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A comprehensive time series power flow (TSPF) framework is proposed for the analysis of fault-induced delayed voltage recovery (FIDVR). TSPF bridges the gap between static power flow simulations and time-domain simulations for FIDVR analysis. FIDVR events can be simulated faster with TSPF, while transient simulations normally require much longer time. In the TSPF framework, a random model for the disconnection of the induction motors is proposed to determine the load for different “snapshots” during FIDVR events. Regression analysis is used to predict the parameters needed in the simulations. There is no need to simplify the network topology or aggregate loads into clusters as in measurement-based load modeling approaches. The techniques presented in this paper successfully reproduced two FIDVR events recorded in heavily meshed distribution networks in New York City in 2010 and 2015. The paper uncovers that the proper modeling of motor protections (thermal and under-voltage) is key to properly predict FIDVR events. [ABSTRACT FROM AUTHOR]

The paper proposes a new adaptive approach to power system model reduction for fast and accurate time-domain simulation. This new approach is a compromise between linear model reduction for faster simulation and nonlinear model reduction for better accuracy. During the simulation period, the approach adaptively switches among detailed and linearly or nonlinearly reduced models based on variations of the system state: it employs unreduced models for the fault-on period, uses weighted column norms of the admittance matrix to decide which functions to be linearized in power system differential-algebraic equations for large changes of the state, and adopts a linearly reduced model for small changes of the state. Two versions of the adaptive model reduction approach are introduced. The first version uses traditional power system partitioning where the model reduction is applied to a defined large external area in a power system and the other area defined as the study area keeps full detailed models. The second version applies the adaptive model reduction to the whole system. The paper also conducts comprehensive case studies comparing simulation results using the proposed adaptively reduced models with the linearly reduced model and coherency-based reduced model on the Northeast Power Coordinating Council 140-bus 48-machine system. [ABSTRACT FROM AUTHOR]

This paper analyzes different models for evaluating investments in energy storage systems (ESS) in power systems with high penetration of renewable energy sources. First of all, two methodologies proposed in the literature are extended to consider ESS investment: a unit commitment model that uses the “system states” (SS) method of representing time; and another one that uses a “representative periods” (RP) method. Besides, this paper proposes two new models that improve the previous ones without a significant increase of computation time. The enhanced models are the “system states reduced frequency matrix” model which addresses short-term energy storage more approximately than the SS method to reduce the number of constraints in the problem, and the “representative periods with transition matrix and cluster indices” (RP-TM&CI) model which guarantees some continuity between representative periods, e.g., days, and introduces long-term storage into a model originally designed only for the short term. All these models are compared using an hourly unit commitment model as benchmark. While both system state models provide an excellent representation of long-term storage, their representation of short-term storage is frequently unrealistic. The RP-TM&CI model, on the other hand, succeeds in approximating both short- and long-term storage, which leads to almost 10 times lower error in storage investment results in comparison to the other models analyzed. [ABSTRACT FROM AUTHOR]

Isentropic compression experiments (ICEs) are an important method to study the dynamic characteristics of materials at pressures, temperatures, and stress or strain rate not attainable in conventional shock experiments. Yet it makes high demands toward the precise current pulse tailoring capability of the source. The China Academy of Engineering Physics is now developing a 20-brick parallel discharge driver and a 256-brick parallel discharge driver (CQ-7) to improve the performance and flexibility of compact magnetic compression devices. The load current of ICEs is tailored by optimizing the switch trigger sequence and the brick charging voltage. This paper establishes the equivalent circuit model of the 20-brick parallel discharge driver, taking the distributed inductance, resistance, and capacitance of transmission plates into account based on the partial-element equivalent circuit method. Besides, the equivalent circuit model of discharge brick based on the switch arc resistance model is also established to study the influence of key structural parameters on the output current. Furthermore, by comparing the simulation and experimental results of simultaneous discharge of 20-brick driver, the accuracy of simulation model is confirmed. This paper is of great significance to the design and optimization of multibrick parallel discharge drivers. [ABSTRACT FROM AUTHOR]

This paper investigates the numerical accuracy of currently employed methods for electromagnetic transient simulation with power electronics. Existing tools often employ the second-order accurate trapezoidal method for numerical integration. However, solution techniques employed to facilitate ideal power-electronic switches do not always preserve this second-order accuracy at switch events. As a result, the step size required to achieve the desired level of accuracy is often smaller than expected, affecting simulation speed. Therefore, this paper aims to assess and improve the tradeoff between step size and accuracy. First, currently employed solution techniques are reviewed by deriving asymptotic estimates of the rates at which approximation errors decrease as the step size reduces. Afterward, a benchmark method is proposed that preserves second-order accuracy at switch events. The tools EMTP-RV and PSCAD are compared with this benchmark method for elementary circuit examples. The results demonstrate the potential to improve accuracy, by several orders of magnitude in some cases, without increasing the number of linear systems to be solved. [ABSTRACT FROM AUTHOR]

Magnetically coupled resonant (MCR) wireless power transfer (WPT) is one of the most promising WPT technologies for its remarkable capability of simultaneous noncontact power transfer for multiple independent loads. Nevertheless, diverse energy requirements of different loads and efficiency quota make it difficult to design and optimize the multiload system. In this paper, a novel driver configuration for the MCR WPT system with multiple loads is proposed, in which the transmitting resonant tank is driven synchronously by multiple inverters operating at multiple switching frequency and sharing a common dc voltage source, then a multifrequency superposition methodology is presented to achieve high efficiency and targeted power distribution. The dominant features of the methodology are listed as follows: 1) the multifrequency power components from multiple inverters can be simultaneously delivered to multiple loads through a single transmitter; 2) the receiving coils are elaborately designed at different resonant frequencies that correspond to the operating frequencies of multiple inverters to achieve targeted power transfer and high efficiency; 3) the resonant frequency of the transmitter can be modulated within the adjacent area of multiple operating frequencies, and the power distribution to meet the requirements of selective loads will be realized; and 4) the resonant frequencies of receivers can also be adjusted to effectively realize the power distribution. In this paper, a double-frequency MCR WPT system with two loads is comprehensively investigated as a representative example, and the studied methodology has been experimentally verified by two prototypes of the proposed circuit configurations. [ABSTRACT FROM AUTHOR]

In contactless energy transfer and vibration system (CETVS) for rotary ultrasonic machining, the energy is delivered to an ultrasonic transducer equipped with a rotary spindle shank through a loosely coupled transformer (LCT). The purpose of this paper is to present a simplified construct, referred to as self-compensation system, to overcome the drawbacks of external compensation elements occupying the limited shank space during the LCT's leakage inductance compensating and the transducer's capacitance compensating. The advantage of this approach is that the secondary leakage inductive reactance of the LCT and the capacitive reactance of the transducer are mutually compensated without an intermediate element, which conserves the spindle shank space and reduces the operating load of an LCT. In this paper, we first derive the mutual compensation equation between a transducer and an LCT. Then, for a given transducer, the structural parameters of an LCT are designed with theoretical calculations and simulation analysis. Experiments are conducted with the self-compensation system excited by a 50 V ultrasonic signal. The results show that the energy transfer efficiency of LCT reached 92.0%, the amplitude of the transducer reached $10.7\,\mu {\rm{m}}$ , when the CETVS is self-compensated. These results indicate that this self-compensation theory and design are feasible. [ABSTRACT FROM AUTHOR]

This paper considers the scheduling of stochastic customer orders to minimize expected cycle time. Customer orders dynamically arrive at a machine station, and each order consists of multiple product types. Random workloads are required by each product type, and the workloads are assigned to a set of unrelated parallel machines in the station to be processed. The objective is to obtain the minimal long-run expected order cycle time through proper workload assignments. In view of the difficulty in evaluating the objective function, this paper models the targeted problem as a simulation optimization problem and proposes to solve it under the multifidelity model framework. To improve the efficiency in evaluating candidate solutions, a low-fidelity model is constructed to select solutions with better performances for high-fidelity simulations. The effectiveness of this low-fidelity model is demonstrated through a series of theoretical evidences. A simulation optimization algorithm, named Bound-Multi-fidelity Optimization with Ordinal Transformation and Optimal Sampling Bound-(MO2TOS), is developed by taking advantage of the properties of the low-fidelity model. Numerical experiments are conducted to evaluate the performance of the proposed algorithm against three other well-known simulation optimization algorithms in the literature. Results indicate that the Bound-MO2TOS outperforms all the other tested algorithms, and its performance is robust against changes in problem scale. Note to Practitioners—Customer order scheduling models have wide applications in industries where every single order may contain multiple product types and the entire order requires one shipment delivery. In many applications, such as pigments dyes manufacturing, auto repair, and grocery, consideration of customer orders rather than individual jobs is often preferred. Given the stochastic nature and the synchronization constraints of the problem, a multifidelity simulation algorithm named Bound-Multi-fidelity Optimization with Ordinal Transformation and Optimal Sampling Bound-(MO2TOS) is proposed. Experimental results suggest that the proposed algorithm outperforms three other popular simulation optimization algorithms under a variety of scenarios. It is admitted that further improvement can be made in refining the computation resource distribution process of Bound-MO2TOS. In the future research, such an improvement will be more thoroughly elaborated so that practitioners can utilize it to coordinate their productions better. [ABSTRACT FROM AUTHOR]

Dual-comparison one-cycle control for the bidirectional power flow in single-phase grid-connected converters is proposed in this paper. Advantages of dual-comparison one-cycle control when compared to conventional one-cycle control is that it does not give any steady-state dc offset, no light-load instability, and implements unipolar pulsewidth modulation without having to sense the grid voltage. Addition of a fictitious current term, which is generated from the gating signal of one of the active devices, using a bandpass filter, enables the bidirectional power flow. The quality factor of the bandpass filter is shown to impact the total harmonic distortion in current, fundamental displacement angle, and steady-state dc offset. The optimal value of a quality factor, obtained with aid of simulations, gives a superior performance. The current drawn or injected into the grid is seen to lag the grid voltage. The reason for a nonunity displacement power factor is analyzed and a compensation to achieve a unity displacement power factor is also proposed in this paper. Detailed simulation and experimental studies are carried out to validate the proposed control and the high performance that can be obtained. [ABSTRACT FROM AUTHOR]

The paper deals with the accurate flux map modeling of synchronous reluctance motors, using finite element analyses. Non-negligible discrepancies were initially observed by comparing two-dimensional (2-D) finite element method (FEM) simulation results with measured flux maps of real machines. Conversely, the three-dimensional (3-D) FEM-based flux mapping offers more accurate estimation of the aforementioned flux linkage characteristics and gives evidence of the 3-D end effects being also a function of the relative position between the magneto-motive force waveforms of the rotor and the stator. The paper investigates such 3-D end effects for different rotor geometries and winding structures, utilizing 2-D and 3-D FEM analysis in comparison to experimental data. The paper confirms that the 3-D effects are non-negligible both in concentrated and distributed winding machines. A simple mathematical approach is proposed for the concentrated winding machine, capable of off-line correction of the 2-D FEM flux maps. The proposed closed-form equation is validated through 3-D FEM and experiments. [ABSTRACT FROM AUTHOR]

In this paper, we address the issue of rule duplication during network updates in software-defined networking (SDN). In SDN, network update involves the controller in sending update packets to desired set of switches, where the update rules are installed. To ensure update consistency, old flow rules are stored until the total update procedure is complete. Higher consumption of ternary content addressable memories (TCAMs) during update increases the cost of network update and decreases the scalability of SDN. In this paper, we propose an approach for consistent update with redundancy reduction, named CURE, which reduces the TCAM usage during update. CURE prioritizes switches according to their usage pattern and schedules updates based on priority zones. The proposed approach guarantees that highly loaded switches are updated first. CURE also maintains packet-level consistency by implementing a multilevel queuing approach. In this framework, each switch in the current update region stores the incoming packets in individual device queues until the switch completes update. Therefore, after the initiation of an update, packets are processed according to new rules only. The results of performance evaluation depict that the average rule space utilization during update using CURE is 29.954% less than using the two-phase update proposed in the existing literature. [ABSTRACT FROM AUTHOR]

The contemporary problem of scheduling the recharge operations of electric vehicles (EVs) has gained a lot of research attention. This is particularly true given the governmental and industrial confidence in a bright future for EVs accompanied with the widespread installation of an enormous number of charging stations across the world. As such, this paper addresses the delay-optimal scheduling of charging EVs at several charging stations (CSs) each with multiple charging outlets. At first, a centralized optimization framework is formulated using an integer linear problem (ILP) that accounts for the delayed arrival of EVs to CSs and the randomness in the requested recharge time interval. Simulation results showed the efficacy of the ILP model when compared to naive as well as sophisticated scheduling heuristics. Next, motivated by the scalability issues of the ILP model, this paper then proposes a distributed game-theoretical approach where each EV communicates with its selected CS and iterates on modifying its strategy until all EVs converge to selecting an appropriate CS that minimizes their waiting times for receiving services. The distributed game-theoretical approach recorded promising results especially when compared to the well-known shortest job first scheduling algorithm. Further, unlike the other approaches, which normally are centralized and suited for offline scheduling, the game-based method is suited for online scheduling since it played at anytime a batch of EVs requests charging services. The running time of the game is remarkably small and outperforms all other heuristics and its convergence to Nash equilibrium is guaranteed after only small number of iterations. [ABSTRACT FROM AUTHOR]

The French National Metrology Institute [Laboratoire National de métrologie et d’Essais (LNE)] collaborates with the French National Radioactive Waste Management Agency (Andra) in order to develop a direct measurement method of the thermal power of typical radioactive waste (radwaste) packages (with an expanded uncertainty better than 5%). This method must be traceable to the international system of units. In the framework of the European project “metrology for decommissioning nuclear facilities,” LNE and Andra work on the development of prototypes of calorimeters in order to accurately measure the thermal power up to 500 W of real-size radwaste packages (0.175 m3). One of the selected metrological approaches is based on the principle of heat-flux calorimetry. This paper describes in detail the calorimeter prototype (at a reduced scale of 1/5) as well as the design of a radwaste package simulator that is used in this paper to perform its calibration. Preliminary results obtained from the calibration of the calorimeter and from the determination of thermal power are also presented with an investigation of the measurement uncertainties. Numerical simulation of the heat-flux calorimeter prototype is also presented. It shows a good agreement with the experimental results and encourages the construction of a real-size heat-flux calorimeter. [ABSTRACT FROM AUTHOR]

A model-based reinforcement learning (RL) method which interplays direct and indirect learning to update ${Q}$ functions is proposed. The environment is approximated by a virtual model that can predict the transition to the next state and the reward of the domain. This virtual model is used to train ${Q}$ functions to accelerate policy learning. Lookup table methods are usually used to establish such environmental models, but these methods need to collect tremendous amounts of experiences to enumerate responses of the environment. In this paper, a stochastic model learning method based on tree structures is presented. To model the transition probability, an online clustering method is applied to equip the model learning method with the abilities to evaluate the transition probability. By the virtual model, the RL method produces simulated experience in the stage of indirect learning. Since simulated transitions and backups are more usefully focused by working backward from the state-action, the pair estimated ${Q}$ value of which changes significantly, the useful one-step backups are actions that lead directly into the one state whose value has already obviously been changed. This, however, may induce a false positive; that is, a backup state may be an invalid state, such as an absorbing or terminal state, especially in cases where the changes of ${Q}$ values at the planning stage are still needed to put back for ranking even though they are based on a simulated experience and are possibly erroneous. It is obvious that when the agent is attracted to generate simulated experience around the area of these absorbing states, the learning efficiency is deteriorated. This paper proposes three detecting methods to solve this problem. Moreover, the policy learning can speed up. The effectiveness and generality of our method is further demonstrated in three numerical simulations. The simulation results demonstrate that the training rate of our method is obviously improved. [ABSTRACT FROM AUTHOR]

Superjunction MOSFETs in cascode configuration with low-voltage silicon MOSFETs are evaluated in this paper. The proposed structure combines the good switching performance provided by the cascode configuration with the benefits of the silicon technology such as its robustness, maturity, and low cost. This paper aims to explain and to demonstrate the reduction of switching losses of superjunction MOSFETs in cascode configuration with respect to their standalone counterparts (directly driven). A detailed simulation analysis of power loss contributions is carried out under hard-switching operation. Moreover, experimental evidence is provided using a boost converter (100–400 V) operating in continuous conduction mode for different switching frequencies (100–400 kHz) and output power levels (180–500 W). [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate how latency insertion method (LIM) can be used for real-time simulation of high switching frequency power electronics systems and how this approach can be implemented for scalable Field Programmable Gate Array (FPGA) execution. We first present a summary of the LIM and how this method can be developed into a solver for high-performance FPGA execution. We then present how common power electronics topologies—buck and boost—can be modeled using the LIM approach, followed by how the LIM model of a three-phase dc/ac converter is created. Afterward, we demonstrate the accuracy of the developed FPGA solver through a set of power electronic system examples, with each example compared with near ideal results of same example provided by a traditional electromagnetic transient type solver. We complete the paper analyzing the scalability of the proposed approach on FPGA devices, both in terms of achievable time step as well as of resource usage. [ABSTRACT FROM AUTHOR]

Conventional finite control set-model predictive control (FCS-MPC) applies single voltage vector within each control period. This leads to relatively high steady-state ripples and requires fast sampling rate. Additionally, enumeration-based optimal vector selection is computationally intensive. Recently, double-vector-based schemes have been proposed to improve the steady-state performance of FCS-MPC. However, they are usually complicated in vector selection and duty ratio calculation. In this paper, a universal multiple-vector-based MPC (UMV-MPC) is proposed, which achieves the same performance as the state-of-the-art double-vector-based MPC, but executes in a much more efficient and universal way. Unlike conventional FCS-MPC, enumerating process and state predictions for candidate voltage vectors are not required in the proposed UMV-MPC to select the best voltage vectors. In UMV-MPC, the optimal vectors and duty ratios are directly constructed from deadbeat control (DBC) based on space vector modulation (SVM), which is easy to follow and quick to use. The proposed UMV-MPC is not only more efficient than prior methods, but also reveals the inherent relationship between double-vector-based MPC and DBC with SVM. A comparative study of UMV-MPC and prior double-vector-based MPC is carried out in this paper. The theoretical analysis as well as simulation and experimental tests on a 2.2-kW induction motor drive are demonstrated to validate the effectiveness of the proposed UMV-MPC. [ABSTRACT FROM AUTHOR]

It has been. As an automated validation method recommended by the IEEE Standard 1597.1/2, the FSV method has gained broad attention in the practice of computational electromagnetics modeling and simulations. This paper reviews the motivation, evolution, enhancements, and criticisms of the method over this time. The aims of this paper are to give a detailed contextualization of the development of the FSV method itself and to discuss the open questions and possible strategies of the next generation of automated validation methods. [ABSTRACT FROM PUBLISHER]

The IEEE International Integrated Reliability Workshop (IIRW) focuses on ensuring electronic device reliability through fabrication, design, testing, characterization, and simulation, as well as identification of the defects and physical mechanisms responsible for reliability problems. Submit your two-page abstract by 12 July 2013 to be part of this unique event. For further information visit http://www.iirw.org or contact the TPC chair. [ABSTRACT FROM AUTHOR]

Numerous research efforts have been conducted to simulate the crowd movements, while relatively few of them are specifically focused on multihazard situations. In this paper, we propose a novel crowd simulation method by modeling the generation and contagion of panic emotion under multihazard circumstances. In order to depict the effect from hazards and other agents to crowd movement, we first classify hazards into different types (transient and persistent, concurrent and nonconcurrent, and static and dynamic) based on their inherent characteristics. Second, we introduce the concept of perilous field for each hazard and further transform the critical level of the field to its invoked-panic emotion. After that, we propose an emotional contagion model to simulate the evolving process of panic emotion caused by multiple hazards. Finally, we introduce an emotional reciprocal velocity obstacles (RVOs) model to simulate the crowd behaviors by augmenting the traditional RVO model with emotional contagion, which for the first time combines the emotional impact and local avoidance together. Our experimental results demonstrate that the overall approach is robust, can better generate realistic crowds and the panic emotion dynamics in a crowd. Furthermore, it is recommended that our method can be applied to various complex multihazard environments. [ABSTRACT FROM AUTHOR]

In surgical simulation, the Navier–Stokes (N–S) equation is commonly employed to imitate the physical characteristics of bleeding and the smooth particle hydrodynamics (SPHs) algorithm is applied to solve the numerical solution of the N–S equation. However, blood is viscous, incompressible and non-Newtonian fluid whose physical properties cannot be fully incorporated by the simple N–S equation, and the kernel approximation of the SPH algorithm may lead to both edge and volume distortions plus high computational cost. In this paper, both the tension force and the effect of platelets on the viscous force of bleeding particles are incorporated into the N–S equation in order to render more realistic visual effect and biological features of bleeding in surgical simulation. Constant core radius of the kernel function of the SPH algorithm is substituted with a function of particle density, avoiding potential edge distortions in simulating bleeding area. A repulsive force between particles is introduced, which effectively prevents volume distortions. Besides, accelerated search for particles based on the cube mesh improves the computational efficiency. The simulation results show that the presented simulation method leads to smooth bleeding surface and improves the visual effects of edge and volume in comparison with existing methods, and relatively high computational efficiency can be achieved as well. [ABSTRACT FROM AUTHOR]

We present a new set of simulation models, organized in a testbed. The aim of the testbed consists in providing researchers with a platform able to credibly represent the complexity of modern semiconductor manufacturing. The testbed is open to public use, and include so far four models. A high-volume/low-mix model and a low-volume/high-mix model constitutes the foundation of the testbed. Two additional models incorporate the complexity of engineering lots. We conclude this paper by presenting a case study that demonstrates that the third and fourth model can be used to assess the performance of integrated dispatching strategies for production and engineering lots. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of selecting a Pareto set from among finite alternatives, where each alternative has multiple performance measures evaluated by stochastic simulations. Under limited simulation resources, we propose an efficient algorithm for solving this problem based on a statistical hypothesis test. Using the test, the proposed algorithm evaluates the uncertainty of each design based on the observed simulation results to identify whether the selected Pareto set is accurate. Based on the evaluated uncertainty, the algorithm assigns additional resources to the designs to maximize the accuracy of the selected Pareto set. Applying the sequential procedure, the algorithm increases the precision of the observed information selectively and gradually. Several experiments, including a practical case study, demonstrated its improved efficiency compared to the existing algorithms in the literature. This improved efficiency, along with low complexity and high robustness to noise, allows the proposed algorithm to be effectively applied to practical system designs. [ABSTRACT FROM AUTHOR]

Multilevel converters with floating capacitors (FCs) are widely applied in recent years in a wide range of industrial applications from high-voltage direct current systems to high power drives. However, some FC topologies lack complete FC voltage balancing capability due to the inherent topology limitation or the insufficient switching state for capacitor balancing. This will result in large ripples on capacitors at low frequency (such as fundamental frequency), limiting their performance and application, particularly, when the fundamental frequency is very low in low-speed drive operations. Typical examples of those multilevel converters are modular multilevel converters (MMC), nested neutral-point-clamped (NNPC) converter, etc. In order to improve the FC balancing for this kind of multilevel converters, this paper proposes a carrier-based pulse-width modulation (PWM) method, named stair edge PWM method. This method can obtain sufficient redundant switching states for FC voltage balancing by producing multiple levels in one PWM period. The FC voltage balancing is thus achieved at switching frequency, which can greatly reduce the capacitor voltage ripple and therefore enable the use of much smaller FCs. Meanwhile, the voltage stress on each device and low $dv/dt$ feature are still the same as the normal multilevel operation, reserving two of the most salient features of multilevel converters. The proposed method also features much simpler and easier implementation compared with space-vector-based approaches, particularly when high-level converters are considered. An application example using a four-level NNPC converter is provided in this paper. The effectiveness and performance of the proposed method are verified by both simulation and experiment. [ABSTRACT FROM AUTHOR]

In this paper, the characteristics of ripple current of a multimegawatt drive system fed by a pulse-width modulation (PWM) inverter are investigated. Based on the investigation, a novel PWM scheme is devised to reduce the switching loss of the inverter under an identical amount of torque ripple of a motor. The proposed PWM is composed of two parts. The first is minimum torque ripple PWM (MTRPWM), which is optimized in terms of the minimum torque ripple in high modulation index (MI). The second determines the minimum switching frequency while holding the average torque ripple less than the allowable value under various operating conditions. It is termed reduced switching frequency PWM (RSFPWM). Consequently, by simply changing the PWM method from conventional fixed switching frequency continuous PWM to the proposed PWM, MTRPWM and RSFPWM, simulation results show that the switching loss of the inverter driving a 3.5 MW induction motor is reduced to 51.6% while keeping the torque ripple in the allowable boundary, where MI is 1.12. This approach is applied to small-scale experimental sets consisting of an interior permanent magnet synchronous machine (IPMSM) motor-generator set, and an induction machine MG set in an effort to verify the validity and feasibility of the proposed method. Based on these experimental results, the cost indexes of the IPMSM and the induction machine, as defined in this paper, decrease by up to 66% and 77%, respectively, when the proposed method is applied when MI is 1.12 compared with the outcome with the conventional PWM. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of local content dissemination among mobile users via decentralized device-to-device (D2D) communication, where the concerned contents have relevance only within a geographic span centered at their respective location of creation. This has several potential applications, for example, advertising and sharing contents specific to an event. To this end, we propose a scheme for locality-bounded content and information dissemination (LUCID) leveraging opportunistic D2D communications. Unlike other existing works, LUCID innovates by not requiring users to share locations of the centers of localities and, thereby, provides a natural defense against possible location privacy attacks. In this paper, we theoretically characterize the behavior of LUCID for different locality sizes. Moreover, we investigate the extent to which an individual user can attempt to infer the location of a center of a locality, and discuss why that is difficult to achieve. Finally, we also consider an alternative version of LUCID where locations are partially shared. Results of simulation-based performance evaluation indicate that, when compared to an optimal scheme, LUCID can deliver contents to about two-third of the relevant users without requiring any location sharing. [ABSTRACT FROM AUTHOR]

This paper presents the design of an optimal integral sliding mode controller (OISMC) to control the total power of a large pressurized heavy water reactor (PHWR). Considering the dynamics of systems relevant to total power control loop of the large PHWR, the single input and single output model adopted in this paper is characterized by 21 state variables. The nonlinear model is linearized around steady-state full power operating point to obtain a linear model for which an OISMC is designed. Optimal controller which guarantees minimum control effort is combined with an ISMC to ensure the robustness of the system in the presence of uncertainties and external disturbances. Stability of the proposed controller is proven by means of Lyapunov approach. From nonlinear simulation studies, performance of the proposed OISMC is found to be satisfactory. [ABSTRACT FROM AUTHOR]

In the strict sense, the electrodes of the electromagnetic flow sensor (EFS) are nonideal, and the selection of models with different dimensions can result in a relatively large difference in the calculation of the weight function, which further affects the estimation of the output signal. The aim of this paper is to explore the difference in the characteristics of the 2-D and 3-D EFSs with nonideal electrodes. In this paper, the analytical expressions of weight function for both 2-D and 3-D cases are deduced mathematically, and a general weight function methodology based on simulation data and fitting is presented to solve the mixed boundary problem. The effectiveness of the proposed method is verified by the comparison with the numerical simulation. Meanwhile, the distributions of weight function for 3-D EFSs with different electrodes in cross sections are obtained by means of the method mentioned above, and the difference between the 2-D model and the 3-D model is revealed intuitively. Finally, the output characteristics of the EFS with different dimensions and electrode shapes are calculated by coupling the data of three fields, including the weight field, the flow field, and the magnetic field. Based on the comparison between the experimental data and the calculated values, the direct influence of the dimension and the electrode shape on the output characteristics of the EFS is discussed, and the theoretical analysis is made for the structure design and optimization of the EFS. [ABSTRACT FROM AUTHOR]

This paper presents a novel control method for multimodule photovoltaic microinverter (MI). The proposed MI employs a two-stage topology with active-clamped current-fed push–pull converter cascaded with a full-bridge inverter. This system can operate in grid-connected mode to feed power to the grid with a programmable power factor. This system can also operate in line-interactive mode, i.e., share load power without feeding power to the grid. In the event of grid power failure, the MI can operate in a standalone mode to supply uninterruptible power to the load. This paper presents a multiloop control scheme with power programmable capability for achieving the above multiple functions. In addition, the proposed control scheme embedded a multimodule parallel capability that multiple MI modules can be paralleled to enlarge the capacity with autonomous control in all operation modes. Finally, three 250-W MI modules are adopted to demonstrate the effectiveness of the proposed control method in simulations as well as experiments. [ABSTRACT FROM PUBLISHER]

Study of polar codes in fading channels is of great importance when applying polar codes in wireless communications. Channel estimation is a fundamental step for communication to be possible in fading channels. Construction of both systematic and nonsystematic polar codes is based on an information set and the known frozen bits. Efficient implementation of systematic and nonsystematic polar codes exists. When it comes to channel estimation or channel tracking, additional pilot symbols are inserted in the codeword traditionally. In this paper, to improve the performance of polar codes in the finite domain, pilot symbols are selected from the coded symbols themselves. In order to keep the existing efficient structure of polar code encoding, pilot selection is critical since not all selections can reuse the existing structure. In this paper, two pilot selections denoted as Uneven Pilot Selection (UEPS) and Even Pilot Selection (EPS) are proposed, which do not change the efficient polar encoding structure. The proposed UEPS and EPS are proven to satisfy the efficient construction condition. The performance of EPS is shown in this paper to outperform both the UEPS and the traditional pilot insertion scheme. The simulation results provided verify the performance of the proposed pilot selection schemes. [ABSTRACT FROM AUTHOR]

This paper presents a systematic and comprehensive approach for differential mode (DM) electromagnetic interference (EMI) filter design in a three-phase boost-type power factor correction (PFC) rectifier. Since the DM EMI filter forms a significant portion of the overall filter as well as converter volume, the reduction of DM filter component size is kept as a major objective in the filter design process in order to improve the power density. In addition to the objectives of volume optimization and conducted emission attenuation requirement to comply with the EMI standard, the filter design process also ensures a near-unity power factor operation with the optimal set of EMI filter parameters. To accomplish this, the paper analyzes the effect of EMI filter component selection on the overall lower order (1–100 kHz) frequency response, which is important for evaluating the dynamic response and stability. The results from the proposed design approach are validated through simulation, the DM Bode plot, and frequency response of the input current with and without EMI filter. As a proof-of-concept verification, the proposed EMI filter is implemented in a 4-kW three-phase boost-PFC prototype, which demonstrates minimal phase displacement (<5°) of the input current. [ABSTRACT FROM PUBLISHER]

This paper presents experimental and simulation analysis of an $\Omega $ -shaped silicon junctionless nanowire field-effect transistor (JL-NWT) with gate lengths of 150 nm and diameter of the Si channel of 8 nm. Our experimental measurements reveal that the ON-currents up to 1.15 mA/ $\mu \text{m}$ for 1.0 V and 2.52 mA/ $\mu \text{m}$ for the 1.8-V gate overdrive with an OFF-current set at 100 nA/ $\mu \text{m}$. Also, the experiment data reveal more than eight orders of magnitude ON-current to OFF-current ratios and an excellent subthreshold slope of 66 mV/dec recorded at room temperature. The obtained experimental current–voltage characteristics are used as a reference point to calibrate the simulations models used in this paper. Our simulation data show good agreement with the experimental results. All simulations are based on drift-diffusion formalism with activated density gradient quantum corrections. Once the simulations methodology is established, the simulations are calibrated to the experimental data. After this, we have performed statistical numerical experiments of a set of 500 different JL-NWTs. Each device has a unique random distribution of the discrete dopants within the silicon body. From those statistical simulations, we extracted important figures of merit, such as OFF-current and ON-current, subthreshold slope, and voltage threshold. The performed statistical analysis, on samples of those 500 JL-NWTs, shows that the mean ${I}_{D} - {V}_{\text {Gs}}$ characteristic is in excellent agreement with the experimental measurements. Moreover, the mean ${I}_{D} - {V}_{\text {Gs}}$ characteristic reproduces better the subthreshold slope data obtained from the experiment in comparison to the continuous model simulation. Finally, performance predictions for the JL transistor with shorter gate lengths and thinner oxide regions are carried out. Among the simulated JL transistors, the configuration with 25-nm gate length and 2-nm oxide thickness shows the most promising characteristics offering scalable designs. [ABSTRACT FROM AUTHOR]

Energy efficiency has become the main concern of IC technology. Tunnel FET (TFET) is recognized to possess the superiority of energy efficiency over MOSFET at ultralow voltage, while variability might limit the voltage reduction and thus the energy saving. Recently, device source doping gradient (SDG) is found to be the dominant variation source in TFET. In this paper, for the first time, with the awareness of SDG variation, the energy efficiency of TFET-based circuits with different activity factors ( $\alpha $ ) is comprehensively reassessed and the device optimization strategy is provided. It is found that the superiority of energy efficiency of TFET will significantly decrease especially for the more active circuit due to the inherent tradeoff between SDG variation and nominal SDG. Based on the quantitative relationship between SDG variation and nominal SDG extracted from the experimental devices, the optimal design of tunnel junction abruptness to maximize the circuit energy efficiency is obtained, leading to significant energy efficiency improvements of TFET-based circuit over MOSFET even for circuit with high $\alpha $. This paper provides helpful device design guidelines for TFET with device variability awareness from the perspective of circuit energy efficiency. [ABSTRACT FROM AUTHOR]

In a recent paper, the problem of inverse synthetic aperture radar (ISAR) imaging moving ground targets was discussed and an effective solution based on a novel joint space-time adaptive processing (STAP)-ISAR formulation was proposed. In the case of bistatic geometry, ISAR imaging can be simply and effectively enabled via the bistatically equivalent monostatic theory, which allows for monostatic ISAR processing to be used to form bistatic ISAR images. However, the clutter nonstationary introduced by the bistatic geometry strongly degraded STAP performances if a monostatic STAP processing is used. In this paper, a new joint STAP-ISAR processing is introduced that works in the bistatic case. Theoretical figures and numerical simulations are used to prove the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Current proton therapy scanning systems always use two independent dipole magnets for spot scanning in proton therapy. However, the space occupied by these two dipole magnets located after the final gantry bending magnets is very large and increases the overall size of the gantry. In order to construct a compact nozzle and decrease the size of the gantry, we decide to design an octupole scanning magnet to replace these two separate dipole magnets. The octupole scanning magnet, which is completely different from traditional octupole magnet, can generate rotating dipole magnetic field with the change of the loaded sinusoidal current phases. In this paper, we have finished the static optimization of an octupole scanning magnet model, including the length and shape of the poles, the diameter of the gap, and the shims on the pole edges, both in Opera two-dimensional (2-D) and 3-D. The corresponding relationship between the size of the gap and the good field region was also studied. The effect of eddy currents on magnetic field stability was also simulated in Opera 3-D. All the simulation results are presented in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we propose a design process for a plasmonic grating structure to induce the resonance at a target wavelength. In a specific condition, surface gratings may induce the surface plasmon propagation due to the diffraction and the resonance wavelength of the surface plasmon propagation is dependent on the grating shape. The grating configuration was designed by the topology optimization scheme based on the reaction-diffusion equation. To shift the resonance wavelength to the target wavelength, this paper maps the frequency response function to a probability distribution function (PDF). The mean value from the PDF becomes a part of the objective function and the design objective is set to minimize the distance between the present resonance wavelength and the target wavelength while keeping the energy intensity. The process of simulation and optimization was performed using the commercial package COMSOL combined with MATLAB programming. [ABSTRACT FROM AUTHOR]

In this paper, the usage of the Parareal method is proposed for the time-parallel solution of the eddy current problem. The method is adapted to the particular challenges of the problem that are related to the differential algebraic character due to non-conducting regions. It is shown how the necessary modification can be automatically incorporated by using a suitable time-stepping method. This paper closes with the first demonstration of a simulation of a realistic four-pole induction machine model using Parareal. [ABSTRACT FROM AUTHOR]

Switchgear is an important power system protection equipment. Internal overheating of high-current switchgear has become the most common problem in the power system. In this paper, two different methods of simulation model are adopted to study the temperature rise issues of the 12-kV medium voltage switchgear. First, the electromagnetic field is calculated by using ANSYS APDL, then coupling with fluid dynamics software CFX to give the temperature and flow field distribution of the switchgear. Second, FLUENT and Maxwell 3-D are used to get the temperature and flow field distribution. It can be proven that CFX simulation of flow field is more suitable for the complex models. In the meantime, it has huge differences with FLUENT software when the temperature rise of the switchgear is calculated. In this paper, the influences of inlet velocity, the number of ventilation holes, and their positions are further studied, which could provide theoretical guidance for reducing temperature rise of the switchgear. [ABSTRACT FROM PUBLISHER]

This editorial introduces the Special Issue on Simulation and Synthesis in Medical Imaging. In this editorial, we define so-far ambiguous terms of simulation and synthesis in medical imaging. We also briefly discuss the synergistic importance of mechanistic (hypothesis-driven) and phenomenological (data-driven) models of medical image generation. Finally, we introduce the twelve papers published in this issue covering both mechanistic (5) and phenomenological (7) medical image generation. This rich selection of papers covers applications in cardiology, retinopathy, histopathology, neurosciences, and oncology. It also covers all mainstream diagnostic medical imaging modalities. We conclude the editorial with a personal view on the field and highlight some existing challenges and future research opportunities. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of estimating a high-dimensional vector of parameters \theta \in \mathbb R^n from a noisy observation. The noise vector is independent identically distributed Gaussian with known variance. For a squared-error loss function, the James–Stein (JS) estimator is known to dominate the simple maximum-likelihood (ML) estimator when the dimension n exceeds two. The JS-estimator shrinks the observed vector toward the origin, and the risk reduction over the ML-estimator is greatest for {\theta } that lie close to the origin. JS-estimators can be generalized to shrink the data toward any target subspace. Such estimators also dominate the ML-estimator, but the risk reduction is significant only when {\theta } lies close to the subspace. This leads to the question: in the absence of prior information about \theta , how do we design estimators that give significant risk reduction over the ML-estimator for a wide range of \theta ? In this paper, we propose shrinkage estimators that attempt to infer the structure of \theta from the observed data in order to construct a good attracting subspace. In particular, the components of the observed vector are separated into clusters, and the elements in each cluster shrunk toward a common attractor. The number of clusters and the attractor for each cluster are determined from the observed vector. We provide concentration results for the squared-error loss and convergence results for the risk of the proposed estimators. The results show that the estimators give significant risk reduction over the ML-estimator for a wide range of \theta , particularly for large $n$ . Simulation results are provided to support the theoretical claims. [ABSTRACT FROM AUTHOR]

This paper analyzes the influence of frequency and voltage variation over the commutation of thyristors in high-power cycloconverters. The analysis demonstrates that frequency and voltage variations can cause commutation failures generating significant damages in cycloconverters. In addition, the paper proposes a method based on the energy required to commutate thyristors to determine the maximum frequency and voltage variations that will not affect commutation between thyristors, information that can be later used for the correct setting of protection relays. The analysis is complemented with simulated results using data obtained from high-power thyristors used in commercially available cycloconverters. Finally, a commutation failure in a 15 MW grinding mill cycloconverter drive is presented and analyzed. [ABSTRACT FROM PUBLISHER]

This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or preprocessed interference-aware operation. This paper presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein. [ABSTRACT FROM AUTHOR]

The developments of connected vehicles are heavily influenced by information and communications technologies, which have fueled a plethora of innovations in various areas, including networking, caching, and computing. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on vehicular networks. In this paper, we propose an integrated framework that can enable dynamic orchestration of networking, caching, and computing resources to improve the performance of next generation vehicular networks. We formulate the resource allocation strategy in this framework as a joint optimization problem, where the gains of not only networking but also caching and computing are taken into consideration in the proposed framework. The complexity of the system is very high when we jointly consider these three technologies. Therefore, we propose a novel deep reinforcement learning approach in this paper. Simulation results with different system parameters are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

The operation of static random access memory (SRAM) in the subthreshold region reduces both leakage power and access energy. Subthreshold operation is one of the proficient techniques to accomplish low-power and high performance system on chip. But the challenge, in subthreshold SRAM design, is the SRAM stability. The sensitivity to process variations increases with technology scaling resulting in reduced stability. In this paper, SRAM write stability is analyzed in the subthreshold region. The semi-analytical model of write static noise margin (WSNM) for 6T SRAM (subthreshold region) has been given in this paper. The results obtained from the analytical model are verified through simulations in Cadence using GPDK 45-nm, UMC 65-nm, and UMC 130-nm technology files. The model is based on the subthreshold current equations of the transistor. Further, the write stability of the SRAM is analyzed with the varying supply voltage and the sizing ratios. The process corner analyses is also accomplished to verify the write stability of the SRAM cell using the model at the worst process corners. To the best of the author’s knowledge, this is the first model to analyze the WSNM based on the traditional butterfly static noise margin approach. It has been observed that the model is valid for all of the technology nodes, i.e., at 45 nm, 65 nm, as well as 130 nm. Also the model holds well for 8T and 10T SRAM configurations in addition to 6T SRAM cell. [ABSTRACT FROM PUBLISHER]

This paper presents the results of mathematical simulation of processes in argon-hydrogen inductively coupled plasma/radio frequency induction plasma torch for plasma chemical reactions. This first part starts a series of papers for simulation and study of plasma properties for a variety of gases and mixtures, which could be used for a number of prospective technologies. The results of mathematical simulation allow further research on the mechanisms of chemical reactions in argon-hydrogen plasma to increase effectiveness of obtaining the target product. [ABSTRACT FROM AUTHOR]

The multipeaked correlation functions of binary offset carrier (BOC) modulated signals introduce an ambiguity threat into the code tracking. Several techniques have been proposed to solve this problem, such as a class of two-dimensional (2-D) tracking techniques, in which the spreading code and the subcarrier are tracked separately. In this paper, the key properties of correlation functions and the theoretical tracking performance analysis considering noise and multipath environments of the general 2-D tracking loop are studied. Exact explicit expressions, taking into account the effects of local subcarrier waveform mismatching and the front-end bandlimiting, are provided for the correlation function employed in 2-D tracking. From these expressions, the key characteristics of 2-D correlation functions such as the shape, coupling relation between dimensions, and the effects of bandlimiting can be clearly seen. Moreover, general theoretical methods to predict the performance of the 2-D tracking techniques under the multipath and noise environments are provided. The results obtained in this paper can facilitate investigations in the area of 2-D tracking technique parameter optimization and performance assessment. [ABSTRACT FROM PUBLISHER]

This paper presents application guidelines for a new generic plant controller model that can be used for renewable plant dynamic system analysis that may include the control of static compensators (STATCOMs), static var compensators (SVCs), and/or energy storage devices. The authors originally presented the need for such a model to the Western Electricity Coordinating Council (WECC) and contributed to various stages of the new model development led by WECC. As Independent System Operators (ISOs)/Regional Reliability Organizations (RTOs)/Transmission Service Providers (TSPs) are moving toward acceptance and use of generic models only the authors have for the first time applied this new model for an operating renewable plant. The new model was configured, parameterized, and tuned to control two STATCOMs and multiple switched capacitors/reactors to represent a master/auxiliary control strategy as implemented in the plant. Dynamic simulations show that the configured and parameterized model is performing properly as expected. This tuned model was submitted to the system operator for compliance with the interconnection requirements of the plant. This is the first submission of the new generic model for this type of control for a renewable project. The submitted model is appropriate for dynamic simulations, which are routinely performed by ISOs/RTOs/TSPs in system impact studies or transmission planning studies. This paper provides useful guidelines in applying this new model for similar projects. [ABSTRACT FROM AUTHOR]

As distributed, communication-based protection systems become more prevalent in the emerging smart grid, the task of critically assessing their reliability has become increasingly challenging due to the complexity of their underlying software designs. This paper demonstrates that the discipline of software model checking can be applied to smart grid protection software designs to rigorously assess their fault tolerance. In this paper, the SPIN model checker is applied to a published wide-area backup protection system (WABPS). The WABPS was specifically architected to be highly reliable under various kinds of common failure scenarios, including mechanical malfunctions, erroneous sensor readings, and communication failures. However, because of its built-in redundancy and decentralized peer-to-peer design, calculating its precise fault tolerance is nontrivial. This paper shows how SPIN can be applied to the WABPS's design to brute-force prove the limits of the number and types of failures that can occur while the system remains able to successfully perform its function. This same technique is applicable to a wide variety of smart grid protection software designs, and the information it provides is invaluable to protection engineers during the development of new systems, for assessing the quality of competing designs, and for risk management purposes. [ABSTRACT FROM AUTHOR]

Both caching and interference alignment (IA) are promising techniques for next-generation wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless networks assume that the channel is invariant, which is unrealistic considering the time-varying nature of practical wireless environments. In this paper, we consider realistic time-varying channels. Specifically, the channel is formulated as a finite-state Markov channel (FSMC). The complexity of the system is very high when we consider realistic FSMC models. Therefore, in this paper, we propose a novel deep reinforcement learning approach, which is an advanced reinforcement learning algorithm that uses a deep $Q$ network to approximate the $Q$ value-action function. We use Google TensorFlow to implement deep reinforcement learning in this paper to obtain the optimal IA user selection policy in cache-enabled opportunistic IA wireless networks. Simulation results are presented to show that the performance of cache-enabled opportunistic IA networks in terms of the network's sum rate and energy efficiency can be significantly improved by using the proposed approach. [ABSTRACT FROM PUBLISHER]