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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
Utilizing an appropriate enzyme immobilization strategy is crucial for designing enzyme-based biosensors. Plant virus-like particles represent ideal nanoscaffolds for an extremely dense and precise immobilization of enzymes, due to their regular shape, high surface-to-volume ratio and high density of surface binding sites. In the present work, tobacco mosaic virus (TMV) particles were applied for the co-immobilization of penicillinase and urease onto the gate surface of a field-effect electrolyte-insulator-semiconductor capacitor (EISCAP) with a p-Si-SiO₂-Ta₂O₅ layer structure for the sequential detection of penicillin and urea. The TMV-assisted bi-enzyme EISCAP biosensor exhibited a high urea and penicillin sensitivity of 54 and 85 mV/dec, respectively, in the concentration range of 0.1–3 mM. For comparison, the characteristics of single-enzyme EISCAP biosensors modified with TMV particles immobilized with either penicillinase or urease were also investigated. The surface morphology of the TMV-modified Ta₂O₅-gate was analyzed by scanning electron microscopy. Additionally, the bi-enzyme EISCAP was applied to mimic an XOR (Exclusive OR) enzyme logic gate.
Bacterial cellulose (BC) is a biopolymer produced by different microorganisms, but in biotechnological practice, Komagataeibacter xylinus is used. The micro- and nanofibrillar structure of BC, which forms many different-sized pores, creates prerequisites for the introduction of other polymers into it, including those synthesized by other microorganisms. The study aims to develop a cocultivation system of BC and prebiotic producers to obtain BC-based composite material with prebiotic activity. In this study, pullulan (PUL) was found to stimulate the growth of the probiotic strain Lactobacillus rhamnosus GG better than the other microbial polysaccharides gellan and xanthan. BC/PUL biocomposite with prebiotic properties was obtained by cocultivation of Komagataeibacter xylinus and Aureobasidium pullulans, BC and PUL producers respectively, on molasses medium. The inclusion of PUL in BC is proved gravimetrically by scanning electron microscopy and by Fourier transformed infrared spectroscopy. Cocultivation demonstrated a composite effect on the aggregation and binding of BC fibers, which led to a significant improvement in mechanical properties. The developed approach for “grafting” of prebiotic activity on BC allows preparation of environmentally friendly composites of better quality.
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.
A capacitive electrolyte-insulator-semiconductor (EISCAP) biosensor modified with Tobacco mosaic virus (TMV) particles for the detection of acetoin is presented. The enzyme acetoin reductase (AR) was immobilized on the surface of the EISCAP using TMV particles as nanoscaffolds. The study focused on the optimization of the TMV-assisted AR immobilization on the Ta 2 O 5 -gate EISCAP surface. The TMV-assisted acetoin EISCAPs were electrochemically characterized by means of leakage-current, capacitance-voltage, and constant-capacitance measurements. The TMV-modified transducer surface was studied via scanning electron microscopy.
Acetoin and diacetyl have a major impact on the flavor of alcoholic beverages such as wine or beer. Therefore, their measurement is important during the fermentation process. Until now, gas chromatographic techniques have typically been applied; however, these require expensive laboratory equipment and trained staff, and do not allow for online monitoring. In this work, a capacitive electrolyte–insulator–semiconductor sensor modified with tobacco mosaic virus (TMV) particles as enzyme nanocarriers for the detection of acetoin and diacetyl is presented. The enzyme acetoin reductase from Alkalihalobacillus clausii DSM 8716ᵀ is immobilized via biotin–streptavidin affinity, binding to the surface of the TMV particles. The TMV-assisted biosensor is electrochemically characterized by means of leakage–current, capacitance–voltage, and constant capacitance measurements. In this paper, the novel biosensor is studied regarding its sensitivity and long-term stability in buffer solution. Moreover, the TMV-assisted capacitive field-effect sensor is applied for the detection of diacetyl for the first time. The measurement of acetoin and diacetyl with the same sensor setup is demonstrated. Finally, the successive detection of acetoin and diacetyl in buffer and in diluted beer is studied by tuning the sensitivity of the biosensor using the pH value of the measurement solution.
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.
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.
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.
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.
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.
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.
In this study, an online multi-sensing platform was engineered to simultaneously evaluate various process parameters of food package sterilization using gaseous hydrogen peroxide (H₂O₂). The platform enabled the validation of critical aseptic parameters. In parallel, one series of microbiological count reduction tests was performed using highly resistant spores of B. atrophaeus DSM 675 to act as the reference method for sterility validation. By means of the multi-sensing platform together with microbiological tests, we examined sterilization process parameters to define the most effective conditions with regards to the highest spore kill rate necessary for aseptic packaging. As these parameters are mutually associated, a correlation between different factors was elaborated. The resulting correlation indicated the need for specific conditions regarding the applied H₂O₂ gas temperature, the gas flow and concentration, the relative humidity and the exposure time. Finally, the novel multi-sensing platform together with the mobile electronic readout setup allowed for the online and on-site monitoring of the sterilization process, selecting the best conditions for sterility and, at the same time, reducing the use of the time-consuming and costly microbiological tests that are currently used in the food package industry.
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.
Objective
Hemodialysis patients show an approximately threefold higher prevalence of cognitive impairment compared to the age-matched general population. Impaired microcirculatory function is one of the assumed causes. Dynamic retinal vessel analysis is a quantitative method for measuring neurovascular coupling and microvascular endothelial function. We hypothesize that cognitive impairment is associated with altered microcirculation of retinal vessels.
Methods
152 chronic hemodialysis patients underwent cognitive testing using the Montreal Cognitive Assessment. Retinal microcirculation was assessed by Dynamic Retinal Vessel Analysis, which carries out an examination recording retinal vessels' reaction to a flicker light stimulus under standardized conditions.
Results
In unadjusted as well as in adjusted linear regression analyses a significant association between the visuospatial executive function domain score of the Montreal Cognitive Assessment and the maximum arteriolar dilation as response of retinal arterioles to the flicker light stimulation was obtained.
Conclusion
This is the first study determining retinal microvascular function as surrogate for cerebral microvascular function and cognition in hemodialysis patients. The relationship between impairment in executive function and reduced arteriolar reaction to flicker light stimulation supports the involvement of cerebral small vessel disease as contributing factor for the development of cognitive impairment in this patient population and might be a target for noninvasive disease monitoring and therapeutic intervention.
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.
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.
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.
This work introduces a novel method for the detection of H₂O₂ vapor/aerosol of low concentrations, which is mainly applied in the sterilization of equipment in medical industry. Interdigitated electrode (IDE) structures have been fabricated by means of microfabrication techniques. A differential setup of IDEs was prepared, containing an active sensor element (active IDE) and a passive sensor element (passive IDE), where the former was immobilized with an enzymatic membrane of horseradish peroxidase that is selective towards H₂O₂. Changes in the IDEs’ capacitance values (active sensor element versus passive sensor element) under H₂O₂ vapor/aerosol atmosphere proved the detection in the concentration range up to 630 ppm with a fast response time (<60 s). The influence of relative humidity was also tested with regard to the sensor signal, showing no cross-sensitivity. The repeatability assessment of the IDE biosensors confirmed their stable capacitive signal in eight subsequent cycles of exposure to H₂O₂ vapor/aerosol. Room-temperature detection of H₂O₂ vapor/aerosol with such miniaturized biosensors will allow a future three-dimensional, flexible mapping of aseptic chambers and help to evaluate sterilization assurance in medical industry.
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.
It was generally believed that coal sources are not favorable as live-in habitats for microorganisms due to their recalcitrant chemical nature and negligible decomposition. However, accumulating evidence has revealed the presence of diverse microbial groups in coal environments and their significant metabolic role in coal biogeochemical dynamics and ecosystem functioning. The high oxygen content, organic fractions, and lignin-like structures of lower-rank coals may provide effective means for microbial attack, still representing a greatly unexplored frontier in microbiology. Coal degradation/conversion technology by native bacterial and fungal species has great potential in agricultural development, chemical industry production, and environmental rehabilitation. Furthermore, native microalgal species can offer a sustainable energy source and an excellent bioremediation strategy applicable to coal spill/seam waters. Additionally, the measures of the fate of the microbial community would serve as an indicator of restoration progress on post-coal-mining sites. This review puts forward a comprehensive vision of coal biodegradation and bioprocessing by microorganisms native to coal environments for determining their biotechnological potential and possible applications.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed.
FEM shakedown analysis of structures under random strength with chance constrained programming
(2022)
Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable.
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.
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.
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.
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.
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.
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.
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.
Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better
address changes in their environment and differentiate their products andservices.
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.
Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435.
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.