration and high cost reduction potential. The limited controllability in volatile solar conditions can cause significant losses, which are difficult to estimate without comprehensive modeling [1]. This paper presents a Methodology to generate predictions of the dynamic behavior of the receiver system as part of an operating assistance system (OAS). Based on this, it delivers proposals if and when to drain and refill the receiver during a cloudy period in order maximize the net yield and quantifies the amount of net electricity gained by this. After prior analysis with a detailed dynamic two-phase model of the entire receiver system, two different reduced modeling approaches where developed and implemented in the OAS. A tailored decision algorithm utilizes both models to deliver the desired predictions efficiently and with appropriate accuracy.
The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle’s drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.
Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.
Modeling and upscaling of a pilot bayonettube reactor for indirect solar mixed methane reforming
(2020)
Modeling contribution to risk assessment of thermal production power for geothermal reservoirs
(2013)
The highly polymorphic human cytochrome P450 2D6 enzyme is involved in the metabolism of up to 25% of all marketed drugs and accounts for significant individual differences in response to CYP2D6 substrates. Because of the differences in the multiplicity and substrate specificity of CYP2D family members among species, it is difficult to predict pathways of human CYP2D6-dependent drug metabolism on the basis of animal studies. To create animal models that reflect the human situation more closely and that allow an in vivo assessment of the consequences of differential CYP2D6 drug metabolism, we have developed a novel straightforward approach to delete the entire murine Cyp2d gene cluster and replace it with allelic variants of human CYP2D6. By using this approach, we have generated mouse lines expressing the two frequent human protein isoforms CYP2D6.1 and CYP2D6.2 and an as yet undescribed variant of this enzyme, as well as a Cyp2d cluster knockout mouse. We demonstrate that the various transgenic mouse lines cover a wide spectrum of different human CYP2D6 metabolizer phenotypes. The novel humanization strategy described here provides a robust approach for the expression of different CYP2D6 allelic variants in transgenic mice and thus can help to evaluate potential CYP2D6-dependent interindividual differences in drug response in the context of personalized medicine.
Concentrated Solar Power (CSP) systems are able to store energy cost-effectively in their integrated thermal energy storage (TES). By intelligently combining Photovoltaics (PV) systems with CSP, a further cost reduction of solar power plants is expected, as well as an increase in dispatchability and flexibility of power generation. PV-powered Resistance Heaters (RH) can be deployed to raise the temperature of the molten salt hot storage from 385 °C up to 565 °C in a Parabolic Trough Collector (PTC) plant. To avoid freezing and decomposition of molten salt, the temperature distribution in the electrical resistance heater is investigated in the present study. For this purpose, a RH has been modeled and CFD simulations have been performed. The simulation results show that the hottest regions occur on the electric rod surface behind the last baffle. A technical optimization was performed by adjusting three parameters: Shell-baffle clearance, electric rod-baffle clearance and number of baffles. After the technical optimization was carried out, the temperature difference between the maximum temperature and the average outlet temperature of the salt is within the acceptable limits, thus critical salt decomposition has been avoided. Additionally, the CFD simulations results were analyzed and compared with results obtained with a one-dimensional model in Modelica.
Modeller for Value Systems
(1997)
The future of industrial manufacturing and production will increasingly manifest in the form of cyber-physical production systems. Here, Digital Shadows will act as mediators between the physical and digital world to model and operationalize the interactions and relationships between different entities in production systems. Until now, the associated concepts have been primarily pursued and implemented from a technocentric perspective, in which human actors play a subordinate role, if they are considered at all. This paper outlines an anthropocentric approach that explicitly considers the characteristics, behavior, and traits and states of human actors in socio-technical production systems. For this purpose, we discuss the potentials and the expected challenges and threats of creating and using Human Digital Shadows in production.
After menopause, decreased levels of estrogen and progesterone remodel the collagen of the soft tissues thereby reducing their stiffness. Stress urinary incontinence is associated with involuntary urine leakage due to pathological movement of the pelvic organs resulting from lax suspension system, fasciae, and ligaments. This study compares the changes in the orientation and position of the female pelvic organs due to weakened fasciae, ligaments, and their combined laxity. A mixture theory weighted by respective volume fraction of elastin-collagen fibre compound (5%), adipose tissue (85%), and smooth muscle (5%) is adopted to characterize the mechanical behaviour of the fascia. The load carrying response (other than the functional response to the pelvic organs) of each fascia component, pelvic organs, muscles, and ligaments are assumed to be isotropic, hyperelastic, and incompressible. Finite element simulations are conducted during Valsalva manoeuvre with weakened tissues modelled by reduced tissue stiffness. A significant dislocation of the urethrovesical junction is observed due to weakness of the fascia (13.89 mm) compared to the ligaments (5.47 mm). The dynamics of the pelvic floor observed in this study during Valsalva manoeuvre is associated with urethral-bladder hypermobility, greater levator plate angulation, and positive Q-tip test which are observed in incontinent females.
Modification and testing of an engine and fuel control system for a hydrogen fuelled gas turbine
(2011)
Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).
A multi-sensor system is a chemical sensor system which quantitatively and qualitatively records gases with a combination of cross-sensitive gas sensor arrays and pattern recognition software. This paper addresses the issue of data analysis for identification of gases in a gas sensor array. We introduce a software tool for gas sensor array configuration and simulation. It concerns thereby about a modular software package for the acquisition of data of different sensors. A signal evaluation algorithm referred to as matrix method was used specifically for the software tool. This matrix method computes the gas concentrations from the signals of a sensor array. The software tool was used for the simulation of an array of five sensors to determine gas concentration of CH4, NH3, H2, CO and C2H5OH. The results of the present simulated sensor array indicate that the software tool is capable of the following: (a) identify a gas independently of its concentration; (b) estimate the concentration of the gas, even if the system was not previously exposed to this concentration; (c) tell when a gas concentration exceeds a certain value. A gas sensor data base was build for the configuration of the software. With the data base one can create, generate and manage scenarios and source files for the simulation. With the gas sensor data base and the simulation software an on-line Web-based version was developed, with which the user can configure and simulate sensor arrays on-line.
Modulation of muscle-tendon interaction in the human triceps surae during an energy dissipation task
(2017)
Molecular Modeling Approach to the Prediction of Mechanical Properties of Silica-Reinforced Rubbers
(2014)
Recently, we have suggested a nanomechanical model for dissipative loss in filled elastomer networks in the context of the Payne effect. The mechanism is based on a total interfiller particle force exhibiting an intermittent loop, due to the combination of short-range repulsion and dispersion forces with a long-range elastic attraction. The sum of these forces leads, under external strain, to a spontaneous instability of “bonds” between the aggregates in a filler network and attendant energy dissipation. Here, we use molecular dynamics simulations to obtain chemically realistic forces between surface modified silica particles. The latter are combined with the above model to estimate the loss modulus and the low strain storage modulus in elastomers containing the aforementioned filler-compatibilizer systems. The model is compared to experimental dynamic moduli of silica filled rubbers. We find good agreement between the model predictions and the experiments as function of the compatibilizer's molecular structure and its bulk concentration.
Molecular-genetic identification of emerged novel invasive pathogens of Asiatic Elm Ulmus pumila L
(2014)
The dwarf elm Ulmus pumila L. (Ulmaceae) is one of indigenous species of flora in Kazakhstan and forms a basis of dendroflora in virtually all settlements of the region. In the past decade, multiple outbreaks of previously unknown diseases of the small-leaved elm have been registered. In our study, by the molecular-genetic analysis it was found that the pathogens responsible for the outbreaks are microfungi belonging to the genus Fusarium – F. solani and F. oxysporum. The nucleotide sequences (ITS regions) isolated from the diseased trees showed very high similarity with the GenBank control numbers EU625403.1 and FJ478128.1 (100.0 and 99.0 % respectively). Oncoming research will focus on the search of natural microbial antagonists of the discovered phytopathogens.
Cell-based sensors for the detection of gases have long been underrepresented, due to the cellular requirement of being cultured in a liquid environment. In this work we established a cell-based gas biosensor for the detection of toxic substances in air, by adapting a commercial sensor chip (Bionas®), previously used for the measurement of pollutants in liquids. Cells of the respiratory tract (A549, RPMI 2650, V79), which survive at a gas phase in a natural context, are used as biological receptors. The physiological cell parameters acidification, respiration and morphology are continuously monitored in parallel. Ammonia was used as a highly water-soluble model gas to test the feasibility of the sensor system. Infrared measurements confirmed the sufficiency of the medium draining method. This sensor system provides a basis for many sensor applications such as environmental monitoring, building technology and public security.
Designing novel or optimizing existing biodegradable polymers for biomedical applications requires numerous tests on the effect of substances on the degradation process. In the present work, polymer-modified electrolyte–insulator–semiconductor (PMEIS) sensors have been applied for monitoring an enzymatically catalyzed degradation of polymers for the first time. The thin films of biodegradable polymer poly(d,l-lactic acid) and enzyme lipase were used as a model system. During degradation, the sensors were read-out by means of impedance spectroscopy. In order to interpret the data obtained from impedance measurements, an electrical equivalent circuit model was developed. In addition, morphological investigations of the polymer surface have been performed by means of in situ atomic force microscopy. The sensor signal change, which reflects the progress of degradation, indicates an accelerated degradation in the presence of the enzyme compared to hydrolysis in neutral pH buffer media. The degradation rate increases with increasing enzyme concentration. The obtained results demonstrate the potential of PMEIS sensors as a very promising tool for in situ and real-time monitoring of degradation of polymers.
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.
Monte Carlo Tree Search (MCTS) is a search technique that in the last decade emerged as a major breakthrough for Artificial Intelligence applications regarding board- and video-games. In 2016, AlphaGo, an MCTS-based software agent, outperformed the human world champion of the board game Go. This game was for long considered almost infeasible for machines, due to its immense search space and the need for a long-term strategy. Since this historical success, MCTS is considered as an effective new approach for many other scientific and technical problems. Interestingly, civil structural engineering, as a discipline, offers many tasks whose solution may benefit from intelligent search and in particular from adopting MCTS as a search tool. In this work, we show how MCTS can be adapted to search for suitable solutions of a structural engineering design problem. The problem consists of choosing the load-bearing elements in a reference reinforced concrete structure, so to achieve a set of specific dynamic characteristics. In the paper, we report the results obtained by applying both a plain and a hybrid version of single-agent MCTS. The hybrid approach consists of an integration of both MCTS and classic Genetic Algorithm (GA), the latter also serving as a term of comparison for the results. The study’s outcomes may open new perspectives for the adoption of MCTS as a design tool for civil engineers.
For now, the Planetary Defense Conference Exercise 2021's incoming fictitious(!), asteroid, 2021 PDC, seems headed for impact on October 20th, 2021, exactly 6 months after its discovery. Today (April 26th, 2021), the impact probability is 5%, in a steep rise from 1 in 2500 upon discovery six days ago. We all know how these things end. Or do we? Unless somebody kicked off another headline-grabbing media scare or wants to keep civil defense very idle very soon, chances are that it will hit (note: this is an exercise!). Taking stock, it is barely 6 months to impact, a steadily rising likelihood that it will actually happen, and a huge uncertainty of possible impact energies: First estimates range from 1.2 MtTNT to 13 GtTNT, and this is not even the worst-worst case: a 700 m diameter massive NiFe asteroid (covered by a thin veneer of Ryugu-black rubble to match size and brightness), would come in at 70 GtTNT. In down to Earth terms, this could be all between smashing fireworks over some remote area of the globe and a 7.5 km crater downtown somewhere. Considering the deliberate and sedate ways of development of interplanetary missions it seems we can only stand and stare until we know well enough where to tell people to pack up all that can be moved at all and save themselves. But then, it could just as well be a smaller bright rock. The best estimate is 120 m diameter from optical observation alone, by 13% standard albedo. NASA's upcoming DART mission to binary asteroid (65803) Didymos is designed to hit such a small target, its moonlet Dimorphos. The Deep Impact mission's impactor in 2005 successfully guided itself to the brightest spot on comet 9P/Tempel 1, a relatively small feature on the 6 km nucleus. And 'space' has changed: By the end of this decade, one satellite communication network plans to have launched over 11000 satellites at a pace of 60 per launch every other week. This level of series production is comparable in numbers to the most prolific commercial airliners. Launch vehicle production has not simply increased correspondingly – they can be reused, although in a trade for performance. Optical and radio astronomy as well as planetary radar have made great strides in the past decade, and so has the design and production capability for everyday 'high-tech' products. 60 years ago, spaceflight was invented from scratch within two years, and there are recent examples of fast-paced space projects as well as a drive towards 'responsive space'. It seems it is not quite yet time to abandon all hope. We present what could be done and what is too close to call once thinking is shoved out of the box by a clear and present danger, to show where a little more preparedness or routine would come in handy – or become decisive. And if we fail, let's stand and stare safely and well instrumented anywhere on Earth together in the greatest adventure of science.
Motivation-based Learning: Teaching Fundamentals of Electrical Engineering with an LED Spinning Top
(2018)
Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.
Rugged terrain robot designs are important for field robotics missions. A number of commercial platforms are available, however, at an impressive price. In this paper, we describe the hardware and software component of a low-cost wheeled rugged-terrain robot. The robot is based on an electric children quad bike and is modified to be driven by wire. In terms of climbing properties, operation time and payload it can compete with some of the commercially available platforms, but at a far lower price.
This work describes a procedure to yield attenuation maps from MR images which are used for the absorption correction (AC) of brain PET data. Such an approach could be mandatory for future combined PET and MRI scanners, which probably do not include a transmission facility. T1-weighted MR images were segmented into brain tissue, bone, soft tissue, and sinus; attenuation coefficients corresponding to elemental composition and density as well as to 511 keV photon energy were respectively assigned. Attenuation maps containing up to four compartments were created and forward projected into sinograms with attenuation factors which then were used for AC during reconstruction of FDG-PET data. The commonly used AC based on a radioactive (68Ge) transmission scan served as reference. The reconstructed radioactivity values obtained with the MRI-based AC were about 20% lower than those obtained with PET-based AC if the skull was not taken into account. Considering the skull the difference was still about 10%. Our investigations demonstrate the feasibility of a MRI-based AC, but revealed also the necessity of a satisfying delineation of bone thickness which tends to be underestimated in our first approach of T1-weighted MR image segmentation.
Multi-attribute relation extraction (MARE): simplifying the application of relation extraction
(2021)
Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Multi-dimensional fragility analysis of a RC building with components using response surface method
(2017)
Conventional fragility curves describe the vulnerability of the main structure under external hazards. However, in complex structures such as nuclear power plants, the safety or the risk depends also on the components associated with a system. The classical fault tree analysis gives an overall view of the failure and contains several subsystems to the main event, however, the interactions in the subsystems are not well represented. In order to represent the interaction of the components, a method suggested by Cimellaro et al. (2006) using multidimensional performance limit state functions to obtain the system fragility curves is adopted. This approach gives the possibility of deriving the cumulative fragility taking into account the interaction of the response of different components. In this paper, this approach is used to evaluate seismic risk of a representative electrical building infrastructure, including the component, of a nuclear power plant. A simplified model of the structure, with nonlinear material behavior is employed for the analysis in Abaqus©. The input variables considered are the material parameters, boundary conditions and the seismic input. The variability of the seismic input is obtained from selected ground motion time histories of spectrum compatible synthetic ccelerograms. Unlike the usual Monte Carlo methods used for the probabilistic analysis of the structure, a computationally effective response surface method is used. This method reduces the computational effort of the calculations by reducing the required
number of samples.
Multi-interface level sensors and new development in monitoring and control of oil separators
(2006)
In the oil industry, huge saving may be made if suitable multi-interface level measurement systems are employed for effectively monitoring crude oil separators and efficient control of their operation. A number of techniques, e.g. externally mounted displacers, differential pressure transmitters and capacitance rod devices, have been developed to measure the separation process with gas, oil, water and other components. Because of the unavailability of suitable multi-interface level measurement systems, oil separators are currently operated by the trial-and-error approach. In this paper some conventional techniques, which have been used for level measurement in industry, and new development are discussed.
The optical performance of a 2-axis solar concentrator was simulated with the COMSOL Multiphysics® software. The concentrator consists of a mirror array, which was created using the application builder. The mirror facets are preconfigured to form a focal point. During tracking all mirrors are moved simultaneously in a coupled mode by 2 motors in two axes, in order to keep the system in focus with the moving sun. Optical errors on each reflecting surface were implemented in combination with the solar angular cone of ± 4.65 mrad. As a result, the intercept factor of solar radiation that is available to the receiver was calculated as a function of the transversal and longitudinal angles of incidence. In addition, the intensity distribution on the receiver plane was calculated as a function of the incidence angles.
Multi-parameter detection for supporting monitoring and control of biogas processes in agriculture
(2014)
High-k perovskite oxide of barium strontium titanate (BST) represents a very attractive multi-functional transducer material for the development of (bio-)chemical sensors. In this work, a Si-based sensor chip containing Pt interdigitated electrodes covered with a thin BST layer (485 nm) has been developed for multi-parameter chemical sensing. The chip has been applied for the contactless measurement of the electrolyte conductivity, the detection of adsorbed charged macromolecules (positively charged polyelectrolytes of polyethylenimine) and the concentration of hydrogen peroxide (H2O2) vapor. The experimental results of functional testing of individual sensors are presented. The mechanism of the BST sensitivity to charged polyelectrolytes and H2O2 vapor has been proposed and discussed.