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Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin’s molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6% and 12.9% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin’s molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems.
Fields of asymmetric tensors play an important role in many applications such as medical imaging (diffusion tensor magnetic resonance imaging), physics, and civil engineering (for example Cauchy-Green-deformation tensor, strain tensor with local rotations, etc.). However, such asymmetric tensors are usually symmetrized and then further processed. Using this procedure results in a loss of information. A new method for the processing of asymmetric tensor fields is proposed restricting our attention to tensors of second-order given by a 2x2 array or matrix with real entries. This is achieved by a transformation resulting in Hermitian matrices that have an eigendecomposition similar to symmetric matrices. With this new idea numerical results for real-world data arising from a deformation of an object by external forces are given. It is shown that the asymmetric part indeed contains valuable information.
Industrial facilities must be thoroughly designed to withstand seismic actions as they exhibit an increased loss potential due to the possibly wideranging damage consequences and the valuable process engineering equipment. Past earthquakes showed the social and political consequences of seismic damage to industrial facilities and sensitized the population and politicians worldwide for the possible hazard emanating from industrial facilities. However, a holistic approach for the seismic design of industrial facilities can presently neither be found in national nor in international standards. The introduction of EN 1998-4 of the new generation of Eurocode 8 will improve the normative situation with
specific seismic design rules for silos, tanks and pipelines and secondary process components. The article presents essential aspects of the seismic design of industrial facilities based on the new generation of Eurocode 8 using the example of tank structures and secondary process components. The interaction effects of the process components with the primary structure are illustrated by means of the experimental results of a shaking table test of a three story moment resisting steel frame with different process components. Finally, an integrated approach of
digital plant models based on building information modelling (BIM) and structural health monitoring (SHM) is presented, which provides not only a reliable decision-making basis for operation, maintenance and repair but also an excellent tool for rapid assessment of seismic damage.
Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current
state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.
The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.
The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.
This study investigated the anaerobic digestion of an algal–bacterial biofilm grown in artificial wastewater in an Algal Turf Scrubber (ATS). The ATS system was located in a greenhouse (50°54′19ʺN, 6°24′55ʺE, Germany) and was exposed to seasonal conditions during the experiment period. The methane (CH4) potential of untreated algal–bacterial biofilm (UAB) and thermally pretreated biofilm (PAB) using different microbial inocula was determined by anaerobic batch fermentation. Methane productivity of UAB differed significantly between microbial inocula of digested wastepaper, a mixture of manure and maize silage, anaerobic sewage sludge, and percolated green waste. UAB using sewage sludge as inoculum showed the highest methane productivity. The share of methane in biogas was dependent on inoculum. Using PAB, a strong positive impact on methane productivity was identified for the digested wastepaper (116.4%) and a mixture of manure and maize silage (107.4%) inocula. By contrast, the methane yield was significantly reduced for the digested anaerobic sewage sludge (50.6%) and percolated green waste (43.5%) inocula. To further evaluate the potential of algal–bacterial biofilm for biogas production in wastewater treatment and biogas plants in a circular bioeconomy, scale-up calculations were conducted. It was found that a 0.116 km2 ATS would be required in an average municipal wastewater treatment plant which can be viewed as problematic in terms of space consumption. However, a substantial amount of energy surplus (4.7–12.5 MWh a−1) can be gained through the addition of algal–bacterial biomass to the anaerobic digester of a municipal wastewater treatment plant. Wastewater treatment and subsequent energy production through algae show dominancy over conventional technologies.
The Solar-Institut Jülich (SIJ) and the companies Hilger GmbH and Heliokon GmbH from Germany have developed a small-scale cost-effective heliostat, called “micro heliostat”. Micro heliostats can be deployed in small-scale concentrated solar power (CSP) plants to concentrate the sun's radiation for electricity generation, space or domestic water heating or industrial process heat. In contrast to conventional heliostats, the special feature of a micro heliostat is that it consists of dozens of parallel-moving, interconnected, rotatable mirror facets. The mirror facets array is fixed inside a box-shaped module and is protected from weathering and wind forces by a transparent glass cover. The choice of the building materials for the box, tracking mechanism and mirrors is largely dependent on the selected production process and the intended application of the micro heliostat. Special attention was paid to the material of the tracking mechanism as this has a direct influence on the accuracy of the micro heliostat. The choice of materials for the mirror support structure and the tracking mechanism is made in favor of plastic molded parts. A qualification assessment method has been developed by the SIJ in which a 3D laser scanner is used in combination with a coordinate measuring machine (CMM). For the validation of this assessment method, a single mirror facet was scanned and the slope deviation was computed.
Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.
Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.
Edge-based and face-based smoothed finite element methods (ES-FEM and FS-FEM, respectively) are modified versions of the finite element method allowing to achieve more accurate results and to reduce sensitivity to mesh distortion, at least for linear elements. These properties make the two methods very attractive. However, their implementation in a standard finite element code is nontrivial because it requires heavy and extensive modifications to the code architecture. In this article, we present an element-based formulation of ES-FEM and FS-FEM methods allowing to implement the two methods in a standard finite element code with no modifications to its architecture. Moreover, the element-based formulation permits to easily manage any type of element, especially in 3D models where, to the best of the authors' knowledge, only tetrahedral elements are used in FS-FEM applications found in the literature. Shape functions for non-simplex 3D elements are proposed in order to apply FS-FEM to any standard finite element.
Non-intrusive measuring techniques have attained a lot of interest in relation to both hydraulic modeling and prototype applications. Complimenting acoustic techniques, significant progress has been made for the development of new optical methods. Computer vision techniques can help to extract new information, e. g. high-resolution velocity and depth data, from videos captured with relatively inexpensive, consumer-grade cameras. Depth cameras are sensors providing information on the distance between the camera and observed features. Currently, sensors with different working principles are available. Stereoscopic systems reference physical image features (passive system) from two perspectives; in order to enhance the number of features and improve the results, a sensor may also estimate the disparity from a detected light to its original projection (active stereo system). In the current study, the RGB-D camera Intel RealSense D435, working on such stereo vision principle, is used in different, typical hydraulic modeling applications. All tests have been conducted at the Utah Water Research Laboratory. This paper will demonstrate the performance and limitations of the RGB-D sensor, installed as a single camera and as camera arrays, applied to 1) detect the free surface for highly turbulent, aerated hydraulic jumps, for free-falling jets and for an energy dissipation basin downstream of a labyrinth weir and 2) to monitor local scours upstream and downstream of a Piano Key Weir. It is intended to share the authors’ experiences with respect to camera settings, calibration, lightning conditions and other requirements in order to promote this useful, easily accessible device. Results will be compared to data from classical instrumentation and the literature. It will be shown that even in difficult application, e. g. the detection of a highly turbulent, fluctuating free-surface, the RGB-D sensor may yield similar accuracy as classical, intrusive probes.
Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures.
The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality.
This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
Process mining gets more and more attention even outside large enterprises and can be a major benefit for small and medium sized enterprises (SMEs) to gain competitive advantages. Applying process mining is challenging, particularly for SMEs because they have less resources and process maturity. So far, IS researchers analyzed process mining challenges with a focus on larger companies. This paper investigates the application of process mining by means of a case study and sheds light into the particular challenges of an IT SME. The results reveal 13 SME process mining challenges and seven guidelines to address them. In this way, the paper contributes to the understanding of process mining application in SME and shows similarities and differences to larger companies.
A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived.
Eye movement modelling examples (EMME) are instructional videos that display a
teacher’s eye movements as “gaze cursor” (e.g. a moving dot) superimposed on the
learning task. This study investigated if previous findings on the beneficial effects of EMME would extend to online lecture videos and compared the effects of displaying the teacher’s gaze cursor with displaying the more traditional mouse cursor as a tool to guide learners’ attention. Novices (N = 124) studied a pre-recorded video lecture on how to model business processes in a 2 (mouse cursor absent/present) × 2 (gaze cursor absent/present) between-subjects design. Unexpectedly, we did not find significant effects of the presence of gaze or mouse cursors on mental effort and learning. However, participants who watched videos with the gaze cursor found it easier to follow the teacher. Overall, participants responded positively to the gaze cursor, especially when the mouse cursor was not displayed in the video.
Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing.
The fourth industrial revolution presents a multitude of challenges for industries, one of which being the increased flexibility required of manufacturing lines as a result of increased consumer demand for individualised products. One solution to tackle this challenge is the digital twin, more specifically the standardised model of a digital twin also known as the asset administration shell. The standardisation of an industry wide communications tool is a critical step in enabling inter-company operations. This paper discusses the current state of asset administration shells, the frameworks used to host them and their problems that need to be addressed. To tackle these issues, we propose an event-based server capable of drastically reducing response times between assets and asset administration shells and a multi-agent system used for the orchestration and deployment of the shells in the field.
The subtilase family (S8), a member of the clan SB of serine proteases are ubiquitous in all kingdoms of life and fulfil different physiological functions. Subtilases are divided in several groups and especially subtilisins are of interest as they are used in various industrial sectors. Therefore, we searched for new subtilisin sequences of the family Bacillaceae using a data mining approach. The obtained 1,400 sequences were phylogenetically classified in the context of the subtilase family. This required an updated comprehensive overview of the different groups within this family. To fill this gap, we conducted a phylogenetic survey of the S8 family with characterised holotypes derived from the MEROPS database. The analysis revealed the presence of eight previously uncharacterised groups and 13 subgroups within the S8 family. The sequences that emerged from the data mining with the set filter parameters were mainly assigned to the subtilisin subgroups of true subtilisins, high-alkaline subtilisins, and phylogenetically intermediate subtilisins and represent an excellent source for new subtilisin candidates.
Halophilic and halotolerant microorganisms represent a promising source of salt-tolerant enzymes suitable for various biotechnological applications where high salt concentrations would otherwise limit enzymatic activity. Considering the current growing enzyme market and the need for more efficient and new biocatalysts, the present study aimed at the characterization of a high-alkaline subtilisin from Alkalihalobacillus okhensis Kh10-101T. The protease gene was cloned and expressed in Bacillus subtilis DB104. The recombinant protease SPAO with 269 amino acids belongs to the subfamily of high-alkaline subtilisins. The biochemical characteristics of purified SPAO were analyzed in comparison with subtilisin Carlsberg, Savinase, and BPN'. SPAO, a monomer with a molecular mass of 27.1 kDa, was active over a wide range of pH 6.0–12.0 and temperature 20–80 °C, optimally at pH 9.0–9.5 and 55 °C. The protease is highly oxidatively stable to hydrogen peroxide and retained 58% of residual activity when incubated at 10 °C with 5% (v/v) H2O2 for 1 h while stimulated at 1% (v/v) H2O2. Furthermore, SPAO was very stable and active at NaCl concentrations up to 5.0 m. This study demonstrates the potential of SPAO for biotechnological applications in the future.
This dataset was acquired at field tests of the steerable ice-melting probe "EnEx-IceMole" (Dachwald et al., 2014). A field test in summer 2014 was used to test the melting probe's system, before the probe was shipped to Antarctica, where, in international cooperation with the MIDGE project, the objective of a sampling mission in the southern hemisphere summer 2014/2015 was to return a clean englacial sample from the subglacial brine reservoir supplying the Blood Falls at Taylor Glacier (Badgeley et al., 2017, German et al., 2021).
The standardized log-files generated by the IceMole during melting operation include more than 100 operational parameters, housekeeping information, and error states, which are reported to the base station in intervals of 4 s. Occasional packet loss in data transmission resulted in a sparse number of increased sampling intervals, which where compensated for by linear interpolation during post processing. The presented dataset is based on a subset of this data: The penetration distance is calculated based on the ice screw drive encoder signal, providing the rate of rotation, and the screw's thread pitch. The melting speed is calculated from the same data, assuming the rate of rotation to be constant over one sampling interval. The contact force is calculated from the longitudinal screw force, which es measured by strain gauges. The used heating power is calculated from binary states of all heating elements, which can only be either switched on or off. Temperatures are measured at each heating element and averaged for three zones (melting head, side-wall heaters and back-plate heaters).
In this study, the performance of an integrated body-imaging array for 7 T with 32 radiofrequency (RF) channels under consideration of local specific absorption rate (SAR), tissue temperature, and thermal dose limits was evaluated and the imaging performance was compared with a clinical 3 T body coil.
Thirty-two transmit elements were placed in three rings between the bore liner and RF shield of the gradient coil. Slice-selective RF pulse optimizations for B1 shimming and spokes were performed for differently oriented slices in the body under consideration of realistic constraints for power and local SAR. To improve the B1+ homogeneity, safety assessments based on temperature and thermal dose were performed to possibly allow for higher input power for the pulse optimization than permissible with SAR limits.
The results showed that using two spokes, the 7 T array outperformed the 3 T birdcage in all the considered regions of interest. However, a significantly higher SAR or lower duty cycle at 7 T is necessary in some cases to achieve similar B1+ homogeneity as at 3 T. The homogeneity in up to 50 cm-long coronal slices can particularly benefit from the high RF shim performance provided by the 32 RF channels. The thermal dose approach increases the allowable input power and the corresponding local SAR, in one example up to 100 W/kg, without limiting the exposure time necessary for an MR examination.
In conclusion, the integrated antenna array at 7 T enables a clinical workflow for body imaging and comparable imaging performance to a conventional 3 T clinical body coil.
Flexible fuel operation of a Dry-Low-NOx Micromix Combustor with Variable Hydrogen Methane Mixture
(2022)
The role of hydrogen (H2) as a carbon-free energy carrier is discussed since decades for reducing greenhouse gas emissions. As bridge technology towards a hydrogen-based energy supply, fuel mixtures of natural gas or methane (CH4) and hydrogen are possible.
The paper presents the first test results of a low-emission Micromix combustor designed for flexible-fuel operation with variable H2/CH4 mixtures. The numerical and experimental approach for considering variable fuel mixtures instead of recently investigated pure hydrogen is described.
In the experimental studies, a first generation FuelFlex Micromix combustor geometry is tested at atmospheric pressure at gas turbine operating conditions corresponding to part- and full-load. The H2/CH4 fuel mixture composition is varied between 57 and 100 vol.% hydrogen content.
Despite the challenges flexible-fuel operation poses onto the design of a combustion system, the evaluated FuelFlex Micromix prototype shows a significant low NOx performance
In general aviation, too, it is desirable to be able to operate existing internal combustion engines with fuels that produce less CO₂ than Avgas 100LL being widely used today It can be assumed that, in comparison, the fuels CNG, LPG or LNG, which are gaseous under normal conditions, produce significantly lower emissions. Necessary propulsion system adaptations were investigated as part of a research project at Aachen University of Applied Sciences.
Inference on the basis of high-dimensional and functional data are two topics which are discussed frequently in the current statistical literature. A possibility to include both topics in a single approach is working on a very general space for the underlying observations, such as a separable Hilbert space. We propose a general method for consistently hypothesis testing on the basis of random variables with values in separable Hilbert spaces. We avoid concerns with the curse of dimensionality due to a projection idea. We apply well-known test statistics from nonparametric inference to the projected data and integrate over all projections from a specific set and with respect to suitable probability measures. In contrast to classical methods, which are applicable for real-valued random variables or random vectors of dimensions lower than the sample size, the tests can be applied to random vectors of dimensions larger than the sample size or even to functional and high-dimensional data. In general, resampling procedures such as bootstrap or permutation are suitable to determine critical values. The idea can be extended to the case of incomplete observations. Moreover, we develop an efficient algorithm for implementing the method. Examples are given for testing goodness-of-fit in a one-sample situation in [1] or for testing marginal homogeneity on the basis of a paired sample in [2]. Here, the test statistics in use can be seen as generalizations of the well-known Cramérvon-Mises test statistics in the one-sample and two-samples case. The treatment of other testing problems is possible as well. By using the theory of U-statistics, for instance, asymptotic null distributions of the test statistics are obtained as the sample size tends to infinity. Standard continuity assumptions ensure the asymptotic exactness of the tests under the null hypothesis and that the tests detect any alternative in the limit. Simulation studies demonstrate size and power of the tests in the finite sample case, confirm the theoretical findings, and are used for the comparison with concurring procedures. A possible application of the general approach is inference for stock market returns, also in high data frequencies. In the field of empirical finance, statistical inference of stock market prices usually takes place on the basis of related log-returns as data. In the classical models for stock prices, i.e., the exponential Lévy model, Black-Scholes model, and Merton model, properties such as independence and stationarity of the increments ensure an independent and identically structure of the data. Specific trends during certain periods of the stock price processes can cause complications in this regard. In fact, our approach can compensate those effects by the treatment of the log-returns as random vectors or even as functional data.
On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.
In the past, CSP and PV have been seen as competing technologies. Despite massive reductions in the electricity generation costs of CSP plants, PV power generation is - at least during sunshine hours - significantly cheaper. If electricity is required not only during the daytime, but around the clock, CSP with its inherent thermal energy storage gets an advantage in terms of LEC. There are a few examples of projects in which CSP plants and PV plants have been co-located, meaning that they feed into the same grid connection point and ideally optimize their operation strategy to yield an overall benefit. In the past eight years, TSK Flagsol has developed a plant concept, which merges both solar technologies into one highly Integrated CSP-PV-Hybrid (ICPH) power plant. Here, unlike in simply co-located concepts, as analyzed e.g. in [1] – [4], excess PV power that would have to be dumped is used in electric molten salt heaters to increase the storage temperature, improving storage and conversion efficiency. The authors demonstrate the electricity cost sensitivity to subsystem sizing for various market scenarios, and compare the resulting optimized ICPH plants with co-located hybrid plants. Independent of the three feed-in tariffs that have been assumed, the ICPH plant shows an electricity cost advantage of almost 20% while maintaining a high degree of flexibility in power dispatch as it is characteristic for CSP power plants. As all components of such an innovative concept are well proven, the system is ready for commercial market implementation. A first project is already contracted and in early engineering execution.
The work presented in this report provides scientific support to building renovation policies in the EU by promoting a holistic point of view on the topic. Integrated renovation can be seen as a nexus between European policies on disaster resilience, energy efficiency and circularity in the building sector. An overview of policy measures for the seismic and energy upgrading of buildings across EU Member States identified only a few available measures for combined upgrading. Regulatory framework, financial instruments and digital tools similar to those for energy renovation, together with awareness and training may promote integrated renovation. A framework for regional prioritisation of building renovation was put forward, considering seismic risk, energy efficiency, and socioeconomic vulnerability independently and in an integrated way. Results indicate that prioritisation of building renovation is a multidimensional problem. Depending on priorities, different integrated indicators should be used to inform policies and accomplish the highest relative or most spread impact across different sectors. The framework was further extended to assess the impact of renovation scenarios across the EU with a focus on priority regions. Integrated renovation can provide a risk-proofed, sustainable, and inclusive built environment, presenting an economic benefit in the order of magnitude of the highest benefit among the separate interventions. Furthermore, it presents the unique capability of reducing fatalities and energy consumption at the same time and, depending on the scenario, to a greater extent.
An improved and convenient ninhydrin assay for aminoacylase activity measurements was developed using the commercial EZ Nin™ reagent. Alternative reagents from literature were also evaluated and compared. The addition of DMSO to the reagent enhanced the solubility of Ruhemann's purple (RP). Furthermore, we found that the use of a basic, aqueous buffer enhances stability of RP. An acidic protocol for the quantification of lysine was developed by addition of glacial acetic acid. The assay allows for parallel processing in a 96-well format with measurements microtiter plates.
Analysis and computation of the transmission eigenvalues with a conductive boundary condition
(2022)
We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber–Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.
The recently discovered first hyperbolic objects passing through the Solar System, 1I/’Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects. In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system. In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology. We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition. Their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy. These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system.
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.
Upcoming gasoline engines should run with a larger number of fuels beginning from petrol over methanol up to gas by a wide range of compression ratios and a homogeneous charge. In this article, the microwave (MW) spark plug, based on a high-speed frequency hopping system, is introduced as a solution, which can support a nitrogen compression ratio up to 1:39 in a chamber and more. First, an overview of the high-speed frequency hopping MW ignition and operation system as well as the large number of applications are presented. Both gives an understanding of this new base technology for MW plasma generation. Focus of the theoretical part is the explanation of the internal construction of the spark plug, on the achievable of the high voltage generation as well as the high efficiency to hold the plasma. In detail, the development process starting with circuit simulations and ending with the numerical multiphysics field simulations is described. The concept is evaluated with a reference prototype covering the frequency range between 2.40 and 2.48 GHz and working over a large power range from 20 to 200 W. A larger number of different measurements starting by vector hot-S11 measurements and ending by combined working scenarios out of hot temperature, high pressure and charge motion are winding up the article. The limits for the successful pressure tests were given by the pressure chamber. Pressures ranged from 1 to 39 bar and charge motion up to 25 m/s as well as temperatures from 30◦ to 125◦.
Industrial production systems are facing radical change in multiple dimensions. This change is caused by technological developments and the digital transformation of production, as well as the call for political and social change to facilitate a transformation toward sustainability. These changes affect both the capabilities of production systems and companies and the design of higher education and educational programs. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these concepts, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the capabilities dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we discuss the benefits of capturing expert knowledge and making it accessible to newcomers, especially in highly specialized industries. The experts argue that in order to cope with the challenges and circumstances of today’s world, students must already during their education at university learn how to work with AI and other technologies. This means that study programs must change and that universities must adapt their structural aspects to meet the needs of the students.
Carbon nanofiber nonwovens represent a powerful class of materials with prospective application in filtration technology or as electrodes with high surface area in batteries, fuel cells, and supercapacitors. While new precursor-to-carbon conversion processes have been explored to overcome productivity restrictions for carbon fiber tows, alternatives for the two-step thermal conversion of polyacrylonitrile precursors into carbon fiber nonwovens are absent. In this work, we develop a continuous roll-to-roll stabilization process using an atmospheric pressure microwave plasma jet. We explore the influence of various plasma-jet parameters on the morphology of the nonwoven and compare the stabilized nonwoven to thermally stabilized samples using scanning electron microscopy, differential scanning calorimetry, and infrared spectroscopy. We show that stabilization with a non-equilibrium plasma-jet can be twice as productive as the conventional thermal stabilization in a convection furnace, while producing electrodes of comparable electrochemical performance.
Atmospheric pressure plasma-jet treatment of PAN-nonwovens—carbonization of nanofiber electrodes
(2022)
Carbon nanofibers are produced from dielectric polymer precursors such as polyacrylonitrile (PAN). Carbonized nanofiber nonwovens show high surface area and good electrical conductivity, rendering these fiber materials interesting for application as electrodes in batteries, fuel cells, and supercapacitors. However, thermal processing is slow and costly, which is why new processing techniques have been explored for carbon fiber tows. Alternatives for the conversion of PAN-precursors into carbon fiber nonwovens are scarce. Here, we utilize an atmospheric pressure plasma jet to conduct carbonization of stabilized PAN nanofiber nonwovens. We explore the influence of various processing parameters on the conductivity and degree of carbonization of the converted nanofiber material. The precursor fibers are converted by plasma-jet treatment to carbon fiber nonwovens within seconds, by which they develop a rough surface making subsequent surface activation processes obsolete. The resulting carbon nanofiber nonwovens are applied as supercapacitor electrodes and examined by cyclic voltammetry and impedance spectroscopy. Nonwovens that are carbonized within 60 s show capacitances of up to 5 F g⁻¹.
Solar thermal concentrated power is an emerging technology that provides clean electricity for the growing energy market. To the solar thermal concentrated power plant systems belong the parabolic trough, the Fresnel collector, the solar dish, and the central receiver system.
For high-concentration solar collector systems, optical and thermal analysis is essential. There exist a number of measurement techniques and systems for the optical and thermal characterization of the efficiency of solar thermal concentrated systems.
For each system, structure, components, and specific characteristics types are described. The chapter presents additionally an outline for the calculation of system performance and operation and maintenance topics. One main focus is set to the models of components and their construction details as well as different types on the market. In the later part of this article, different criteria for the choice of technology are analyzed in detail.
Concentrating solar power
(2022)
The focus of this chapter is the production of power and the use of the heat produced from concentrated solar thermal power (CSP) systems.
The chapter starts with the general theoretical principles of concentrating systems including the description of the concentration ratio, the energy and mass balance. The power conversion systems is the main part where solar-only operation and the increase in operational hours.
Solar-only operation include the use of steam turbines, gas turbines, organic Rankine cycles and solar dishes. The operational hours can be increased with hybridization and with storage.
Another important topic is the cogeneration where solar cooling, desalination and of heat usage is described.
Many examples of commercial CSP power plants as well as research facilities from the past as well as current installed and in operation are described in detail.
The chapter closes with economic and environmental aspects and with the future potential of the development of CSP around the world.
Kawasaki Heavy Industries, Ltd. (KHI), Aachen University of Applied Sciences, and B&B-AGEMA GmbH have investigated the potential of low NOx micro-mix (MMX) hydrogen combustion and its application to an industrial gas turbine combustor. Engine demonstration tests of a MMX combustor for the M1A-17 gas turbine with a co-generation system were conducted in the hydrogen-fueled power generation plant in Kobe City, Japan.
This paper presents the results of the commissioning test and the combined heat and power (CHP) supply demonstration. In the commissioning test, grid interconnection, loading tests and load cut-off tests were successfully conducted. All measurement results satisfied the Japanese environmental regulation values. Dust and soot as well as SOx were not detected. The NOx emissions were below 84 ppmv at 15 % O2. The noise level at the site boundary was below 60 dB. The vibration at the site boundary was below 45 dB.
During the combined heat and power supply demonstration, heat and power were supplied to neighboring public facilities with the MMX combustion technology and 100 % hydrogen fuel. The electric power output reached 1800 kW at which the NOx emissions were 72 ppmv at 15 % O2, and 60 %RH. Combustion instabilities were not observed. The gas turbine efficiency was improved by about 1 % compared to a non-premixed type combustor with water injection as NOx reduction method. During a total equivalent operation time of 1040 hours, all combustor parts, the M1A-17 gas turbine as such, and the co-generation system were without any issues.
With proven impact of statistical fracture analysis on fracture classifications, it is desirable to minimize the manual work and to maximize repeatability of this approach. We address this with an algorithm that reduces the manual effort to segmentation, fragment identification and reduction. The fracture edge detection and heat map generation are performed automatically. With the same input, the algorithm always delivers the same output. The tool transforms one intact template consecutively onto each fractured specimen by linear least square optimization, detects the fragment edges in the template and then superimposes them to generate a fracture probability heat map.
We hypothesized that the algorithm runs faster than the manual evaluation and with low (< 5 mm) deviation. We tested the hypothesis in 10 fractured proximal humeri and found that it performs with good accuracy (2.5 mm ± 2.4 mm averaged Euclidean distance) and speed (23 times faster). When applied to a distal humerus, a tibia plateau, and a scaphoid fracture, the run times were low (1–2 min), and the detected edges correct by visual judgement. In the geometrically complex acetabulum, at a run time of 78 min some outliers were considered acceptable. An automatically generated fracture probability heat map based on 50 proximal humerus fractures matches the areas of high risk of fracture reported in medical literature.
Such automation of the fracture analysis method is advantageous and could be extended to reduce the manual effort even further.
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.
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.
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.
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.
Retinal vessels are similar to cerebral vessels in their structure and function. Moderately low oscillation frequencies of around 0.1 Hz have been reported as the driving force for paravascular drainage in gray matter in mice and are known as the frequencies of lymphatic vessels in humans. We aimed to elucidate whether retinal vessel oscillations are altered in Alzheimer's disease (AD) at the stage of dementia or mild cognitive impairment (MCI). Seventeen patients with mild-to-moderate dementia due to AD (ADD); 23 patients with MCI due to AD, and 18 cognitively healthy controls (HC) were examined using Dynamic Retinal Vessel Analyzer. Oscillatory temporal changes of retinal vessel diameters were evaluated using mathematical signal analysis. Especially at moderately low frequencies around 0.1 Hz, arterial oscillations in ADD and MCI significantly prevailed over HC oscillations and correlated with disease severity. The pronounced retinal arterial vasomotion at moderately low frequencies in the ADD and MCI groups would be compatible with the view of a compensatory upregulation of paravascular drainage in AD and strengthen the amyloid clearance hypothesis.
Lolium perenne (perennial ryegrass) is aproductive and high-quality forage grass indigenous to Southern Europe, temperate Asia, and North Africa. Nowadays it is widespread and the dominant grass species on green areas in temperate climates. This abundant source of biomass is suitable for the development of bioeconomic processes because of its high cellulose and water-soluble carbohydrate content. In this work, novel breeds of the perennial ryegrass are being examined with regards to their quality parameters and biotechnological utilization options within the context of bioeconomy. Three processing operations are presented. In the first process, the perennial ryegrass is pretreated by pressing or hydrothermal extraction to derive glucosevia subsequent enzymatic hydrolysis of cellulose. A yield of up to 82 % glucose was achieved when using the hydrothermal ex-traction as pretreatment. In a second process, the ryegrass is used to produce lactic acid in high concentrations. The influence of the growth conditions and the cutting time on the carboxylic acid yield is investigated. A yield of lactic acid of above 150 g kg⁻¹ dry matter was achieved. The third process is to use Lolium perenne as a substrate in the fermentation of K. marxianus for the microbial production of single-cell proteins. The perennial ryegrass is screw-pressed and the press juice is used as medium. When supplementing the press juice with yeast media components, a biomass concentration of up to 16 g L⁻¹ could be achieved.
The replacement of existing spillway crests or gates with labyrinth weirs is a proven techno-economical means to increase the discharge capacity when rehabilitating existing structures. However, additional information is needed regarding energy dissipation of such weirs, since due to the folded weir crest, a three-dimensional flow field is generated, yielding more complex overflow and energy dissipation processes. In this study, CFD simulations of labyrinth weirs were conducted 1) to analyze the discharge coefficients for different discharges to compare the Cd values to literature data and 2) to analyze and improve energy dissipation downstream of the structure. All tests were performed for a structure at laboratory scale with a height of approx. P = 30.5 cm, a ratio of the total crest length to the total width of 4.7, a sidewall angle of 10° and a quarter-round weir crest shape. Tested headwater ratios were 0.089 ≤ HT/P ≤ 0.817. For numerical simulations, FLOW-3D Hydro was employed, solving the RANS equations with use of finite-volume method and RNG k-ε turbulence closure. In terms of discharge capacity, results were compared to data from physical model tests performed at the Utah Water Research Laboratory (Utah State University), emphasizing higher discharge coefficients from CFD than from the physical model. For upstream heads, some discrepancy in the range of ± 1 cm between literature, CFD and physical model tests was identified with a discussion regarding differences included in the manuscript. For downstream energy dissipation, variable tailwater depths were considered to analyze the formation and sweep-out of a hydraulic jump. It was found that even for high discharges, relatively low downstream Froude numbers were obtained due to high energy dissipation involved by the three-dimensional flow between the sidewalls. The effects of some additional energy dissipation devices, e.g. baffle blocks or end sills, were also analyzed. End sills were found to be non-effective. However, baffle blocks with different locations may improve energy dissipation downstream of labyrinth weirs.
Introduction
In regard of surgical training, the reproducible simulation of life-like proximal humerus fractures in human cadaveric specimens is desirable. The aim of the present study was to develop a technique that allows simulation of realistic proximal humerus fractures and to analyse the influence of rotator cuff preload on the generated lesions in regards of fracture configuration.
Materials and methods
Ten cadaveric specimens (6 left, 4 right) were fractured using a custom-made drop-test bench, in two groups. Five specimens were fractured without rotator cuff preload, while the other five were fractured with the tendons of the rotator cuff preloaded with 2 kg each. The humeral shaft and the shortened scapula were potted. The humerus was positioned at 90° of abduction and 10° of internal rotation to simulate a fall on the elevated arm. In two specimens of each group, the emergence of the fractures was documented with high-speed video imaging. Pre-fracture radiographs were taken to evaluate the deltoid-tuberosity index as a measure of bone density. Post-fracture X-rays and CT scans were performed to define the exact fracture configurations. Neer’s classification was used to analyse the fractures.
Results
In all ten cadaveric specimens life-like proximal humerus fractures were achieved. Two III-part and three IV-part fractures resulted in each group. The preloading of the rotator cuff muscles had no further influence on the fracture configuration. High-speed videos of the fracture simulation revealed identical fracture mechanisms for both groups. We observed a two-step fracture mechanism, with initial impaction of the head segment against the glenoid followed by fracturing of the head and the tuberosities and then with further impaction of the shaft against the acromion, which lead to separation of the tuberosities.
Conclusion
A high energetic axial impulse can reliably induce realistic proximal humerus fractures in cadaveric specimens. The preload of the rotator cuff muscles had no influence on initial fracture configuration. Therefore, fracture simulation in the proximal humerus is less elaborate. Using the presented technique, pre-fractured specimens are available for real-life surgical education.
Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.
Technical assessment of Brayton cycle heat pumps for the integration in hybrid PV-CSP power plants
(2022)
The hybridization of Concentrated Solar Power (CSP) and Photovoltaics (PV) systems is a promising approach to reduce costs of solar power plants, while increasing dispatchability and flexibility of power generation. High temperature heat pumps (HT HP) can be utilized to boost the salt temperature in the thermal energy storage (TES) of a Parabolic Trough Collector (PTC) system from 385 °C up to 565 °C. A PV field can supply the power for the HT HP, thus effectively storing the PV power as thermal energy. Besides cost-efficiently storing energy from the PV field, the power block efficiency of the overall system is improved due to the higher steam parameters. This paper presents a technical assessment of Brayton cycle heat pumps to be integrated in hybrid PV-CSP power plants. As a first step, a theoretical analysis was carried out to find the most suitable working fluid. The analysis included the fluids Air, Argon (Ar), Nitrogen (N2) and Carbon dioxide (CO2). N2 has been chosen as the optimal working fluid for the system. After the selection of the ideal working medium, different concepts for the arrangement of a HT HP in a PV-CSP hybrid power plant were developed and simulated in EBSILON®Professional. The concepts were evaluated technically by comparing the number of components required, pressure losses and coefficient of performance (COP).
Introduction: In peripheral percutaneous (VA) extracorporeal membrane oxygenation (ECMO) procedures the femoral arteries perfusion route has inherent disadvantages regarding poor upper body perfusion due to watershed. With the advent of new long flexible cannulas an advancement of the tip up to the ascending aorta has become feasible. To investigate the impact of such long endoluminal cannulas on upper body perfusion, a Computational Fluid Dynamics (CFD) study was performed considering different support levels and three cannula positions.
Methods: An idealized literature-based- and a real patient proximal aortic geometry including an endoluminal cannula were constructed. The blood flow was considered continuous. Oxygen saturation was set to 80% for the blood coming from the heart and to 100% for the blood leaving the cannula. 50% and 90% venoarterial support levels from the total blood flow rate of 6 l/min were investigated for three different positions of the cannula in the aortic arch.
Results: For both geometries, the placement of the cannula in the ascending aorta led to a superior oxygenation of all aortic blood vessels except for the left coronary artery. Cannula placements at the aortic arch and descending aorta could support supra-aortic arteries, but not the coronary arteries. All positions were able to support all branches with saturated blood at 90% flow volume.
Conclusions: In accordance with clinical observations CFD analysis reveals, that retrograde advancement of a long endoluminal cannula can considerably improve the oxygenation of the upper body and lead to oxygen saturation distributions similar to those of a central cannulation.
Wearable EEG has gained popularity in recent years driven by promising uses outside of clinics and research. The ubiquitous application of continuous EEG requires unobtrusive form-factors that are easily acceptable by the end-users. In this progression, wearable EEG systems have been moving from full scalp to forehead and recently to the ear. The aim of this study is to demonstrate that emerging ear-EEG provides similar impedance and signal properties as established forehead EEG. EEG data using eyes-open and closed alpha paradigm were acquired from ten healthy subjects using generic earpieces fitted with three custom-made electrodes and a forehead electrode (at Fpx) after impedance analysis. Inter-subject variability in in-ear electrode impedance ranged from 20 kΩ to 25 kΩ at 10 Hz. Signal quality was comparable with an SNR of 6 for in-ear and 8 for forehead electrodes. Alpha attenuation was significant during the eyes-open condition in all in-ear electrodes, and it followed the structure of power spectral density plots of forehead electrodes, with the Pearson correlation coefficient of 0.92 between in-ear locations ELE (Left Ear Superior) and ERE (Right Ear Superior) and forehead locations, Fp1 and Fp2, respectively. The results indicate that in-ear EEG is an unobtrusive alternative in terms of impedance, signal properties and information content to established forehead EEG.
Damage of reinforced concrete (RC) frames with masonry infill walls has been observed after many earthquakes. Brittle behaviour of the masonry infills in combination with the ductile behaviour of the RC frames makes infill walls prone to damage during earthquakes. Interstory deformations lead to an interaction between the infill and the RC frame, which affects the structural response. The result of this interaction is significant damage to the infill wall and sometimes to the surrounding structural system too. In most design codes, infill walls are considered as non-structural elements and neglected in the design process, because taking into account the infills and considering the interaction between frame and infill in software packages can be complicated and impractical. A good way to avoid negative aspects arising from this behavior is to ensure no or low-interaction of the frame and infill wall, for instance by decoupling the infill from the frame. This paper presents the numerical study performed to investigate new connection system called INODIS (Innovative Decoupled Infill System) for decoupling infill walls from surrounding frame with the aim to postpone infill activation to high interstory drifts thus reducing infill/frame interaction and minimizing damage to both infills and frames. The experimental results are first used for calibration and validation of the numerical model, which is then employed for investigating the influence of the material parameters as well as infill’s and frame’s geometry on the in-plane behaviour of the infilled frames with the INODIS system. For all the investigated situations, simulation results show significant improvements in behaviour for decoupled infilled RC frames in comparison to the traditionally infilled frames.
Because of simple construction process, high energy efficiency, significant fire resistance and excellent sound isolation, masonry infilled reinforced concrete (RC) frame structures are very popular in most of the countries in the world, as well as in seismic active areas. However, many RC frame structures with masonry infills were seriously damaged during earthquake events, as the traditional infills are generally constructed with direct contact to the RC frame which brings undesirable infill/frame interaction. This interaction leads to the activation of the equivalent diagonal strut in the infill panel, due to the RC frame deformation, and combined with seismically induced loads perpendicular to the infill panel often causes total collapses of the masonry infills and heavy damages to the RC frames. This fact was the motivation for developing different approaches for improving the behaviour of masonry infills, where infill isolation (decoupling) from the frame has been more intensively studied in the last decade. In-plane isolation of the infill wall reduces infill activation, but causes the need for additional measures to restrain out-of-plane movements. This can be provided by installing steel anchors, as proposed by some researchers. Within the framework of European research project INSYSME (Innovative Systems for Earthquake Resistant Masonry Enclosures in Reinforced Concrete Buildings) the system based on a use of elastomers for in-plane decoupling and steel anchors for out-of-plane restrain was tested. This constructive solution was tested and deeply investigated during the experimental campaign where traditional and decoupled masonry infilled RC frames with anchors were subjected to separate and combined in-plane and out-of-plane loading. Based on a detailed evaluation and comparison of the test results, the performance and effectiveness of the developed system are illustrated.
Useful market simulations are key to the evaluation of diferent market designs existing of multiple market mechanisms or rules. Yet a simulation framework which has a comparison of diferent market mechanisms in mind was not found. The need to create an objective view on different sets of market rules while investigating meaningful agent strategies concludes that such a simulation framework is needed to advance the research on this subject. An overview of diferent existing market simulation models is given which also shows the research gap and the missing capabilities of those systems. Finally, a methodology is outlined how a novel market simulation which can answer the research questions can be developed.
Electric flight has the potential for a more sustainable and energy-saving way of aviation compared to fossil fuel aviation. The electric motor can be used as a generator inflight to regenerate energy during descent. Three different approaches to regenerating with electric propeller powertrains are proposed in this paper. The powertrain is to be set up in a wind tunnel to determine the propeller efficiency in both working modes as well as the noise emissions. Furthermore, the planned flight tests are discussed. In preparation for these tests, a yaw stability analysis is performed with the result that the aeroplane is controllable during flight and in the most critical failure case. The paper shows the potential for inflight regeneration and addresses the research gaps in the dual role of electric powertrains for propulsion and regeneration of general aviation aircraft.
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.
Masonry infill walls are the most traditional enclosure system that is still widely used in RC frame buildings all over the world, particularly in seismic active regions. Although infill walls are usually neglected in seismic design, during an earthquake event they are subjected to in-plane and out-of-plane forces that can act separately or simultaneously. Since observations of damage to buildings after recent earthquakes showed detrimental effects of in-plane and out-of-plane load interaction on infill walls, the number of studies that focus on influence of in-plane damage on out-of-plane response has significantly increased. However, most of the xperimental campaigns have considered only solid infills and there is a lack of combined in-plane and out-of-plane experimental tests on masonry infills with openings, although windows and doors strongly affect seismic performance. In this paper, two types of experimental tests on infills with window openings are presented. The first is a pure out-of-plane test and the second one is a sequential in-plane and out-of-plane test aimed at investigating the effects of existing in-plane damage on outof-plane response. Additionally, findings from two tests with similar load procedure that were carried out on fully infilled RC frames in the scope of the same project are used for comparison. Test results clearly show that window opening increased vulnerability of infills to combined seismic actions and that prevention of damage in infills with openings is of the utmost importance for seismic safety.
Miniaturized electrolyte–insulator–semiconductor capacitors (EISCAPs) with ultrathin gate insulators have been studied in terms of their pH-sensitive sensor characteristics: three different EISCAP systems consisting of Al–p-Si–Ta2O5(5 nm), Al–p-Si–Si3N4(1 or 2 nm)–Ta2O5 (5 nm), and Al–p-Si–SiO2(3.6 nm)–Ta2O5(5 nm) layer structures are characterized in buffer solution with different pH values by means of capacitance–voltage and constant capacitance method. The SiO2 and Si3N4 gate insulators are deposited by rapid thermal oxidation and rapid thermal nitridation, respectively, whereas the Ta2O5 film is prepared by atomic layer deposition. All EISCAP systems have a clear pH response, favoring the stacked gate insulators SiO2–Ta2O5 when considering the overall sensor characteristics, while the Si3N4(1 nm)–Ta2O5 stack delivers the largest accumulation capacitance (due to the lower equivalent oxide thickness) and a higher steepness in the slope of the capacitance–voltage curve among the studied stacked gate insulator systems.
This study addresses a proof-of-concept experiment with a biocompatible screen-printed carbon electrode deposited onto a biocompatible and biodegradable substrate, which is made of fibroin, a protein derived from silk of the Bombyx mori silkworm. To demonstrate the sensor performance, the carbon electrode is functionalized as a glucose biosensor with the enzyme glucose oxidase and encapsulated with a silicone rubber to ensure biocompatibility of the contact wires. The carbon electrode is fabricated by means of thick-film technology including a curing step to solidify the carbon paste. The influence of the curing temperature and curing time on the electrode morphology is analyzed via scanning electron microscopy. The electrochemical characterization of the glucose biosensor is performed by amperometric/voltammetric measurements of different glucose concentrations in phosphate buffer. Herein, systematic studies at applied potentials from 500 to 1200 mV to the carbon working electrode (vs the Ag/AgCl reference electrode) allow to determine the optimal working potential. Additionally, the influence of the curing parameters on the glucose sensitivity is examined over a time period of up to 361 days. The sensor shows a negligible cross-sensitivity toward ascorbic acid, noradrenaline, and adrenaline. The developed biocompatible biosensor is highly promising for future in vivo and epidermal applications.
NMR standardization approach that uses the 2H integral of deuterated solvent for quantitative multinuclear analysis of pharmaceuticals is described. As a proof of principle, the existing NMR procedure for the analysis of heparin products according to US Pharmacopeia monograph is extended to the determination of Na+ and Cl- content in this matrix. Quantification is performed based on the ratio of a 23Na (35Cl) NMR integral and 2H NMR signal of deuterated solvent, D2O, acquired using the specific spectrometer hardware. As an alternative, the possibility of 133Cs standardization using the addition of Cs2CO3 stock solution is shown. Validation characteristics (linearity, repeatability, sensitivity) are evaluated. A holistic NMR profiling of heparin products can now also be used for the quantitative determination of inorganic compounds in a single analytical run using a single sample. In general, the new standardization methodology provides an appealing alternative for the NMR screening of inorganic and organic components in pharmaceutical products.
Nuclear magnetic resonance (NMR) spectrometric methods for the quantitative analysis of pure heparin in crude heparin is proposed. For quantification, a two-step routine was developed using a USP heparin reference sample for calibration and benzoic acid as an internal standard. The method was successfully validated for its accuracy, reproducibility, and precision. The methodology was used to analyze 20 authentic porcine heparinoid samples having heparin content between 4.25 w/w % and 64.4 w/w %. The characterization of crude heparin products was further extended to a simultaneous analysis of these common ions: sodium, calcium, acetate and chloride. A significant, linear dependence was found between anticoagulant activity and assayed heparin content for thirteen heparinoids samples, for which reference data were available. A Diffused-ordered NMR experiment (DOSY) can be used for qualitative analysis of specific glycosaminoglycans (GAGs) in heparinoid matrices and, potentially, for quantitative prediction of molecular weight of GAGs. NMR spectrometry therefore represents a unique analytical method suitable for the simultaneous quantitative control of organic and inorganic composition of crude heparin samples (especially heparin content) as well as an estimation of other physical and quality parameters (molecular weight, animal origin and activity).
Heparin is a natural polysaccharide, which plays essential role in many biological processes. Alterations in building blocks can modify biological roles of commercial heparin products, due to significant changes in the conformation of the polymer chain. The variability structure of heparin leads to difficulty in quality control using different analytical methods, including infrared (IR) spectroscopy. In this paper molecular modelling of heparin disaccharide subunits was performed using quantum chemistry. The structural and spectral parameters of these disaccharides have been calculated using RHF/6-311G. In addition, over-sulphated chondroitin sulphate disaccharide was studied as one of the most widespread contaminants of heparin. Calculated IR spectra were analyzed with respect to specific structure parameters. IR spectroscopic fingerprint was found to be sensitive to substitution pattern of disaccharide subunits. Vibrational assignments of calculated spectra were correlated with experimental IR spectral bands of native heparin. Chemometrics was used to perform multivariate analysis of simulated spectral data.
Recent earthquakes as the 2012 Emilia earthquake sequence showed that recently built unreinforced masonry (URM) buildings behaved much better than expected and sustained, despite the maximum PGA values ranged between 0.20–0.30 g, either minor damage or structural damage that is deemed repairable. Especially low-rise residential and commercial masonry buildings with a code-conforming seismic design and detailing behaved in general very well without substantial damages. The low damage grades of modern masonry buildings that was observed during this earthquake series highlighted again that codified design procedures based on linear analysis can be rather conservative. Although advances in simulation tools make nonlinear calculation methods more readily accessible to designers, linear analyses will still be the standard design method for years to come. The present paper aims to improve the linear seismic design method by providing a proper definition of the q-factor of URM buildings. These q-factors are derived for low-rise URM buildings with rigid diaphragms which represent recent construction practise in low to moderate seismic areas of Italy and Germany. The behaviour factor components for deformation and energy dissipation capacity and for overstrength due to the redistribution of forces are derived by means of pushover analyses. Furthermore, considerations on the behaviour factor component due to other sources of overstrength in masonry buildings are presented. As a result of the investigations, rationally based values of the behaviour factor q to be used in linear analyses in the range of 2.0–3.0 are proposed.
Recent earthquakes showed that low-rise URM buildings following codecompliant seismic design and details behaved in general very well without substantial damages. Although advances in simulation tools make nonlinear calculation methods more readily accessible to designers, linear analyses will still be the standard design method for years to come. The present paper aims to improve the linear seismic design method by providing a proper definition of the q-factor of URM buildings. Values of q-factors are derived for low-rise URM buildings with rigid diaphragms, with reference to modern structural configurations realized in low to moderate seismic areas of Italy and Germany. The behaviour factor components for deformation and energy dissipation capacity and for overstrength due to the redistribution of forces are derived by means of pushover analyses. As a result of the investigations, rationally based values of the behaviour factor q to be used in linear analyses in the range of 2.0 to 3.0 are proposed.
Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.
New materials often lead to innovations and advantages in technical applications. This also applies to the particle receiver proposed in this work that deploys high-temperature and scratch resistant transparent ceramics. With this receiver design, particles are heated through direct-contact concentrated solar irradiance while flowing downwards through tubular transparent ceramics from top to bottom. In this paper, the developed particle receiver as well as advantages and disadvantages are described. Investigations on the particle heat-up characteristics from solar irradiance were carried out with DEM simulations which indicate that particle temperatures can reach up to 1200 K. Additionally, a simulation model was set up for investigating the dynamic behavior. A test receiver at laboratory scale has been designed and is currently being built. In upcoming tests, the receiver test rig will be used to validate the simulation results. The design and the measurement equipment is described in this work.
We present a concise mini overview on the approaches to the disposal of nuclear waste currently used or deployed. The disposal of nuclear waste is the end point of nuclear waste management (NWM) activities and is the emplacement of waste in an appropriate facility without the intention to retrieve it. The IAEA has developed an internationally accepted classification scheme based on the end points of NWM, which is used as guidance. Retention times needed for safe isolation of waste radionuclides are estimated based on the radiotoxicity of nuclear waste. Disposal facilities usually rely on a multi-barrier defence system to isolate the waste from the biosphere, which comprises the natural geological barrier and the engineered barrier system. Disposal facilities could be of a trench type, vaults, tunnels, shafts, boreholes, or mined repositories. A graded approach relates the depth of the disposal facilities’ location with the level of hazard. Disposal practices demonstrate the reliability of nuclear waste disposal with minimal expected impacts on the environment and humans.
This paper covers the use of the magnetic Wiegand effect to design an innovative incremental encoder. First, a theoretical design is given, followed by an estimation of the achievable accuracy and an optimization in open-loop operation.
Finally, a successful experimental verification is presented. For this purpose, a permanent magnet synchronous machine is controlled in a field-oriented manner, using the angle information of the prototype.
GHEtool is a Python package that contains all the functionalities needed to deal with borefield design. It is developed for both researchers and practitioners. The core of this package is the automated sizing of borefield under different conditions. The sizing of a borefield is typically slow due to the high complexity of the mathematical background. Because this tool has a lot of precalculated data, GHEtool can size a borefield in the order of tenths of milliseconds. This sizing typically takes the order of minutes. Therefore, this tool is suited for being implemented in typical workflows where iterations are required.
GHEtool also comes with a graphical user interface (GUI). This GUI is prebuilt as an exe-file because this provides access to all the functionalities without coding. A setup to install the GUI at the user-defined place is also implemented and available at: https://www.mech.kuleuven.be/en/tme/research/thermal_systems/tools/ghetool.
In proton therapy, the dose from secondary neutrons to the patient can contribute to side effects and the creation of secondary cancer. A simple and fast detection system to distinguish between dose from protons and neutrons both in pretreatment verification as well as potentially in vivo monitoring is needed to minimize dose from secondary neutrons. Two 3 mm long, 1 mm diameter organic scintillators were tested for candidacy to be used in a proton–neutron discrimination detector. The SCSF-3HF (1500) scintillating fibre (Kuraray Co. Chiyoda-ku, Tokyo, Japan) and EJ-260 plastic scintillator (Eljen Technology, Sweetwater, TX, USA) were irradiated at the TRIUMF Neutron Facility and the Proton Therapy Research Centre. In the proton beam, we compared the raw Bragg peak and spread-out Bragg peak response to the industry standard Markus chamber detector. Both scintillator sensors exhibited quenching at high LET in the Bragg peak, presenting a peak-to-entrance ratio of 2.59 for the EJ-260 and 2.63 for the SCSF-3HF fibre, compared to 3.70 for the Markus chamber. The SCSF-3HF sensor demonstrated 1.3 times the sensitivity to protons and 3 times the sensitivity to neutrons as compared to the EJ-260 sensor. Combined with our equations relating neutron and proton contributions to dose during proton irradiations, and the application of Birks’ quenching correction, these fibres provide valid candidates for inexpensive and replicable proton-neutron discrimination detectors
This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual
labour and increased productivity.
Image reconstruction analysis for positron emission tomography with heterostructured scintillators
(2022)
The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0×3.1×15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32% for 100 μm thick plastic layers and 52% for 50 μm, the CTR distribution improved to 204±49 ps and 220±41 ps respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On a NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast to noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses.
Nanoparticles are recognized as highly attractive tunable materials for designing field-effect biosensors with enhanced performance. In this work, we present a theoretical model for electrolyte-insulator-semiconductor capacitors (EISCAP) decorated with ligand-stabilized charged gold nanoparticles. The charged AuNPs are taken into account as additional, nanometer-sized local gates. The capacitance-voltage (C–V) curves and constant-capacitance (ConCap) signals of the AuNP-decorated EISCAPs have been simulated. The impact of the AuNP coverage on the shift of the C–V curves and the ConCap signals was also studied experimentally on Al–p-Si–SiO₂ EISCAPs decorated with positively charged aminooctanethiol-capped AuNPs. In addition, the surface of the EISCAPs, modified with AuNPs, was characterized by scanning electron microscopy for different immobilization times of the nanoparticles.
Frequency mixing magnetic detection (FMMD) has been explored for its applications in fields of magnetic biosensing, multiplex detection of magnetic nanoparticles (MNP) and the determination of core size distribution of MNP samples. Such applications rely on the application of a static offset magnetic field, which is generated traditionally with an electromagnet. Such a setup requires a current source, as well as passive or active cooling strategies, which directly sets a limitation based on the portability aspect that is desired for point of care (POC) monitoring applications. In this work, a measurement head is introduced that involves the utilization of two ring-shaped permanent magnets to generate a static offset magnetic field. A steel cylinder in the ring bores homogenizes the field. By variation of the distance between the ring magnets and of the thickness of the steel cylinder, the magnitude of the magnetic field at the sample position can be adjusted. Furthermore, the measurement setup is compared to the electromagnet offset module based on measured signals and temperature behavior.
Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as “colourization”) of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples’ total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization.
An interdisciplinary view on humane interfaces for digital shadows in the internet of production
(2022)
Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers’ capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization.
This study aims to quantify the kinematics, kinetics and muscular activity of all-out handcycling exercise and examine their alterations during the course of a 15-s sprint test. Twelve able-bodied competitive triathletes performed a 15-s all-out sprint test in a recumbent racing handcycle that was attached to an ergometer. During the sprint test, tangential crank kinetics, 3D joint kinematics and muscular activity of 10 muscles of the upper extremity and trunk were examined using a power metre, motion capturing and surface electromyography (sEMG), respectively. Parameters were compared between revolution one (R1), revolution two (R2), the average of revolution 3 to 13 (R3) and the average of the remaining revolutions (R4). Shoulder abduction and internal-rotation increased, whereas maximal shoulder retroversion decreased during the sprint. Except for the wrist angles, angular velocity increased for every joint of the upper extremity. Several muscles demonstrated an increase in muscular activation, an earlier onset of muscular activation in crank cycle and an increased range of activation. During the course of a 15-s all-out sprint test in handcycling, the shoulder muscles and the muscles associated to the push phase demonstrate indications for short-duration fatigue. These findings are helpful to prevent injuries and improve performance in all-out handcycling.
The seismic performance and safety of major European industrial facilities has a global interest for Europe, its citizens and economy. A potential major disaster at an industrial site could affect several countries, probably far beyond the country where it is located. However, the seismic design and safety assessment of these facilities is practically based on national, often outdated seismic hazard assessment studies, due to many reasons, including the absence of a reliable, commonly developed seismic hazard model for whole Europe. This important gap is no more existing, as the 2020 European Seismic Hazard Model ESHM20 was released in December 2021. In this paper we investigate the expected impact of the adoption of ESHM20 on the seismic demand for industrial facilities, through the comparison of the ESHM20 probabilistic hazard at the sites where industrial facilities are located with the respective national and European regulations. The goal of this preliminary work in the framework of Working Group 13 of the European Association for Earthquake Engineering (EAEE), is to identify potential inadequacies in the design and safety control of existing industrial facilities and to highlight the expected impact of the adoption of the new European Seismic Hazard Model on the design of new industrial facilities and the safety assessment of existing ones.
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.
Hydrogen is playing an increasingly important role in research and politics as an energy carrier of the future. Since hydrogen has commonly been produced from methane by steam reforming, the need for climate-friendly, alternative production routes is emerging. In addition to electrolysis, fermentative routes for the production of so-called biohydrogen are "green" alternatives. The application of microorganisms offers the advantage of sustainable production from renewable resources using easily manageable technologies. In this project, the hyperthermophilic, anaerobic microorganism Thermotoga neapolitana is used for the productio nof biohydrogen from renewable resources. The enzymatically hydrolyzed resources were used in fermentation leading to yield coefficients of 1.8 mole H₂ per mole glucose when using hydrolyzed straw and ryegrass supplemented with medium, respectively. These results are similar to the hydrogen yields when using Thermotoga basal medium with glucose (TBGY) as control group. In order to minimize the supplementation of the hydrolysate and thus increase the economic efficiency of the process, the essential media components were identified. The experiments revealed NaCl, KCl, and glucose as essential components for cell growth as well as biohydrogen production. When excluding NaCl, a decrease of 96% in hydrogen production occured.
REM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
The European Union's aim to become climate neutral by 2050 necessitates ambitious efforts to reduce carbon emissions. Large reductions can be attained particularly in energy intensive sectors like iron and steel. In order to prevent the relocation of such industries outside the EU in the course of tightening environmental regulations, the establishment of a climate club jointly with other large emitters and alternatively the unilateral implementation of an international cross-border carbon tax mechanism are proposed. This article focuses on the latter option choosing the steel sector as an example. In particular, we investigate the financial conditions under which a European cross border mechanism is capable to protect hydrogen-based steel production routes employed in Europe against more polluting competition from abroad. By using a floor price model, we assess the competitiveness of different steel production routes in selected countries. We evaluate the climate friendliness of steel production on the basis of specific GHG emissions. In addition, we utilize an input-output price model. It enables us to assess impacts of rising cost of steel production on commodities using steel as intermediates. Our results raise concerns that a cross-border tax mechanism will not suffice to bring about competitiveness of hydrogen-based steel production in Europe because the cost tends to remain higher than the cost of steel production in e.g. China. Steel is a classic example for a good used mainly as intermediate for other products. Therefore, a cross-border tax mechanism for steel will increase the price of products produced in the EU that require steel as an input. This can in turn adversely affect competitiveness of these sectors. Hence, the effects of higher steel costs on European exports should be borne in mind and could require the cross-border adjustment mechanism to also subsidize exports.
This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut Jülich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 % based on the tested days. The result fulfils SIJ’s aim to achieve a reliability of around 70 %, but SIJ aims to still improve the DNI forecast quality.
In this work, three patent pending calibration methods for heliostat fields of central receiver systems (CRS) developed by the Solar-Institut Jülich (SIJ) of the FH Aachen University of Applied Sciences are presented. The calibration methods can either operate in a combined mode or in stand-alone mode. The first calibration method, method A, foresees that a camera matrix is placed into the receiver plane where it is subjected to concentrated solar irradiance during a measurement process. The second calibration method, method B, uses an unmanned aerial vehicle (UAV) such as a quadrocopter to automatically fly into the reflected solar irradiance cross-section of one or more heliostats (two variants of method B were tested). The third calibration method, method C, foresees a stereo central camera or multiple stereo cameras installed e.g. on the solar tower whereby the orientations of the heliostats are calculated from the location detection of spherical red markers attached to the heliostats. The most accurate method is method A which has a mean accuracy of 0.17 mrad. The mean accuracy of method B variant 1 is 1.36 mrad and of variant 2 is 1.73 mrad. Method C has a mean accuracy of 15.07 mrad. For method B there is great potential regarding improving the measurement accuracy. For method C the collected data was not sufficient for determining whether or not there is potential for improving the accuracy.
Quantitative evaluation of health management designs for fuel cell systems in transport vehicles
(2022)
Focusing on transport vehicles, mainly with regard to aviation applications, this paper presents compilation and subsequent quantitative evaluation of methods aimed at building an optimum integrated health management solution for fuel cell systems. The methods are divided into two different main types and compiled in a related scheme. Furthermore, different methods are analysed and evaluated based on parameters specific to the aviation context of this study. Finally, the most suitable method for use in fuel cell health management systems is identified and its performance and suitability is quantified.
Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed
A promising approach to reduce the system costs of molten salt solar receivers is to enable the irradiation of the absorber tubes on both sides. The star design is an innovative receiver design, pursuing this approach. The unconventional design leads to new challenges in controlling the system. This paper presents a control concept for a molten salt receiver system in star design. The control parameters are optimized in a defined test cycle by minimizing a cost function. The control concept is tested in realistic cloud passage scenarios based on real weather data. During these tests, the control system showed no sign of unstable behavior, but to perform sufficiently in every scenario further research and development like integrating Model Predictive Controls (MPCs) need to be done. The presented concept is a starting point to do so.
Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments
(2022)
Abstract
In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.
Concerning current efforts to improve operational efficiency and to lower overall costs of concentrating solar power (CSP) plants with prediction-based algorithms, this study investigates the quality and uncertainty of nowcasting data regarding the implications for process predictions. DNI (direct normal irradiation) maps from an all-sky imager-based nowcasting system are applied to a dynamic prediction model coupled with ray tracing. The results underline the need for high-resolution DNI maps in order to predict net yield and receiver outlet temperature realistically. Furthermore, based on a statistical uncertainty analysis, a correlation is developed, which allows for predicting the uncertainty of the net power prediction based on the corresponding DNI forecast uncertainty. However, the study reveals significant prediction errors and the demand for further improvement in the accuracy at which local shadings are forecasted.
In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.
We study the possibility to fabricate an arbitrary phase mask in a one-step laser-writing process inside the volume of an optical glass substrate. We derive the phase mask from a Gerchberg–Saxton-type algorithm as an array and create each individual phase shift using a refractive index modification of variable axial length. We realize the variable axial length by superimposing refractive index modifications induced by an ultra-short pulsed laser at different focusing depth. Each single modification is created by applying 1000 pulses with 15 μJ pulse energy at 100 kHz to a fixed spot of 25 μm diameter and the focus is then shifted axially in steps of 10 μm. With several proof-of-principle examples, we show the feasibility of our method. In particular, we identify the induced refractive index change to about a value of Δn=1.5⋅10−3. We also determine our current limitations by calculating the overlap in the form of a scalar product and we discuss possible future improvements.
When confining pressure is low or absent, extensional fractures are typical, with fractures occurring on unloaded planes in rock. These “paradox” fractures can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. But this criterion makes unrealistic strength predictions in biaxial compression and tension. A new extension strain criterion overcomes this limitation by adding a weighted principal shear component. The weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr–Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting failure modes, which are unexpected in the understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak P. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.
Diversity management is seen as a decisive factor for ensuring the development of socially responsible innovations (Beacham and Shambaugh, 2011; Sonntag, 2014; López, 2015; Uebernickel et al., 2015). However, many diversity management approaches fail due to a one-sided consideration of diversity (Thomas and Ely, 2019) and a lacking linkage between the prevailing organizational culture and the perception of diversity in the respective organization. Reflecting the importance of diverse perspectives, research institutions have a special responsibility to actively deal with diversity, as they are publicly funded institutions that drive socially relevant development and educate future generations of developers, leaders and decision-makers. Nevertheless, only a few studies have so far dealt with the influence of the special framework conditions of the science system on diversity management. Focusing on the interdependency of the organizational culture and diversity management especially in a university research environment, this chapter aims in a first step to provide a theoretical perspective on the framework conditions of a complex research organization in Germany in order to understand the system-specific factors influencing diversity management. In a second step, an exploratory cluster analysis is presented, investigating the perception of diversity and possible influencing factors moderating this perception in a scientific organization. Combining both steps, the results show specific mechanisms and structures of the university research environment that have an impact on diversity management and rigidify structural barriers preventing an increase of diversity. The quantitative study also points out that the management level takes on a special role model function in the scientific system and thus has an influence on the perception of diversity. Consequently, when developing diversity management approaches in research organizations, it is necessary to consider the top-down direction of action, the special nature of organizational structures in the university research environment as well as the special role of the professorial level as role model for the scientific staff.
Promoting diversity and combatting discrimination in research organizations: a practitioner’s guide
(2022)
The essay is addressed to practitioners in research management and from
academic leadership. It describes which measures can contribute to creating an inclusive climate for research teams and preventing and effectively dealing with discrimination. The practical recommendations consider the policy and organizational levels, as well as the individual perspective of research managers. Following a series of basic recommendations, six lessons learned are formulated, derived from the contributions to the edited collection on “Diversity and Discrimination in Research Organizations.”