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Clean Energy and Fuel (Hydrogen) Storage

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ISBN: 9783039216307 9783039216314 Year: Pages: 278 DOI: 10.3390/books978-3-03921-631-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

Clean energy and fuel storage are often required for both stationary and automotive applications. Some of these clean energy and fuel storage technologies currently under extensive research and development include hydrogen storage, direct electric storage, mechanical energy storage, solar–thermal energy storage, electrochemical (batteries and supercapacitors), and thermochemical storage. The gravimetric and volumetric storage capacity, energy storage density, power output, operating temperature and pressure, cycle life, recyclability, and cost of clean energy or fuel storage are some of the factors that govern efficient energy and fuel storage technologies for potential deployment in energy harvesting (solar and wind farms) stations and onboard vehicular transportation. This Special Issue thus serves the need for promoting exploratory research and development on clean energy and fuel storage technologies while addressing their challenges to practical and sustainable infrastructures.

Keywords

dye-sensitized solar cells --- carbon materials --- Ag nanoparticles --- freestanding TiO2 nanotube arrays --- gas turbine engine --- lean direct injection --- four-point --- low emissions combustion --- carbonate gas reservoirs --- water invasion --- recovery factor --- aquifer size --- production rate --- hydrogen storage --- complex hydrides --- nanocatalyst --- LiNH2 --- MgH2 --- ball milling --- Li-ion batteries --- nanocomposite materials --- cathode --- anode --- binder --- separator --- ionic liquid --- vertically oriented graphene --- electrical double layers --- charge density --- capacitance --- gas storage --- material science --- rock permeability --- synthetic rock salt testing --- Klinkenberg method --- hydrogen storage systems --- hydrogen absorption --- thermochemical energy storage --- metal hydride --- magnetism --- heat transfer enhancement --- Power to Liquid --- Fischer–Tropsch --- dynamic modeling --- lab-scale --- lithium-ion batteries --- simplified electrochemical model --- state of charge estimator --- extended kalman filter --- hot summer and cold winter area --- PCM roof --- comprehensive incremental benefit --- conjugate phase change heat transfer --- lattice Boltzmann method --- large-scale wind farm --- auxiliary services compensation --- battery energy storage system --- optimal capacity --- equivalent loss of cycle life --- hydrogen storage --- porous media --- bacterial sulfate reduction --- methanogenesis --- gas loss --- diffusion --- reactive transport modeling --- PHREEQC --- energy discharge --- bubbles burst --- bubbles transportation --- crystal growth rates --- undercooling --- salt cavern --- leaching tubing --- flutter instability --- flow-induced vibration --- internal and reverse external axial flows --- thermal energy storage (TES) --- slag --- regenerator --- concentrated solar power (CSP) --- quality function deployment (QFD) --- failure mode and effect analysis (FMEA) --- thermal energy storage --- electrochemical energy storage --- hydrogen energy storage --- salt cavern energy storage

New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

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ISBN: 9783039282906 9783039282913 Year: Pages: 428 DOI: 10.3390/books978-3-03928-291-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Industrial Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Modern factories are experiencing rapid digital transformation supported by emerging technologies, such as the Industrial Internet of things (IIOT), industrial big data and cloud technologies, deep learning and deep analytics, AI, intelligent robotics, cyber-physical systems and digital twins, complemented by visual computing (including new forms of artificial vision with machine learning, novel HMI, simulation, and visualization). This is evident in the global trend of Industry 4.0. The impact of these technologies is clear in the context of high-performance manufacturing. Important improvements can be achieved in productivity, systems reliability, quality verification, etc. Manufacturing processes, based on advanced mechanical principles, are enhanced by big data analytics on industrial sensor data. In current machine tools and systems, complex sensors gather useful data, which is captured, stored, and processed with edge, fog, or cloud computing. These processes improve with digital monitoring, visual data analytics, AI, and computer vision to achieve a more productive and reliable smart factory. New value chains are also emerging from these technological changes. This book addresses these topics, including contributions deployed in production, as well as general aspects of Industry 4.0.

Keywords

cutting insert selection --- cutting parameter optimization --- artificial neural networks --- genetic algorithm --- connected enterprise --- smart manufacturing --- big data --- machine learning --- data reduction --- predictive analytics --- in-line dimensional inspection --- warm forming --- 3D mesh reconstruction --- optical system --- revolution workpiece --- defect detection --- polymer lithium-ion battery --- convolutional neural network --- deep learning --- blister defect --- flower pollination algorithm --- Industry 4.0 --- anomaly detection --- scheduling --- neural network --- skyline queries --- Cyber-Physical Systems (CPS) --- scalability test --- Internet of Things (IoT) --- INDUSTRY 4.0 --- economic recession --- research and development indicators --- maintenance expert --- competence --- decision support --- micro-armature --- defect detection --- convolutional neural networks --- computer vision --- capacity control --- job shop systems --- RMTs --- operator theory --- 4th industrial revolution --- industry 4.0 --- AHP --- QFD --- matching --- fibre of preserved Szechuan pickle --- contour detection --- dilated convolutions --- HED --- social network --- industry 4.0 --- industrial knowledge graph --- deep learning --- industrial big data --- intellectualization of industrial information --- digital manufacturing --- smart factory --- Industry 4.0 --- digital platforms --- automated surface inspection --- D-VGG16 --- bilinear model --- Grad-CAM --- classification --- localization --- elliptical paraboloid array --- self-calibration method --- vertex distance --- optical slope sensor --- geometric relationship --- relative angle --- fabric defect detection --- LGM --- FCM --- image smoothing --- Industry 4.0 --- marketing innovations --- innovative marketing tools --- impacts marketing innovations --- Industry 4.0 --- configure-to-order --- BIM --- construction equipment --- digital information flow --- lean assembly --- digital twins --- cyber-physical production systems --- depthwise separable convolution --- YOLOv3 --- feature pyramid --- aircraft structure crack detection --- industrial load management --- demand-side management --- demand-side response --- energy flexibility --- IT concept --- platform-based ecosystem --- control service --- smart service --- control as a service --- cloud-based control system --- automation system --- chatter --- train wheel --- smart system --- turning --- edge computing --- n/a

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english (2)


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2020 (1)

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