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Proton Exchange Membrane Fuel Cells (PEMFC) are energy efficient and environmentally friendly alternatives to conventional energy conversion systems in many yet emerging applications. In order to enable prediction of their performance and durability, it is crucial to gain a deeper understanding of the relevant operation phenomena, e.g., electrochemistry, transport phenomena, thermodynamics as well as the mechanisms leading to the degradation of cell components. Achieving the goal of providing predictive tools to model PEMFC performance, durability and degradation is a challenging task requiring the development of detailed and realistic models reaching from the atomic/molecular scale over the meso scale of structures and materials up to components, stack and system level. In addition an appropriate way of coupling the different scales is required.
This review provides a comprehensive overview of the state of the art in modeling of PEMFC, covering all relevant scales from atomistic up to system level as well as the coupling between these scales. Furthermore, it focuses on the modeling of PEMFC degradation mechanisms and on the coupling between performance and degradation models.
Virtual-Reality-Anwendungen ermöglichen es Anbietern von Erfahrungsgütern durch innovative Produktpräsentationen die inhärenten Informationsasymmetrien zu reduzieren. Dadurch kann den potenziellen Kunden eine effiziente Leistungsbeurteilung ermöglicht und das Risiko einer informationsbedingten Fehlentscheidung minimiert werden. Die vorliegende Studie fokussiert sich auf die Identifikation wichtiger Determinanten, die die Nutzungsintention von Virtual-Reality-Anwendungen zur Leistungsbeurteilung von Erfahrungsgütern beeinflussen. Um das Akzeptanzverhalten von Nutzern gegenüber dieser neuartigen Technologie zu erforschen, wurde ein erweitertes Technologieakzeptanzmodell eingesetzt. Als Untersuchungsobjekt wurde eigens für die Studie eine Virtual-Reality-Anwendung entwickelt, die es den Nutzern ermöglichte, eigenständig ein virtuelles Erfahrungsgut zu erkunden. Insgesamt nahmen 569 Probanden an der Datenerhebung teil. Für die Berechnung des Strukturgleichungsmodells und die Hypothesenüberprüfung wurde eine Partial-Least-Squares-Analyse eingesetzt. Wie die Studienergebnisse verdeutlichen, führt das immersive Produkterlebnis zu einer effizienteren Informationsbeschaffung. Speziell der wahrgenommene Nutzen einer Virtual-Reality-Anwendung ist ein zentraler Prädiktor, der sowohl auf die Nutzungseinstellung als auch auf die Nutzungsintention einen starken positiven Einfluss ausübt.
Virtual reality (VR) offers the opportunity to create virtual worlds that could replace real experiences. This research investigates the influence of user motivation, temporal distance and experience type on the satisfaction with the VR experience, and the degree of acceptance of a VR experience as a substitute for a real experience. The results suggest that the degree of acceptance of a VR experience as a substitute for a real experience is higher for passive VR experiences compared to active VR experiences. Furthermore, the results support the assumption that users are more satisfied with passive VR experiences.
Purpose
The purpose of this study is to investigate the effects of telepresence while using a smartphone-based virtual reality system (SBVR) to explore a hotel virtually and to determine the influence of this immersive experience on the booking intention of the potential customer.
Design/methodology/approach
Within the scope of this study, a conceptual research model was developed which covered utilitarian and hedonic aspects of the user experience of SBVRs and showed their relevance for the booking intention. A virtual reality application was programmed especially for the study, in which the test persons were able to virtually explore a hotel complex. A total of 569 people participated in the study. A questionnaire was used for the data collection. The structural equation modelling and hypothesis verification were carried out using the partial least squares method.
Findings
The immersive feeling of telepresence increases the perceived enjoyment and usefulness of the potential customer. In addition, the user's curiosity is aroused by the telepresence, which also significantly increases the perceived enjoyment as well as the perceived usefulness. The hedonic and utilitarian value of the virtual hotel experience increases the probability that the customer will book the travel accommodation.
Research limitations/implications
The virtual reality application developed for the study is based on static panoramic images and does not contain audio-visual elements (e.g. sound, video, animation). Audio-visual elements might increase the degree of immersion and could therefore be investigated in future research.
Practical implications
The results of the study show that the SBVR is a suitable marketing tool to present hotels in an informative and entertaining way, and can thereby increase sales and profits.
Originality/value
For the first time, this study investigates the potential of SBVRs for the virtual product presentation of hotels and provides empirical evidence that the availability of this innovative form of presentation leads to a higher booking intention.
Virtual reality in the hotel industry: assessing the acceptance of immersive hotel presentation
(2019)
In the hotel industry, it is crucial to reduce the inherent information asymmetry with regard to the goods offered. This asymmetry can be minimised through the use of smartphone-based virtual reality applications (SBVRs), which allow virtual simulation of real experiences and thus enable more efficient information retrieval. The aim of the study is to determine for the first time the user acceptance of these immersive hotel presentations for assessing the performance of a travel accommodation. For this purpose, the Technology Acceptance Model (TAM) was used to explain the acceptance behaviour for this new technology. A virtual reality application was specially developed, in which the participants could explore a hotel virtually. A total of 569 participants took part in the study. The structural equation model and the hypotheses were tested using a Partial Least Squares (PLS) analysis. The results illustrate that the immersive product experience leads to more efficient information gathering. The perceived usefulness significantly affects the attitude towards using the technology as well as the intention to use it. In contrast to the traditional TAM, the perceived ease of use of SBVRs has no effect on the perceived usefulness or attitude towards using the technology.
Given the looming threats of climate change and the rapid worldwide urbanization, it is a necessity to prioritize the transition towards a carbon-free built environment. This research study provides a holistic digital methodology for parametric design of urban residential buildings with regard to the Mediterranean semi-arid climate zone of Morocco in the early design phase. The morphological parameters of the urban residential buildings, namely the buildings’ typology, the distance between buildings, the urban grid’s orientation, and the window-towall ratio, are evaluated in order to identify the key combinations of passive and active solar design strategies that determine the high energy performing configurations, based on the introduced Energy Performance Index (EPI), which is the ratio between solar BIPV production to maximum available installed BIPV capacity and the normalized thermal energy needs. Through an automated processing of 2187 iterations via Grasshopper, we simulate daylight autonomy, indoor thermal comfort and solar rooftop photovoltaic and building integrated photovoltaic (BIPV) energy potential. Then, we analyze the conflicting objectives of energy efficiency measures, active solar design strategies, and indoor visual comfort in the decision-making process that supports our goal of getting closer to net zero urban residential buildings. The digital workflow showed interesting trends in reaching a balanced equilibrium between performance metrics influenced by the contrasting impact of solar exposure on indoor daylight autonomy and thermal energy demand. Furthermore, the study’s findings indicate that it is possible to achieve an annual load match exceeding 66,56 % while simultaneously ensuring an acceptable visual indoor comfort (sDA higher than 0.4). The findings also highlight the important role of the BIPV system in shifting towards the net zero energy goal, by contributing up to 30 % of the overall solar energy output and covering up to 20 % of the yearly self-consumption. Moreover, the energy balance evaluation on an hourly basis indicates that BIPV system notably enhances the daily load cover factor by up to 5.5 %, particularly in the case of slab SN typology, throughout the different seasons. Graphical representations of the yearly, monthly and hourly load matches and the hourly energy balance of the best performing configurations provide a thorough understanding of the potential evolution of the urban energy system over time as a result of the gradual integration of active solar electricity production.
A versatile liquid metal (LM) printing process enabling the fabrication of various fully printed devices such as intra- and interconnect wires, resistors, diodes, transistors, and basic circuit elements such as inverters which are process compatible with other digital printing and thin film structuring methods for integration is presented. For this, a glass capillary-based direct-write method for printing LMs such as eutectic gallium alloys, exploring the potential for fully printed LM-enabled devices is demonstrated. Examples for successful device fabrication include resistors, p–n diodes, and field effect transistors. The device functionality and easiness of one integrated fabrication flow shows that the potential of LM printing is far exceeding the use of interconnecting conventional electronic devices in printed electronics.
Introduction The use of scaffolds in tissue engineering is becoming increasingly important as solutions need to be found for the problem of preserving human tissue, such as bone or cartilage. In this work, scaffolds were printed from the biomaterial known as polycaprolactone (PCL) on a 3D Bioplotter. Both the external and internal geometry were varied to investigate their influence on mechanical stability and biocompatibility. Materials and Methods: An Envisiontec 3D Bioplotter was used to fabricate the scaffolds. First, square scaffolds were printed with variations in the strand width and strand spacing. Then, the filling structure was varied: either lines, waves, and honeycombs were used. This was followed by variation in the outer shape, produced as either a square, hexagon, octagon, or circle. Finally, the internal and external geometry was varied. To improve interaction with the cells, the printed PCL scaffolds were coated with type-I collagen. MG-63 cells were then cultured on the scaffolds and various tests were performed to investigate the biocompatibility of the scaffolds. Results: With increasing strand thickness and strand spacing, the compressive strengths decreased from 86.18 + 2.34 MPa (200 µm) to 46.38 + 0.52 MPa (600 µm). The circle was the outer shape with the highest compressive strength of 76.07 + 1.49 MPa, compared to the octagon, which had the lowest value of 52.96 ± 0.98 MPa. Varying the external shape (toward roundness) geometry, as well as the filling configuration, resulted in the highest values of compressive strength for the round specimens with honeycomb filling, which had a value of 91.4 + 1.4 MPa. In the biocompatibility tests, the round specimens with honeycomb filling also showed the highest cell count per mm2, with 1591 ± 239 live cells/mm2 after 10 days and the highest value in cell proliferation, but with minimal cytotoxic effects (9.19 ± 2.47% after 3 days).
Compact solid discharge products enable energy storage devices with high gravimetric and volumetric energy densities, but solid deposits on active surfaces can disturb charge transport and induce mechanical stress. In this Letter, we develop a nanoscale continuum model for the growth of Li2O2 crystals in lithium–oxygen batteries with organic electrolytes, based on a theory of electrochemical nonequilibrium thermodynamics originally applied to Li-ion batteries. As in the case of lithium insertion in phase-separating LiFePO4 nanoparticles, the theory predicts a transition from complex to uniform morphologies of Li2O2 with increasing current. Discrete particle growth at low discharge rates becomes suppressed at high rates, resulting in a film of electronically insulating Li2O2 that limits cell performance. We predict that the transition between these surface growth modes occurs at current densities close to the exchange current density of the cathode reaction, consistent with experimental observations.
In this paper we present a model of the discharge of a lithium–oxygen battery with aqueous electrolyte. Lithium–oxygen batteries (Li–O2) have recently received great attention due to their large theoretical specific energy. Advantages of the aqueous design include the stability of the electrolyte, the long experience with gas diffusion electrodes (GDEs), and the solubility of the reaction product lithium hydroxide. However, competitive specific energies can only be obtained if the product is allowed to precipitate. Here we present a dynamic one-dimensional model of a Li–O2 battery including a GDE and precipitation of lithium hydroxide. The model is parameterized using experimental data from the literature. We demonstrate that GDEs remove power limitations due to slow oxygen transport in solutions and that lithium hydroxide tends to precipitate on the anode side. We discuss the system architecture to engineer where nucleation and growth predominantly occurs and to optimize for discharge capacity.
Lithium–sulfur (Li/S) cells are promising candidates for a next generation of safe and cost-effective high energy density batteries for mobile and stationary applications. At present, most Li/S cells still suffer from relatively poor cyclability, capacity loss under moderate current densities and self-discharge. Furthermore, the underlying chemical mechanisms of the general discharge/charge behavior as well as Li/S-specific phenomena like the polysulfide shuttle are not yet fully understood. Here we present a thermodynamically consistent, fully reversible continuum model of a Li/S cell with simplified four-step electrochemistry, including a simple description of the polysulfide shuttle effect. The model is parameterized using experimental discharge curves obtained from literature and reproduces behavior at various current densities with fairly high accuracy. While being instructively simple, the presented model can still reproduce distinct macroscopic Li/S-cell features caused by the shuttle effect, e.g., seemingly infinite charging at low charge current densities, and suboptimal coulombic efficiency. The irreversible transport of active material from the cathode to the anode results in a voltage drop and capacity loss during cycling, which can also be observed experimentally.
Appraising the Methodological Quality of Sports Injury Video Analysis Studies: The QA-SIVAS Scale
(2023)
Background
Video analysis (VA) is commonly used in the assessment of sports injuries and has received considerable research interest. Until now, no tool has been available for the assessment of study quality. Therefore, the objective of this study was to develop and evaluate a valid instrument that reliably assesses the methodological quality of VA studies.
Methods
The Quality Appraisal for Sports Injury Video Analysis Studies (QA-SIVAS) scale was developed using a modified Delphi approach including expert consensus and pilot testing. Reliability was examined through intraclass correlation coefficient (ICC3,1) and free-marginal kappa statistics by three independent raters. Construct validity was investigated by comparing QA-SIVAS with expert ratings by using Kendall’s tau analysis. Rating time was studied by applying the scale to 21 studies and computing the mean time for rating per study article.
Results
The QA-SIVAS scale consists of an 18-item checklist addressing the study design, data source, conduct, report, and discussion of VA studies in sports injury research. Inter- and intra-rater reliability were excellent with ICCs > 0.97. Expert ratings revealed a high construct validity (0.71; p < 0.001). Mean rating time was 10 ± 2 min per article.
Conclusion
QA-SIVAS is a reliable and valid instrument that can be easily applied to sports injury research. Future studies in the field of VA should adhere to standardized methodological criteria and strict quality guidelines.
Human–robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human–machine differentiation to the speed and separation monitoring in human–robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.
A diode array HPTLC method for dequalinium chloride in pharmaceutical preparations is presented. For separation a Nano TLC silica gel plate (Merck) is used with the mobile phase methanol-7.8% aqueous NH(4)(+)CH(3)COO(-) (17:3, v/v) over a distance of 6 cm. Dequalinium chloride shows an R(F) value of 0.58. Pure dequalinium chloride is measured in the wavelength range from 200 to 500 nm and shows several by-products, contour plot visualized in absorption, fluorescence and using the Kubelka-Munk transformation. Scanning of a single track in absorption and fluorescence measuring 600 spectra in the range from 200 to 1100 nm takes 30s. As a sample pre-treatment of an ointment it is simply dissolved in methanol and can be quantified in absorption from 315 to 340 nm. The same separation can also be quantified using fluorescence spectrometry in the range from 355 to 370 nm. A new staining method for dequalinium chloride, using sodium tetraphenyl borate/HCl in water allows a fluorescence quantification in the range from 445 to 485 nm. The linearity range of absorption and fluorescence measurements is from 10 to 2000 ng. Sugar-containing preparations like liquids or lozenges with a reduced sample pre-treatment can be reliably quantified only in fluorescence. The total for the quantification of an ointment sample (measuring four standards and five samples), including all sample pre-treatment steps takes less than 45 min!
The characteristic features and applications of linear and nonlinear guided elastic waves propagating along surfaces (2D) and wedges (1D) are discussed. Laser-based excitation, detection, or contact-free analysis of these guided waves with pump–probe methods are reviewed. Determination of material parameters by broadband surface acoustic waves (SAWs) and other applications in nondestructive evaluation (NDE) are considered. The realization of nonlinear SAWs in the form of solitary waves and as shock waves, used for the determination of the fracture strength, is described. The unique properties of dispersion-free wedge waves (WWs) propagating along homogeneous wedges and of dispersive wedge waves observed in the presence of wedge modifications such as tip truncation or coatings are outlined. Theoretical and experimental results on nonlinear wedge waves in isotropic and anisotropic solids are presented.
Die Zuverlässigkeit und Betriebssicherheit von Feldgeräten ist für den sicheren und wirtschaftlichen Betrieb prozesstechnischer Anlagen unerlässlich. Ein entscheidender Faktor ist die Widerstandskraft der Geräte gegen die herrschenden Umgebungsbedingungen. Durch Korrosionsschäden hervorgerufene Anlagenstillstände zeigen, dass diesem Thema nicht immer die notwendige Aufmerksamkeit gewidmet wird, obwohl die korrosionsbedingten wirtschaftlichen Schäden immens sind. Wie man mit dem Thema Korrosionsschutz ernsthaft umgehen kann, zeigt dieser Beitrag am Beispiel elektrischer Stellantriebe.
Design and Implementation of a Camera-Based Tracking System for MAV Using Deep Learning Algorithms
(2023)
In recent years, the advancement of micro-aerial vehicles has been rapid, leading to their widespread utilization across various domains due to their adaptability and efficiency. This research paper focuses on the development of a camera-based tracking system specifically designed for low-cost drones. The primary objective of this study is to build up a system capable of detecting objects and locating them on a map in real time. Detection and positioning are achieved solely through the utilization of the drone’s camera and sensors. To accomplish this goal, several deep learning algorithms are assessed and adopted because of their suitability with the system. Object detection is based upon a single-shot detector architecture chosen for maximum computation speed, and the tracking is based upon the combination of deep neural-network-based features combined with an efficient sorting strategy. Subsequently, the developed system is evaluated using diverse metrics to determine its performance for detection and tracking. To further validate the approach, the system is employed in the real world to show its possible deployment. For this, two distinct scenarios were chosen to adjust the algorithms and system setup: a search and rescue scenario with user interaction and precise geolocalization of missing objects, and a livestock control scenario, showing the capability of surveying individual members and keeping track of number and area. The results demonstrate that the system is capable of operating in real time, and the evaluation verifies that the implemented system enables precise and reliable determination of detected object positions. The ablation studies prove that object identification through small variations in phenotypes is feasible with our approach.
Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. A configuration using a mobile robot Husky A200, and a LiDAR (light detection and ranging) sensor was used to implement the setup. For verification of the proposed setup, different scan matching methods for odometry determination in indoor and outdoor environments are tested. An assessment of the accuracy of the baseline 3D-SLAM system and the selected evaluation system is presented by comparing different scenarios and test situations. It was shown that the hdl_graph_slam in combination with the LiDAR OS1 and the scan matching algorithms FAST_GICP and FAST_VGICP achieves good mapping results with accuracies up to 2 cm.
Evaluation of Deep Learning-Based Neural Network Methods for Cloud Detection and Segmentation
(2021)
This paper presents a systematic approach for accurate short-time cloud coverage prediction based on a machine learning (ML) approach. Based on a newly built omnidirectional ground-based sky camera system, local training and evaluation data sets were created. These were used to train several state-of-the-art deep neural networks for object detection and segmentation. For this purpose, the camera-generated a full hemispherical image every 30 min over two months in daylight conditions with a fish-eye lens. From this data set, a subset of images was selected for training and evaluation according to various criteria. Deep neural networks, based on the two-stage R-CNN architecture, were trained and compared with a U-net segmentation approach implemented by CloudSegNet. All chosen deep networks were then evaluated and compared according to the local situation.