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Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.
artificial neural network --- downscaling --- innovative methods --- reservoir inflow forecasting --- simulation --- extreme events --- climate variability --- sparse monitoring network --- weighted mean analogue --- sampling errors --- precipitation --- drought indices --- discrete wavelet --- SWSI --- hyetograph --- trends --- climate change --- SIAP --- Kabul river basin --- Hurst exponent --- extreme rainfall --- evolutionary strategy --- the Cauca River --- hydrological drought --- global warming --- least square support vector regression --- polynomial normal transform --- TRMM --- satellite data --- Fiji --- heavy storm --- flood regime --- compound events --- random forest --- uncertainty --- seasonal climate forecast --- INDC pledge --- Pakistan --- wavelet artificial neural network --- HBV model --- temperature --- APCC Multi-Model Ensemble --- meteorological drought --- flow regime --- high resolution --- rainfall --- clausius-clapeyron scaling --- statistical downscaling --- ENSO --- forecasting --- variation analogue --- machine learning --- extreme rainfall analysis --- hydrological extremes --- multivariate modeling --- monsoon --- non-stationary --- support vector machine --- ANN model --- stretched Gaussian distribution --- drought prediction --- non-normality --- statistical analysis --- extreme precipitation exposure --- drought analysis --- extreme value theory --- streamflow --- flood management
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Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications.
Technology: general issues --- History of engineering & technology --- LIM --- slip frequency --- linear induction motor --- automatic train operation --- rotor field-oriented angle error --- indirect rotor field-oriented control --- induction machine drives --- model-based prediction --- linear induction motors --- finite element analysis --- end effect --- induction machines --- electrical machines --- thermal modeling --- soft magnetic material --- thermal conductivity --- induction motor --- solid rotor --- effective parameters --- finite element method --- modelling of ring induction motors --- Monte Carlo method --- accurate modelling --- induction machine --- electromagnetic models --- model selection --- optimization --- artificial neural networks --- pattern search --- evolutionary strategy --- simulated annealing --- artificial neural network --- fourth central moment --- homogeneity analysis --- induction motors --- mechanical unbalance --- one broken rotor bar --- outer-race bearing fault --- startup transient current --- two broken rotor bars --- three-phase induction motor --- squirrel-cage rotor --- energy efficiency --- motor performance --- n/a --- dynamic model --- Matlab/Simulink --- rotor winding --- stator winding
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Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications.
LIM --- slip frequency --- linear induction motor --- automatic train operation --- rotor field-oriented angle error --- indirect rotor field-oriented control --- induction machine drives --- model-based prediction --- linear induction motors --- finite element analysis --- end effect --- induction machines --- electrical machines --- thermal modeling --- soft magnetic material --- thermal conductivity --- induction motor --- solid rotor --- effective parameters --- finite element method --- modelling of ring induction motors --- Monte Carlo method --- accurate modelling --- induction machine --- electromagnetic models --- model selection --- optimization --- artificial neural networks --- pattern search --- evolutionary strategy --- simulated annealing --- artificial neural network --- fourth central moment --- homogeneity analysis --- induction motors --- mechanical unbalance --- one broken rotor bar --- outer-race bearing fault --- startup transient current --- two broken rotor bars --- three-phase induction motor --- squirrel-cage rotor --- energy efficiency --- motor performance --- n/a --- dynamic model --- Matlab/Simulink --- rotor winding --- stator winding
Choose an application
Induction machines are one of the most important technical applications for both the industrial world and private use. Since their invention (achievements of Galileo Ferraris, Nikola Tesla, and Michal Doliwo-Dobrowolski), they have been widely used in different electrical drives and as generators, thanks to their features such as reliability, durability, low price, high efficiency, and resistance to failure. The methods for designing and using induction machines are similar to the methods used in other electric machines but have their own specificity. Many issues discussed here are based on the fundamental achievements of authors such as Nasar, Boldea, Yamamura, Tegopoulos, and Kriezis, who laid the foundations for the development of induction machines, which are still relevant today. The control algorithms are based on the achievements of Blaschke (field vector-oriented control) and Depenbrock or Takahashi (direct torque control), who created standards for the control of induction machines. Today’s induction machines must meet very stringent requirements of reliability, high efficiency, and performance. Thanks to the application of highly efficient numerical algorithms, it is possible to design induction machines faster and at a lower cost. At the same time, progress in materials science and technology enables the development of new machine topologies. The main objective of this book is to contribute to the development of induction machines in all areas of their applications.
Technology: general issues --- History of engineering & technology --- LIM --- slip frequency --- linear induction motor --- automatic train operation --- rotor field-oriented angle error --- indirect rotor field-oriented control --- induction machine drives --- model-based prediction --- linear induction motors --- finite element analysis --- end effect --- induction machines --- electrical machines --- thermal modeling --- soft magnetic material --- thermal conductivity --- induction motor --- solid rotor --- effective parameters --- finite element method --- modelling of ring induction motors --- Monte Carlo method --- accurate modelling --- induction machine --- electromagnetic models --- model selection --- optimization --- artificial neural networks --- pattern search --- evolutionary strategy --- simulated annealing --- artificial neural network --- fourth central moment --- homogeneity analysis --- induction motors --- mechanical unbalance --- one broken rotor bar --- outer-race bearing fault --- startup transient current --- two broken rotor bars --- three-phase induction motor --- squirrel-cage rotor --- energy efficiency --- motor performance --- dynamic model --- Matlab/Simulink --- rotor winding --- stator winding --- LIM --- slip frequency --- linear induction motor --- automatic train operation --- rotor field-oriented angle error --- indirect rotor field-oriented control --- induction machine drives --- model-based prediction --- linear induction motors --- finite element analysis --- end effect --- induction machines --- electrical machines --- thermal modeling --- soft magnetic material --- thermal conductivity --- induction motor --- solid rotor --- effective parameters --- finite element method --- modelling of ring induction motors --- Monte Carlo method --- accurate modelling --- induction machine --- electromagnetic models --- model selection --- optimization --- artificial neural networks --- pattern search --- evolutionary strategy --- simulated annealing --- artificial neural network --- fourth central moment --- homogeneity analysis --- induction motors --- mechanical unbalance --- one broken rotor bar --- outer-race bearing fault --- startup transient current --- two broken rotor bars --- three-phase induction motor --- squirrel-cage rotor --- energy efficiency --- motor performance --- dynamic model --- Matlab/Simulink --- rotor winding --- stator winding
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