The future of power systems belongs to renewables. And to integrate them, the expansion of the electricity grids is undoubtedly necessary. Furthermore, power systems cannot operate without reserves and flexibilities. ...
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In this paper, we present a method for the automated determination of aerosol jet parameters for the Aerosol-on-Demand (AoD) jet-printhead. A critical aspect in the simulation of our computational fluid dynamics (CFD)...
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Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron *** study the powder samples that are widely used in materials development,scanning electron micro...
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Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron *** study the powder samples that are widely used in materials development,scanning electron microscopes(SEMs)are increasingly used at the laboratory scale to generate large datasets with hundreds of *** these images to identify distinct particles and determine their morphology requires careful analysis,and automating this process remains *** this work,we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM *** address several challenges inherent to measurements,such as image blur and particle ***,our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a *** that disparate length scales are often present in large datasets,we use this framework to create two models that are separately trained to handle images obtained at low or high *** testing these models on a variety of inorganic samples,our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts,revealing comparable accuracy while requiring a fraction of the *** findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.
This paper introduces a multiobjective optimization strategy for minimizing both energy pulsation and power dissipation in modular multilevel converters (MMCs). The occurrence of energy pulsation and power dissipation...
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Laser-scanning confocal microscopy of the human cornea acquires in vivo images of corneal tissues with cellular resolution, which offers diagnostic potential for a variety of diseases. However, involuntary fixational ...
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One new robust variant of the formulation of the problem of searching for the principal components are considered. It’s based on the application of differentiable estimates of the average value, insensitive to outlie...
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We introduce a lightweight framework for semantic segmentation that utilizes structured classifiers as an alternative to deep learning methods. Biomedical data is known for being scarce and difficult to label. However...
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The increasing use of information and communication technologies has led to increasing threats on critical infrastructure like smart grids. Owing to confidentiality issues and difficulties in experimenting cyberattack...
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Due to the energy transition, which involves phasing out base load power plants such as coal, there is a need to establish storage systems within the energy system to compensate for fluctuations of renewable energies....
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Due to the energy transition, which involves phasing out base load power plants such as coal, there is a need to establish storage systems within the energy system to compensate for fluctuations of renewable energies. Batteries are suitable for day-night cycles and particularly for short-cycle applications. To address the problem of dark-doldrums, when neither wind nor solar energy is available, gas and, in the more distant future, hydrogen power plants are to be used. By combining batteries and hydrogen power plants in a hybrid energy storage system, further advantages and application possibilities arise regarding grid stability and system design. This work illustrates interrelationships between the subsystems, optimizes proportions, and demonstrates logical system sizes, technologies, and their costs. A central part of the work are the self-derived methods for system design and the justification of these. Storage pressure, running times, availability time, annual cycles and design of the subsystems are described. Systems of this scale are difficult to imagine. A program developed as part of this work to implement the methods, visualizes the system, displays the system parameters, and shows the best-case and worst-case capital expenditures. An optimized system design is presented. Different combinations in the system design show the effects on capital expenditures. Starting from 2 to 4 hours of availability time, the hybrid system becomes cheaper than a pure battery system in terms of capital expenditures.
Industry 4.0-compliant digitalization is intensively penetrating the industrial Eco-system, bringing its benefits by generating or improving new complementary functionalities and associated business, providing a feasi...
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Industry 4.0-compliant digitalization is intensively penetrating the industrial Eco-system, bringing its benefits by generating or improving new complementary functionalities and associated business, providing a feasible way to interconnect stakeholders within the value chain and supply-chain, as well as along the product and system's Life-Cycle, which can share digitalized data and information in form of Added-value Services. To facilitate perform those businesses, Industry 4.0-compliant service-oriented infrastructures are required. Functionalities and associated data and information can be provided/exposed and/or consumed as services by systems of Cyber-physical things. In the language of Industry 4.0, those physical things are identified as"Assets". Each physical"Asset" has associated a Cyber-part, the so called Asset Administration Shell (AAS), which contains a set of digitalized Data/Information/Function-Models, i.e., Digital Twins, and responsible for supporting an Industry 4.0-compliant communication/networking of the digitalized Asset. The AAS is fully responsible for the provision, exposition, consumption, composition, orchestration of services. The broad adoption of the AAS in a digitalized industrial environment is mainly depending on the costs of the digitalization-migration-process, which needs to respond to a set of functional and technical requirements. Among others, requirements for using Low-Cost technologies supporting the implementation of AAS with low energy consumption, efficiency and flexibility, should essentially be fulfilled. In this scenario, the authors present a service-collector of AAS that is implemented in commercial low-cost technology and deployed in a common Industry 4.0-compliant network, using REST-API and and OPC UA based infrastructure. The paper describes also the corresponding algorithm to perform the service-collection, based on the Python programming language, which is finally deployed and executed by a Single-Board Compute
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