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The earth’s magnetosphere is an intricate input–output system, where the inputs are the solar wind parameters and the output measure are the geomagnetic. The disturbance storm time (DST) index is one such quantity measure for the intensity of disturbance in the geomagnetic field due to the magnetic storm. The geomagnetic activities have catastrophic effects on several communication networks and harmful for biological livings. Therefore, it is significant to develop a model for the prediction of disturbance in the geomagnetic field. This paper presents linear as well as nonlinear parametric techniques to model the complex magnetosphere dynamics. Neural network (NN)-based modeling techniques, such as feed-forward NN (FFNN), NN integrated with nonlinear autoregression with exogenous (NARX) inputs, adaptive neuro-fuzzy inference system (ANFIS), and recurrent NN are developed for the prediction of the magnetic storm. Global search algorithms, such as particle swarm optimization and genetic algorithm, also train the developed FFNNs. All the models are trained on 15 years’ real-time series data of solar wind parameters and DST index on a frequency of 1 h. The accuracy of the predicted DST index for multiple intensity levels of the magnetic storm using all developed linear and nonlinear modeling techniques is presented, compared, and analyzed thoroughly. The performance of NN integrated with NARX inputs and ANFIS is higher than rest of methods developed in the paper. Both techniques have the capability to predict mild, moderate, and intense magnetic storm with high degree of accuracy. The comparative analysis with state of the art shows the enhanced accuracy and robustness of developed models in this paper. [ABSTRACT FROM AUTHOR]

Simulating the interaction of RF-waves with charged particle beams is difficult and computationally expensive, even on present high-end computers. There is a tradeoff between fidelity and complexity/expense of the two primary techniques, particle-in-cell and envelope methods. This paper presents an approach based on the partial decomposition of the Maxwell equations to achieve a fully second-order set of ordinary differential equations (ODEs) describing the interaction. It has the potential for self-consistent inclusion of ac and dc space-charge effects through a solution of evanescent ODEs, effects that are handled poorly, if at all, by existing envelope methods. The resulting technique provides flexibility in adjusting simulation fidelity versus computational costs. The developments presented in this paper establish a mathematical framework for this technique and test its core aspects by demonstrating accurate solution of the ODEs using analytic sources. [ABSTRACT FROM AUTHOR]

This paper proposes an all-in-one system for hyperloop that conducts propulsion, levitation, and guidance. Currently demand on high-speed long-distance transportation is increasing, so that hyperloop is getting attention and studied hard globally. Hyperloop is a new innovative transportation in which a levitated subsonic speed train travels through a vacuum cylindrical tube. Hyperloop needs functions of propulsion, levitation, and guidance for its service, and many devices are necessary for those functions. In the tube, a constrained space, many devices make the entire system complicated, and the size of the vehicle and tube are increased. Therefore, the costs of maintenance, manufacture, and construction are increased and control of each device becomes very difficult. But a non-symmetric double-sided linear induction motor (NSDLIM), the subject of this paper, is an all-in-one system that could conduct all functions. In this paper, the concept of NSDLIM was introduced and its possibility was suggested. Requirements of NSDLIM were investigated considering very high acceleration, velocity, and low air pressure. An NSDLIM model was designed and analyzed by using the finite-element method. Then, NSDLIM parameters that affect performance were investigated and adjusted to improve performance. The derived model performance was shown, and its possibility was considered. [ABSTRACT FROM AUTHOR]

Singular divergence-conforming bases have been proposed for the solution of integral equations although they have seen only occasional use in practical applications. The existing singular bases are not hierarchical, which prevents their use in adaptive $ {p}$ -refinement applications. In this paper, a new family of singular hierarchical basis functions is proposed for quadrilateral cells. These functions model the singularities associated with current and charge density at edges and are more convenient for modeling such singularities than triangular bases of the same kind. The basis functions are of the additive kind and combine a hierarchical polynomial representation on quadrilaterals with linearly independent singular terms that incorporate general exponents that may be adjusted for the specific wedge angle of interest. Moreover, the added singular basis functions are computed on the fly. On the basis of various reported numerical results, this paper also illustrates the difficulties, the advantages, the accuracy, and the cost of using such bases in the method of moment solutions of integral equations. [ABSTRACT FROM AUTHOR]

This paper presents parameter values and ranges of static load models used in a power system analysis for the representation of both individual electrical devices and aggregate system loads. The paper discusses and correlates load models and their parameters following statistical processing of the responses of around 100 transmission system operators and utilities around the world, who participated in a survey initiated by CIGRE Working Group C4.605, with the corresponding information on load models and their parameter values from the existing literature. According to the survey, the most frequently used static load models are voltage dependent, and voltage and frequency dependent exponential load models. The identified typical parameter values and ranges of these static load models, both for low voltage devices and for aggregate loads at higher voltage levels, are results of the analysis of a large number of data. Based on these results, the paper provides recommendations for their further use in power system studies and also introduces a novel method for obtaining the mean values and ranges of parameters of the aggregate system load models. [ABSTRACT FROM AUTHOR]

Magnetic flux leakage (MFL) response predicting is important for defect estimation. This paper first proposes a concept of basic signal by discovering the combination property of the MFL response. The basic signal can be used to predict the MFL response conveniently by a basic signal combination method (BSCM), which is also innovatively put forward in this paper. In this method, the basic signal is calculated in advance, and the MFL response can be calculated by several transformation and combination operations. Both the simulation and experimental results demonstrate the feasibility of BSCM. Compared with other traditional methods (magnetic dipole method and finite-element method), BSCM shows a good performance on both the computational speed and accuracy. [ABSTRACT FROM AUTHOR]

In this paper, the pinning process of pinned photodiodes (PPDs) is described by a new analytical model, assuming the PPD to be composed of inner and junction regions. There are two definitions of the pinning potential: maximum conduction band potential variation ($\Delta \varphi _{M}$) and maximum electron quasi-fermi level potential variation ($\Delta $ FP $_{M}$). The output of the previous pinning potential models is only an approximation of $\Delta \varphi _{M}$. In this paper, a comprehensive model is proposed in which both aforementioned definitions of pinning potential can be achieved analytically. The proposed model is a system of equations relating PPD’s main characteristics such as $\Delta \varphi _{M}$ and equilibrium full-well capacity to other main PPD parameters such as PPD spatial dimensions, impurity dopant concentrations, maximum inner region potential, and remnant carrier population at $\Delta \varphi _{M}$. The proposed model is verified by two previously reported experiment-based data. [ABSTRACT FROM AUTHOR]

The papers in this special section brings together papers focused on the recent advancements and breakthroughs in the technology of modeling and enhanced active/reactive power control of wind power conversion systems, ranging from components of wind turbines to wind farms. [ABSTRACT FROM PUBLISHER]

The acquired industrial data often contain missing outputs because of the irregularities of complicated industrial environment, which make the outputs of the training dataset incomplete. In this paper, a semi-supervised sparse Bayesian regression model is proposed for dealing with the incomplete outputs problem by employing a variational inference technique. Within the settings of specific hierarchical priors over the missing outputs, in this paper, we derive the posterior probability distribution over the uncertain variables including the missing outputs. Given that the posterior distribution is not analytically tractable, a hybrid learning procedure is designed for combining the variational inference with a gradient-based method to obtain optimal approximate posteriors. To verify the performance of the proposed method, a number of comparative experiments are conducted and analyzed by using the datasets (including artificial and real world ones) coming with different proportions of missing outputs. Compared to the existing semi-supervised regression approaches, we demonstrated the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The critical nature of vehicular communications requires their extensive testing and evaluation. Analytical models can represent an attractive and cost-effective approach for such evaluation if they can adequately model all underlying effects that impact the performance of vehicular communications. Several analytical models have been proposed to date to model vehicular communications based on the IEEE 802.11p (or DSRC) standard. However, existing models normally model in detail the MAC (Medium Access Control), and generally simplify the propagation and interference effects. This reduces their value as an alternative to evaluate the performance of vehicular communications. This paper addresses this gap, and presents new analytical models that accurately model the performance of vehicle-to-vehicle communications based on the IEEE 802.11p standard. The models jointly account for a detailed modeling of the propagation and interference effects, as well as the impact of the hidden terminal problem. The model quantifies the PDR (Packet Delivery Ratio) as a function of the distance between transmitter and receiver. The paper also presents new analytical models to quantify the probability of the four different types of packet errors in IEEE 802.11p. In addition, the paper presents the first analytical model capable to accurately estimate the Channel Busy Ratio (CBR) metric even under high channel load levels. All the analytical models are validated by means of simulation for a wide range of parameters, including traffic densities, packet transmission frequencies, transmission power levels, data rates and packet sizes. An implementation of the models is provided openly to facilitate their use by the community. [ABSTRACT FROM AUTHOR]

Supporting parallel multi-priority data streams is vital for maintaining the quality of service (QoS) in vehicle-to-everything (V2X) communication. Hence, the European telecommunications standard institute (ETSI) has defined four packet types, with varying priority levels, to be used as broadcast packets in such communication. This paper studies the medium access control (MAC) layer performance of IEEE 802.11p and cellular-V2X (C-V2X) Mode 4 using discrete-time Markov chain (DTMC) based models, while considering parallel multi-priority data streams. The overall model consists of four queue models with their respective traffic generators, which are appropriately linked with the DTMCs modeling the MAC layer operations of IEEE 802.11p and C-V2X Mode 4. Closed-form solutions for the steady-state probabilities of the models are obtained, which are then utilized to derive expressions for key performance indicators at the MAC layer. Numerical results are provided to draw insights on the MAC layer performance of the two technologies. IEEE 802.11p is comparatively superior in average delay, and at maintaining fairness among multi-priority data streams, whereas C-V2X Mode 4 exhibits better collision resolution, which leads to its higher throughput. The paper also includes design insights on possible performance enhancements for future releases. [ABSTRACT FROM AUTHOR]

This paper presents a fast analytical model for estimating the components of the PM flux density distribution in the air-gap for a number of interior permanent magnet synchronous machines (IPMSMs). Deriving the two-dimensional (2-D) analytical model for IPMSMs is more challenging compared to that of surface-mounted permanent magnet synchronous machines (SPMSMs) due to the inconsistent geometry of the rotor in polar coordinates. IPMSMs are usually modeled by using 0-D or 1-D methods such as the magnetic equivalent circuit (MEC); however, the MEC method is unable to take into account the tangential component of the magnetic flux density vector. In this paper, a 2-D analytical no-load electromagnetic model for five rotor topologies of IPMSMs is proposed. The effects of the stator slots on the radial component of the PM flux density distribution in the air-gap are then included by defining an air-gap function. The effects of the stator slots on the tangential components of the PM flux density distribution in the air-gap are also considered by injecting virtual surface currents (VSCs) or virtual permanent magnets (VPMs). For verification purposes, the analytical results are compared with those of the finite element method (FEM) and the experimental results of one of the cases. [ABSTRACT FROM AUTHOR]

Magnetic gears can perform the same function as mechanical gears with the added benefits inherent to contactless power transfer. However, quick and accurate analysis tools are required for magnetic gears to reach their full potential. As end effects can significantly impact the slip torque of a magnetic gear, 2D models often overestimate the slip torques, so 3D models are frequently required. Therefore, this paper proposes a 3D linear Magnetic Equivalent Circuit (MEC) or reluctance network model of radial flux magnetic gears with surface mounted magnets. This is an extension of a previously developed 2D MEC model, and, like the previous 2D model, it is thoroughly parametrized so that it can be directly applied to a wide range of parametric cases. This is Part I of a two-part paper and focuses on the implementation of the 3D MEC model. Part II compares the 3D MEC model against nonlinear finite element analysis (FEA) models to validate the MEC model's accuracy and to develop guidelines for discretizing the geometry. [ABSTRACT FROM AUTHOR]

The short-circuit response of inverter-interfaced distributed generators (IIDGs) is not adequately represented in many conventional protection studies. This paper presents an in-depth analysis of IIDG behavior during grid faults and proposes a more accurate reduced-order parameterized short-circuit current (RPSC) model of inverters. Typical inverter components are thoroughly investigated to identify those that play dominant roles during faults. The paper shows that the current limiter is the dominant factor for the steady-state fault-current of inverter; while the inverter filter along with the severity of the voltage disturbance largely determine the initial transient spike of inverter fault current. The proposed model is low-order and can be used in large scale simulations. The parameters of the proposed RPSC model can be extracted from laboratory experiments without requiring proprietary manufacturer information. The proposed fault-current model is analogous to the well-known synchronous machine model that segregates the inverter fault current into subtransient, transient, and steady-state fault currents. Experimental and simulation tests are presented to validate the model. [ABSTRACT FROM AUTHOR]

This paper discusses the back-flashover (BFO) phenomena in a high-voltage (HV) vertical double-circuit transmission line by means of numerical simulations. The single- and multiphase BFOs are analyzed considering 24 cases of AC-voltage angles and nonlinear characteristic of flashovers, taking advantage of the circuit analysis method in time domain. The models used in circuit analysis are the TEM-delay model, which can take into account the non-TEM characteristics of tower and line, and the conventional models. Prior to the BFO analysis, the characteristics of circuit models are compared and discussed with the numerical electromagnetic analysis results. In BFO analysis, it is clarified that the occurrence probability of the multiphase BFO is heavily depending on the bias AC-voltages. The relation of measured BFO phases and AC-voltages are well explained by the TEM-delay model with the valid lightning current magnitude. The conventional circuit models could have underestimated the occurrence of BFOs in HV transmission lines. The analysis and discussions shown in this paper can be utilized for advanced evaluation of lightning performance of transmission lines that considers the seriousness of lightning accidents. [ABSTRACT FROM AUTHOR]

This paper reports on the design optimization of double gate (DG) tunnel FET (TFET) for dynamic memory applications in sub-100-nm regime. It is shown that incorporation of lateral spacing ( L_ \text gap) between the gates, and an underlap region ( L\text {un}) between drain and back gate reduces state “0” degradation, which along with optimal biases, results in an improved Retention Time (RT) at 85 °C. The systematic design optimization increases RT from ~80 to ~300 ms with the use of L\text {gap} at 85 °C, which can be further improved to ~600 ms with the introduction of L\text {un} . The careful investigation shows the back gate scaled down to 25 nm with a front gate region of 100 nm, and operation even at elevated temperatures (125 °C). The insights into DG TFET DRAM operation in terms of individual as well as total lengths highlights the RT enhancement by a factor of 3 with constant total length (200 nm) and an improved scalability with total length scaled down to 160 nm. This paper provides new opportunities to realize TFET-based DRAM with improved RT, scalability, and high temperature operation. [ABSTRACT FROM PUBLISHER]

In this paper, the effects of motion blur on 2-D digital image correlation (DIC) measurements are discussed, with a particular focus on the description of displacement measurement uncertainty. The research started with the simulation of motion blur with a suitable literature-based algorithm. Then the state of the art of uncertainty analysis in the context of DIC was compared with simulation results, and it was found that the effects of motion blur on uncertainty are not predicted correctly by the literature models. This phenomenon is explained by the fact that the literature models do not consider motion blur. Consequently, a simple monodimensional case is analyzed. In this way, it has been possible to evaluate the sensitivity of DIC correlation function [evaluated as the sum of squared differences (SSD)] to motion blur. Using these results, it is possible to extend the analysis to the case of a generic image with the help of a power-law model. Eventually, the model proposed in this paper is able to represent the effects of motion blur correctly. [ABSTRACT FROM AUTHOR]

Automated scene analysis has been a topic of great interest in computer vision and cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded scene analysis has attracted much attention. However, the visual occlusions and ambiguities in crowded scenes, as well as the complex behaviors and scene semantics, make the analysis a challenging task. In the past few years, an increasing number of works on the crowded scene analysis have been reported, which covered different aspects including crowd motion pattern learning, crowd behavior and activity analyses, and anomaly detection in crowds. This paper surveys the state-of-the-art techniques on this topic. We first provide the background knowledge and the available features related to crowded scenes. Then, existing models, popular algorithms, evaluation protocols, and system performance are provided corresponding to different aspects of the crowded scene analysis. We also outline the available datasets for performance evaluation. Finally, some research problems and promising future directions are presented with discussions. [ABSTRACT FROM PUBLISHER]

This research paper presents and comments on analytical models for calculating the widths of cracks formed as a result of imposed deformations generating tensile stresses in reinforced concrete base-restrained members. This issue regarding the mechanics of concrete structures has been presented on the basis of calculation models since 1968. In accordance with the current regulations of the European standard, the mechanics of the cracking of base-restrained members have been presented in a very simplified way, which was justified by a limited number of research studies performed on such members as well as in a few subject publications. The main purpose of this work was to present especially those models that had the greatest practical significance within a specific period of time or formed the basis for further studies of other authors. In addition, future trends in the development of computational tools are presented. The chronologically presented development of design ideas, which takes into account varying degrees of advancement of the mechanics of cracking due to the distinctly different design consequences, is a valuable source of information and an inspiration for subsequent researchers. In the second part of the paper, a few of the most important issues connected with the calculation of the crack width in base-restrained walls are presented. It is shown that currently, on the basis of the up-to-date knowledge, there are possibilities to create more complementary standard guidelines, which is already taking place in the case of European guidelines. [ABSTRACT FROM AUTHOR]

This paper concerns the force density optimization for medium-stroke reluctance actuators applied in antivibration applications. The force density in a conventional E-core reluctance actuator is limited for medium strokes by the nonlinear force–displacement characteristic. In this paper, different tooth topologies are analyzed to maximize the force density along the stroke using the finite-element analysis. Teeth parameters are tuned in each topology to analyze the influences on the force density over a stroke of $\pm$12.5 mm. An analytic thermal model is used to estimate the surface temperature and is verified with finite-element simulations. The optimal topology is validated by experiments on a prototype. [ABSTRACT FROM AUTHOR]

This paper aims at proposing an unsupervised hierarchical nonparametric Bayesian framework for modeling axial data (i.e., observations are axes of direction) that can be partitioned into multiple groups, where each observation within a group is sampled from a mixture of Watson distributions with an infinite number of components that are allowed to be shared across different groups. First, we propose a hierarchical nonparametric Bayesian model for modeling grouped axial data based on the hierarchical Pitman-Yor process mixture model of Watson distributions. Then, we demonstrate that by setting the discount parameters of the proposed model to 0, another hierarchical nonparametric Bayesian model based on hierarchical Dirichlet process can be derived for modeling axial data. To learn the proposed models, we systematically develop a closed-form optimization algorithm based on the collapsed variational Bayes (CVB) inference. Furthermore, to ensure the convergence of the proposed learning algorithm, an annealing mechanism is introduced to the framework of CVB inference, leading to an averaged collapsed variational Bayes inference strategy. The merits of the proposed models for modeling grouped axial data are demonstrated through experiments on both synthetic data and real-world applications involving gene expression data clustering and depth image analysis. [ABSTRACT FROM AUTHOR]

The increasing penetration of distributed renewable energy sources drastically alters the dynamic characteristics of distribution networks (DNs). Therefore, several equivalent models have been recently proposed, to analyze more accurately the complex behavior of modern DNs. However, relatively simple models are still commonly used in practice for dynamic power system studies. In addition, dynamic equivalent models for DNs are sensitive to different operating conditions and there is lack of systematic understanding of their performance. Scope of this paper is to propose a methodology for identifying the applicability range in terms of accuracy and generalization capability of several conventional and newly developed equivalent models for the dynamic analysis of modern DNs. A set of metrics is used for the modelling accuracy assessment and a sensitivity analysis framework is introduced to fully quantify the generalization capabilities of DN equivalent models. Based on the above, guidelines and recommendations for the development of robust equivalent models for DN analysis are proposed. [ABSTRACT FROM AUTHOR]

Embracing outside-in open innovation (OI) can result in a plethora of organizational advantages, including improved innovation performance. Although some studies have found that outside-in OI improves innovation performance, others have shown that it has no effect or even a negative effect. This mixed empirical evidence leads to a need to unpack the relationship between outside-in OI and innovation performance, and to examine how certain key mediating variables related to the outside-in OI process can ensure that outside-in OI turns into improved innovation performance. Thus, this paper aims to examine the influence of outside-in OI on innovation performance considering the mediating roles of knowledge sharing and innovation strategy. This paper draws on a cross-industrial sample of 112 firms. Data are analyzed using a set of ordinary-least-squares regression models and the bootstrap procedure. Results show that knowledge sharing and innovation strategy fully mediate the relationship between outside-in OI and innovation performance. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) adoption provides an opportunity for high-technology-based, value-added processes and requires an infrastructural transformation and more qualified employee involvement. The I4.0 literature contains researches presenting an awareness, guidance, and complementary activities for an I4.0 concept. However, there is no detailed study focusing on the challenges and implementation problems in I4.0 adoption. Hence, the purpose of this paper is determining the I4.0 adoption challenges and analyzing these barriers based on the expert opinions. The methodology within the scope of this paper contains the literature review, interviews with experts who are responsible for the I4.0 projects at Bosch, analyzing the determined barriers by interpretive structural modeling (ISM) and cross impact matrix multiplication applied to classification (MICMAC) analysis. The barriers are investigated in a structural base, the relationships between these challenges have been identified, and finally how barriers affect each other has been presented in order to discover the root cause triggering the other factors. An I4.0 practitioner can infer from these two analysis results that which challenge should be focused first in order to reach a solution. Additionally, an ISM case study results provides a general view to the I4.0 adoption process. A practitioner can also decide on what to do first by criticizing the results so that they can reduce the negative effects of the adoption process. [ABSTRACT FROM AUTHOR]

This paper proposes an analytical model for the prediction of air gap magnetic field distribution for axial flux permanent magnet (AFPM) machine with various types of misalignments. The AFPM machine geometry is first transformed to a polar representation. Consequently, the subdomain model based on current sheet technique is developed. Then the stator coordinate system is chosen as reference coordinate to consider both static/dynamic angular and axis misalignments. The back electromagnetic forces and cogging torque are obtained accordingly based on Maxwell's equations. The results show that the proposed approach agrees with the finite-element method. The model is further validated by experiments under healthy, dynamic angular and axis misalignment conditions, which can validate the proposed approach. It turns out that the proposed approach can predict the performance of AFPM machines with types of misalignment quickly and effectively, which is greatly significant for further fault detection. [ABSTRACT FROM AUTHOR]

This paper develops an improved dynamic reliability model for compressor rotor system, defined as a “unconventional active system” here. First, regarding to the variety of system-component connections, system specific reliability modeling technique is presented, in which the stress and strength are both nonnegative stochastic processes. The new model fully considers the load characteristics of rotor blades, and inherently embodied the effect of the statistical dependence between the failures of the rotor blades. Then, calculated by the new model, the relationship between reliability and time, and that between the hazard rate and time, for a compressor rotor system are discussed, respectively. Comparing to the traditional series system reliability model, the new system reliability model developed in this paper has higher accuracy for compressor rotor system, since the traditional models neglect the difference between compressor rotor system and traditional active system. Moreover, in order to master the cruise characteristics of the aero-plane during reliability analysis of its compressor rotor blade set, a flight cruise is separated into several stages based on the value of Mach number and its change rate, and a subsection solution method is innovatively proposed accordingly. At the end of the paper, a certain cruise of fighter plane is analyzed to verify the accuracy of the new method. The results show that, as to a flight cruise with different stages, the new method is basically reasonable to most of the load histories, especially for the situation with impact loads existing. [ABSTRACT FROM AUTHOR]

In this paper, we modify the graph model for conflict resolution (GMCR) to model interactive unawareness of decision makers (DMs) about the options available to them in the conflict. More specifically, we consider a GMCR with two DMs, where a DM, in some given state, can be unconscious about some of his options, or about the options of his opponent, and therefore, may have only a partial knowledge of the state space. By interactive unawareness, it is meant that a DM can reason about the awareness level of the other DM and about the awareness level of the other DM regarding his or her own awareness level and so on. We generalize standard solution concepts for this model and illustrate its usefulness by means of a hypothetical war conflict. [ABSTRACT FROM AUTHOR]

This paper is concerned with control-oriented modeling of a class of wireless power transfer systems with a phase-shift-controlled inverter. Two methods are investigated: the analytical modeling method, which is based on physical laws, and the refined instrumental variable method, which is based on sampled data. It shows that the former provides physical insights into the system, and that the resulting models will be accurate if the true circuit component parameters are a priori known. Otherwise, the model accuracy may decline. By contrast, the latter provides a cheap solution for accurate modeling, based only on a set of sampled input–output data, and the resulting model can capture very well the dynamic behavior of the system within a defined operating range. In real applications, it is always hard to know the actual circuit component parameters, since they may drift from the nominal values, due to some reasons such as the aging of circuit components and the variation of coil placement, making the analytical modeling method not very accurate. Therefore, to preserve the virtues of both methods, it is suggested to use them as a combination, that is, using the analytical modeling method to determine the model structure while using the data-driven modeling method to estimate the model parameters. All results derived in this paper are verified by means of both numerical simulation and experimental validation. [ABSTRACT FROM AUTHOR]

Battery safety is one of the most crucial issues in the utilization of lithium-ion batteries (LiBs) for all-climate electric vehicles. Short circuit, overcharge, and overheat are three common field failures of LiBs. In this paper, online fault diagnosis for external short circuit (ESC) of LiB packs is investigated. The experiments are carried out to obtain and compare ESC characteristics of 18650-type NMC battery pack and single cell. Based on the analysis of experimental results, a two-step equivalent circuit model is established to describe the ESC process and an online model-based scheme is proposed to diagnose ESC faults of battery packs. The proposed scheme is evaluated by experimental data. The results show that it can effectively diagnose ESC faults in 3.5 s after their occurrences with the terminal voltage error less than 25 mV. The proposed scheme has shown great generalization ability. ESC faults of battery packs under different number of cells connected in series and unavailable current information can also be diagnosed at the terminal voltage error less than 48 and 60 mV, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we quantify the impact of uncertainty in predicted mobility information on the sensing cost of the mobile sensing problem (i.e. sensing of target areas) in vehicular sensor networks. We focus on vehicular sensor networks in which the communication channel is the bottleneck of the system, and sensing the environment is meant to be provided with a minimum load on the communication channel. First, we formulate an opportunistic scheduler, which does not utilize predicted mobility information in the sensing procedure. Then, we formulate a strategic scheduler, which utilizes predicted mobility information in the sensing procedure. After that, we propose two types of noise models that capture the uncertainty in knowing mobility information. We quantify the impact of uncertainty in knowing mobility information on the sensing cost of the strategic scheduler using an independent coverage model. We find that the strategic scheduler outperforms the noise-free opportunistic scheduler even when the strategic scheduler utilizes noisy mobility information up to a certain threshold of noise. This threshold is determined in the paper, and is referred to as the breaking point of the strategic scheduler. Simulation results of the breaking point closely matches our analysis, which demonstrates the correctness of the used analysis methodology. Finally, we use an estimation model for the mobility information between two points on the road, and we propose an algorithm to keep the scheduling scheme below the breaking point. [ABSTRACT FROM AUTHOR]

This paper presents an approach for systematically modeling a class of microgrid (MG) systems. The derived model accommodates grid-connected and islanded operation of the MG simultaneously, and allows modeling of converter-based as well as directly interfaced resources. Full modeling of virtual synchronous machines and actual synchronous generators is addressed. The originally nonlinear model is then converted to a linear model whose eigenvalues determine local stability of the MG. The model is used to analyze impacts of cross-coupling droop terms on the MG stability. The conclusions of this analysis are as follows. Addition of cross-coupling droop terms reduces the losses, compromises the stability in the grid-connected mode, and improves the stability in standalone mode. Therefore, for an MG that is intended to continuously operate at grid-connected and standalone mode, only a modest amount of cross-coupling terms is recommended to increase the efficiency without compromising the grid-connected stability. Simulation and experimental results are presented to verify the derivations. [ABSTRACT FROM AUTHOR]

Confocal gyrotron traveling-wave tube (gyro-TWT) is capable of operating in higher order modes, so it is attractive in high-frequency (> 100 GHz) band. However, the reported experimental and simulation results of confocal gyro-TWT usually operated at fundamental harmonic, so high external magnetic field was essential. In this paper, a second harmonic 220-GHz confocal gyro-TWT was designed through linear and nonlinear theory and particle-in-cell (PIC) simulation. The key problem of suppressing the backward-wave oscillations (BWOs) of both fundamental and second harmonics was solved by limiting the cavity length of the first section less than the critical BWOs length. In PIC simulations, the gyro-TWT operates at HE07 mode with an output power of 4.55 kW, the efficiency of 2.2% gain of 21.8 and the −3 dB bandwidth of 6 GHz. The calculated results from the nonlinear theory are in good agreement with the results from PIC simulation. [ABSTRACT FROM AUTHOR]

In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a radial basis function (RBF) neural network with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop system, a geometric analysis based ILC method is adopted in the outer loop. Finally, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach. [ABSTRACT FROM AUTHOR]

There has been much increased interest in the academic and industrial research communities on vehicular ad-hoc networks (VANETs). In this paper, we present an analytical model to study the end-to-end delay in a one-way VANET. This paper proposes an analytical formula for the end-to-end delay probability distribution. Using the derived probability distribution, the probability that the end-to-end delay is lower than a given threshold may be calculated. In addition, one can straightforwardly study the impact of parameters such as wireless communication range, vehicular densities, distance between source the destination, and minimum and maximum vehicle speeds on the end-to-end delay. This can help to better understand data dissemination in VANETs. Moreover, closed forms for lower and upper bounds on the end-to-end delay probability distribution are obtained. Extensive simulation results demonstrate the accuracy of our analysis. [ABSTRACT FROM AUTHOR]

Over the past five years, topic models have been applied to bibliometrics research as an efficient tool for discovering latent and potentially useful content. The combination of topic modeling algorithms and bibliometrics has generated new challenges of interpreting and understanding the outcome of topic modeling. Motivated by these new challenges, this paper proposes a systematic methodology for topic analysis in scientific literature corpora to face the concerns of conducting post topic modeling analysis. By linking the corpus metadata with the discovered topics, we feature them with a number of topic-based analytic indices to explore their significance, developing trend, and received attention. A topic relation identification approach is then presented to quantitatively model the relations among the topics. To demonstrate the feasibility and effectiveness of our methodology, we present two case studies, using big data and dye-sensitized solar cell publications derived from searches in World of Science. Possible application of the methodology in telling good stories of a target corpus is also explored to facilitate further research management and opportunity discovery. [ABSTRACT FROM AUTHOR]

Acoustic noise modeling, analysis, and reduction are critical in the design of switched reluctance machines for noise-sensitive applications. Although the analytical method can provide a fast simulation of the acoustic noise, it is generally less accurate compared to the numerical method. In order to improve the simulation accuracy, a novel analytical method is presented in this paper. The proposed method considers the excitation of the high-axial-order vibration modes to simulate the vibration behavior and the acoustic noise in the three-dimensional (3D) domain. Methods of obtaining the input data for the 3D analytical simulations are presented. The acoustic noise results obtained from the numerical simulations and experiments from an 8/6 switched reluctance motor drive are used to validate the analytical method presented in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic thermal model which predicts the winding temperature of electrical machines at steady-state and transient conditions where windings are used in integrated battery chargers (IBCs) for DC charging in a stationary position. Using winding in high current charging process causes rising winding temperature which affects insulation life. Switched reluctance machines are a proper choice for using in electric vehicles (EVs) because of their advantages such as simple and sturdy structures. IBCs can reduce volume and weight of EVs and total cost is diminished because of integration. The analytical thermal model proposed in this paper can calculates the winding temperature in balanced and unbalanced currents injection because of the phase inductance in each rotor angle is distinct, so current excitation in each phase should be different for obtaining zero total torque and keeping rotor in a stationary position, also a reduced-order model is proposed with minor impact on the accuracy of the model. Special attention has been paid to monitor the winding temperature with considering the motor lifetime in DC charging mode, this view has not been addressed in IBCs before. The proposed model is then validated against experimental results and 3D finite element method. [ABSTRACT FROM AUTHOR]

This paper presents some results on the accuracy of normal form analysis for large deviations from the stable equilibrium point (SEP) in a power system. The results of studies on the region of convergence of Neumann series, which is required for normal form analysis, are presented. A polynomial function approximation is proposed to model the generator exciter limiter. Studies on the accuracy of higher order normal form analysis for large deviations from SEP are presented. Use of Prony analysis in addition to simulation is proposed for the verification of accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes a systematic and general approach to model correlated stochastic processes in power systems by means of stochastic differential-algebraic equations. The paper discusses the theoretical background of stochastic differential-algebraic equations and provides a variety of examples of correlated stochastic models for power system applications. With this aim, stochastic processes with Normal and Weibull distributions are considered. The case study utilizes the well-known two-area system to demonstrate that the presence of correlation between the stochastic processes can cause instability, despite the fact that the same system is stable if the same processes are uncorrelated. The case study also considers a 1479-bus dynamic model of the all-island Irish transmission system to show the scalability of the proposed technique, and to compare scenarios with different levels of correlation among stochastic processes. Results indicate that correlation has a non-negligible impact on short-term dynamics. A high level of correlation among the processes, in fact, can give raise to instability. [ABSTRACT FROM AUTHOR]

In this paper, we propose a training framework for an inverter-based memristive neuromorphic hardware. The framework, which is called PHAX, is a physical characteristics aware one relying on an ex-situ training approach. The considered neuromorphic circuit is highly energy efficient hybrid CMOS-memristive implementation of neuromorphic circuits. To solve the problem of high sensitivity of the training to the mismatches between the high-level mathematical modeling of the neurons and the corresponding physical characteristics, an approach for analytical yet accurate modeling of the memristive crossbar and neuron circuits is suggested. The approach, which is based on SPICE simulations, models the inverter-based neurons using a hyperbolic tangent function. To increase the training efficacy, the backpropagation training algorithm is modified by considering some constraints based on the physical characteristics of the memristive circuit. This modification along with the accurate back-annotation of the physical characteristics considerably improve the effectiveness of the ex-situ training method of the neuromorphic circuit. The results of this paper show an average reduction of $1805{\times }$ in the training runtime compared to that of the in-situ training approach. Furthermore, the results of applying the approach on the kernels of some applications such as image recognition, image processing, and financial analysis reveal that the designed neuromorphic circuits provide an average power saving (speed up) of $1478{\times }$ ( $5.2{\times }$ ) over the ASIC implementation in a 90-nm CMOS technology. [ABSTRACT FROM AUTHOR]

The process of the sabot discard of an electromagnetic integrated launched projectile (EMILP) has a great effect on the operational effectiveness of integrated launched projectile (ILP). Aiming at the characteristics of high-velocity discard, strong muzzle magnetic field of the EMILP, a coupled model of magnetic field and flow field for simulating the EMILP sabot discard has been established by using the harmonic analysis method, time–frequency analysis method and fitting interpolation method to gain the time-varying functions of electromagnetic force and torque, which serve as the external force and moment of six degrees of freedom (SDOF) movement, and meanwhile, by using the dynamic mesh technique to couple the fluid flow control equations and the SDOF movement equations. Taking for example, the EMILP named IAT-HVP designed by the Institute of Advanced Technology (IAT), University of Texas, Austin, TX, USA, this paper makes a simulation analysis of the sabot discard of ILP at a different angle of attack, and makes a comparison between it and test data. Simulation results show that the model proposed in this paper is high precision and effective. [ABSTRACT FROM AUTHOR]

Application of the nonthermal plasma (NTP) technology for NOX removal from diesel engine exhaust has already been experimentally proved to be an efficient method at laboratory level. The NOX removal efficiency depends on various electrical and physical parameters, and very few studies have been carried out to predict it with the variation in those parameters. In this paper, an approach has been made using dimensional analysis to predict the NOX concentration with the NTP treatment, based on its dependence on various operating parameters. A relation has been obtained between NOX concentration and 11 numbers of parameters affecting NOX removal so as to form dimensionless groups. A mathematical model has been established using the experimental data and nonlinear regression technique. Experiments are conducted to validate this model with variations in the parameters voltage, flow rate, temperature, discharge gap width, and initial NOX concentration. The predicted NOX concentration values have been found to be well matched with the experimental results. The rms errors for the test data are found to be 4.64%, and in ppm, it is 9.58. [ABSTRACT FROM AUTHOR]

In this paper, we present a surface potential-based explicit continuous model for a metal-ferroelectric-insulator-semiconductor (MFIS) type gate-all-around negative capacitance transistor (GAA-NCFET). Unlike previously reported models, an explicit formulation to calculate the electrical characteristics of GAA-NCFET is proposed. Our model includes the radial dependence of the electric field in the ferroelectric, ignored in the previous works and accurately captures ferroelectric material parameter variations in the nonhysteretic regime. In contrast to bulk NCFETs, GAA-NCFET characteristics show different bias dependence due to the absence of bulk charge. We also present analytical expressions for the terminal charges which are essential to obtain the trans-capacitances for transient simulations. We find that, compared with conventional MOSFETs, the gate charge saturates to a different fraction of its maximum value. Furthermore, the modeling of quantum mechanical effect and overlap capacitances in an MFIS NCFET structure is discussed. Finally, the proposed model has been implemented in Verilog-A and tested for the transient response of ring oscillator in a commercial circuit simulator. [ABSTRACT FROM AUTHOR]

This paper presents a shutdown dose rate (SDR) calculation to estimate a newly developed preliminary concept of the equatorial port model for the Korean fusion demonstration reactor (K-DEMO). The equatorial port model was designed to provide effective radiation shielding abilities adopting the port shielding block and labyrinth structure, which was integrated into the modified K-DEMO neutronic analysis model by the Monte Carlo automatic modeling system. A rigorous two-step method was applied to couple transport (MCNP) and activation (FISPACT) codes according to three steps of calculation procedures. The results of neutron flux and decay gamma transport calculation for the equatorial port area have been indicated in this paper. The SDR calculation result near the equatorial port area reveals that a dose level in the equatorial port interspace was below $100~\mu $ Sv/h after 12 days of the shutdown. Shielding blocks and two labyrinth structures prove that they effectively attenuate neutrons on the current concept of the equatorial port model. [ABSTRACT FROM AUTHOR]

The reflectometry diagnostic for demonstration fusion reactor (DEMO) is envisaged to provide the electron density profile and to be used as a control diagnostic for the real-time vertical position controller. An initial conceptual study has been performed defining the position of the antennas and the routing of the waveguides. In the present design, the integration has been driven by the remote handling and blanket interfaces. To progress with the system integration, neutronics simulations were performed to assess the cooling requirements. This paper presents a nuclear and thermal analysis for the initial design of the reflectometry diagnostic for DEMO. The neutronics simulations were performed using the Monte Carlo simulation program MCNP6 and FENDL 2.1 cross sections, while ANSYS mechanical v18 was used to perform the thermal analysis. Simulation results show that the nuclear heat loads reach 8 W/cm3 at the surface of the diagnostics section. Without an active cooling system, the operating temperatures of the components under such heat loads would be well above the acceptable from the thermomechanical point of view. The thermal analysis here presented provides the temperature distribution in the components when subjected to neutron/gamma irradiation and thermal radiation from the plasma, after the implementation of a preliminary design of the active cooling system. The operation temperatures of the plasma-facing antennas, as well as the performance of the diagnostics system from the neutron shielding point of view, are analyzed and discussed in this paper. [ABSTRACT FROM AUTHOR]

Rate control typically involves two steps: bit allocation and bitrate control. The bit allocation step can be implemented in various fashions depending on how many levels of allocation are desired and whether or not an optimal rate–distortion (R-D) performance is pursued. The bitrate control step has a simple aim in achieving the target bitrate as precisely as possible. In our recent research, we have developed a \lambda -domain rate control algorithm that is capable of controlling the bitrate precisely for High Efficiency Video Coding (HEVC). The initial research showed that the bitrate control in the \lambda -domain can be more precise than the conventional schemes. However, the simple bit allocation scheme adopted in this initial research is unable to achieve an optimal R-D performance reflecting the inherent R-D characteristics governed by the video content. In order to achieve an optimal R-D performance, the bit allocation algorithms need to be developed taking into account the video content of a given sequence. The key issue in deriving the video-content-guided optimal bit allocation algorithm is to build a suitable R-D model to characterize the R-D behavior of the video content. In this paper, to complement the R- \lambda model developed in our initial work, a D- \lambda model is properly constructed to complete a comprehensive framework of \lambda -domain R-D analysis. Based on this comprehensive \lambda -domain R-D analysis framework, a suite of optimal bit allocation algorithms are developed. In particular, we design both picture-level and basic-unit-level bit allocation algorithms based on the fundamental R-D optimization theory to take full advantage of the content-guided principles. The proposed algorithms are implemented in HEVC reference software, and the experimental results demonstrate that they can achieve an obvious R-D performance improvement with a smaller bitrate control error. The proposed bit allocation algorithms have already been adopted by the Joint Collaborative Team on Video Coding and integrated into the HEVC reference software. [ABSTRACT FROM PUBLISHER]

In this paper, the procedure for designing a sliding-mode controller for maximum power point tracking photovoltaic (PV) applications is proposed. It is applied to a single-ended primary inductor converter, thus to a fourth-order topology, but it can be extended to a wide class of converters suitable for PV applications. The reachability and existence conditions give rise to a number of design inequalities that add to the classical steady-state conditions in order to have the desired closed-loop converter's performances. The superiority of the control technique over the classical tracking methods is analytically demonstrated through the procedure proposed in this paper. The analytical results have been validated by means of both simulations and experiments. [ABSTRACT FROM PUBLISHER]

On the wheel-rail supported hybrid railway system, the linear synchronous motor (LSM) for very high-speed transit must be a system that can maintain a large air gap, and the maximum vertical displacement must be taken into consideration in designing the LSM. As such, this paper designs two small-scale LSM models that produce equal output power—one with the normal-conducting magnet and the other with the superconducting magnet. In addition, this paper conducts a comparative analysis of the various characteristics by applying the electromagnetic numerical analysis method. Furthermore, this paper manufactures two small-scale LSM prototypes which have the normal-conducting magnet and the superconducting magnet, while also conducting a no-load and load test. Through such comparisons, this paper attempts to verify the characteristic values of the two models. [ABSTRACT FROM AUTHOR]

Although much work has been done and significant progress has been made on partial discharges (PD) measurement and detection techniques, this is not the case for PD modeling. Four types of internal PD modeling, in sequential order from first to last developed, are three-capacitance (abc), induced charge concept (ICC), finite element analysis (FEA), and Multiphysics models. The abc model is too simple to provide an understanding of the physical phenomena affecting PD. In contrast, Multiphysics models are immature. Multiphysics models require a high number of physical parameters that need to be experimentally determined, which is not a trivial task. Moreover, adjusting the physical parameters to achieve a good agreement between simulation results and measurement results for a specific geometry and dimension may not work for other geometries and dimensions. The FEA model, a relatively recent model, and the ICC model, which fall between the abc and Multiphysics models in terms of modeling complexity, can partly explain mechanisms and physical phenomena associated with internal PD. However, to the best of our knowledge, there is only one paper comparing ICC and FEA models for a case study; thus, further research is needed to elucidate various aspects of these two models. In this paper, 1) an improved ICC and a FEA capable of describing phenomena occurring during PD are developed, 2) both developed models are coded and implemented either in MATLAB or in COMSOL Multiphysics linked with MATLAB, and their simulation results are compared and analyzed, and 3) the influence of different parameters including void shape, void size, and void air pressure on PD parameters are studied. [ABSTRACT FROM AUTHOR]

The hybrid modular multilevel converter (HMMC), consisting of half-bridge and full-bridge submodules (SMs), has become a competitive topology due to the DC fault ride-through capability (FRTC). Redundancy schemes need to be employed to improve the reliability, including fixed-level and voltage-sharing active schemes, as well as passive scheme. However, different schemes affect reliability differently, which entails specific models. The contributions of this paper involve that analytical reliability models of HMMCs are proposed with considerations of voltage stress in active scheme, as well as imperfect bypass switch in passive scheme, and the comparison of different schemes is conducted to help the redundancy design. The reliability of HMMCs is divided into basic and extra components by the requirement of FRTC, which are modeled through the Markov chain and iteration method. A case study is conducted to validate the feasibility and accuracy of the proposed models, and the reliability analysis is presented, together with comparisons of different redundancy schemes. The results illustrate that reliability improvements of both fixed-level mode and passive scheme are prone to suffer saturation effect with the increase of redundant half-bridge SMs, which may even cause reliability decline in voltage-sharing mode. [ABSTRACT FROM AUTHOR]