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Energies SI Book "Selected Papers from the ICEUBI2019 – International Congress on Engineering – Engineering for Evolution", groups six papers into fundamental engineering areas: Aeronautics and Astronautics, and Electrotechnical and Mechanical Engineering. ICEUBI—International Congress on Engineering is organized every two years by the Engineering Faculty of Beira Interior University, Portugal, promoting engineering in society through contact among researchers and practitioners from different fields of engineering, and thus encouraging the dissemination of engineering research, innovation, and development. All selected papers are interrelated with energy topics (fundamentals, sources, exploration, conversion, and policies), and provide relevant data for academics, research-focused practitioners, and policy makers.

Technology: general issues --- HVAC --- water-cooled condenser --- air-cooled condenser --- evaporative --- TWI --- turbulence modeling --- supercritical injection --- Liquid Rocket Engines --- energy saving and efficiency --- aerodynamic coefficients --- propulsive efficiency --- bioenergetics --- biomimetics --- grid-tied inverter --- grey wolf optimizer --- PR controllers --- LCL filter --- passive damping --- propeller --- aircraft --- turboprop --- flight efficiency --- flight speed --- hydro-thermal coordination --- Lagrangian relaxation --- Lagrangian dual problem --- Lagrange multipliers --- subgradient methods --- step-size update algorithm

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Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries.

Technology: general issues --- History of engineering & technology --- fault detection --- deep learning --- transfer learning --- anomaly detection --- bearing --- wind turbines --- misalignment --- fault diagnosis --- information fusion --- improved artificial bee colony algorithm --- LSSVM --- D–S evidence theory --- optimal bandwidth --- kernel density estimation --- JS divergence --- domain adaptation --- partial transfer --- subdomain --- rotating machinery --- gearbox --- signal interception --- peak extraction --- cubic spline interpolation envelope --- combined fault diagnosis --- empirical wavelet transform --- grey wolf optimizer --- low pass FIR filter --- support vector machine --- satellite momentum wheel --- Huffman-multi-scale entropy (HMSE) --- support vector machine (SVM) --- adaptive particle swarm optimization (APSO) --- rail surface defect detection --- machine vision --- YOLOv4 --- MobileNetV3 --- multi-source heterogeneous fusion --- n/a --- D-S evidence theory

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Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries.

fault detection --- deep learning --- transfer learning --- anomaly detection --- bearing --- wind turbines --- misalignment --- fault diagnosis --- information fusion --- improved artificial bee colony algorithm --- LSSVM --- D–S evidence theory --- optimal bandwidth --- kernel density estimation --- JS divergence --- domain adaptation --- partial transfer --- subdomain --- rotating machinery --- gearbox --- signal interception --- peak extraction --- cubic spline interpolation envelope --- combined fault diagnosis --- empirical wavelet transform --- grey wolf optimizer --- low pass FIR filter --- support vector machine --- satellite momentum wheel --- Huffman-multi-scale entropy (HMSE) --- support vector machine (SVM) --- adaptive particle swarm optimization (APSO) --- rail surface defect detection --- machine vision --- YOLOv4 --- MobileNetV3 --- multi-source heterogeneous fusion --- n/a --- D-S evidence theory

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This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book.

Technology: general issues --- History of engineering & technology --- flexible job-shop scheduling problem --- combinatorial optimization --- genetic algorithm --- candidate order-based genetic algorithm --- multichromosome --- facility layout --- optimization --- metaheuristic algorithm --- cell formation --- design of experiments --- digital platforms --- decision-making --- insurance --- Baltic --- customization --- personalization --- assembly line balancing --- group technology --- cluster algorithm --- bottleneck station --- output rate --- tolerance allocation --- machine and process selection --- heuristic approach --- univariate search method --- whale optimization algorithm --- selective assembly --- overrunning clutch assembly --- harmony search algorithm --- Hastelloy X --- turning --- cutting force --- surface roughness --- liquid nitrogen --- grass-hooper optimization algorithm --- moth-flame optimization algorithm --- hybrid bat algorithm --- optimization problem --- the distributed assembly permutation flowshop scheduling problem --- variable neighborhood descent --- multi-criteria assessment --- cell manufacturing design --- operational complexity --- makespan --- production line balancing rate --- electrochemical machining (ECM) --- material removal rate (MRR) --- nickel presence (NP) --- grey wolf optimizer (GWO) --- moth-flame optimization algorithm (MFO) --- Monel 400 alloys --- n/a

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This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- allied in-situ injection and production (AIIP) --- CO2 huff and puff --- shale oil reservoirs --- enhanced oil recovery --- renewable energy sources --- forecasting --- Weibull distribution --- neural networks --- optimal economic dispatch --- particle swarm optimization --- distribution network (DN) --- doubly-fed induction generator (DFIG) --- feeder automation (FA) --- compatibility --- adaptive control strategy (ACS) --- coordination technology --- air-cooled condenser --- mechanical draft wet-cooling towers --- hot recirculation rate --- complex building environment --- numerical simulation --- Neutral Point Clamped Z-Source Inverter (NPCZSI) --- shoot-through duty ratio --- modulation index --- voltage gain --- power quality --- dynamic modeling --- DC-DC converter --- electric vehicle (EV) --- charge pump capacitor --- fuzzy logic control --- maximum power point tracking --- photovoltaic --- push pull converter --- off-grid voltage source inverter --- medium voltage distribution network --- switch station --- electric vehicle --- DC–DC converter --- reconfiguration --- orderly charging --- grey wolf optimizer --- electrical harmonics --- harmonic estimation --- total harmonic distortion --- battery energy storage system --- third-harmonic current injection --- high efficiency --- active damping