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This paper presents an FPGA-based Digital Real-Time Simulation (DRTS) environment for the analysis of Electromagnetic Transients (EMTs) of power systems that include multiple Power Electronic Converters (PECs). The main features of the proposed DRTS platform are that it i) employs two-value resistor switch model for PECs and thus avoids inaccuracies of Associate Discrete Circuit (ADC) model and ii) does not require separation of PECs by transmission lines (stub lines) and thus accurately represents PECs in close electrical proximity of each other. These features respectively result in a time-variant and large system admittance matrix which significantly increases the computation burden in each simulation time-step and can render it infeasible for real-time applications. To overcome this problem this paper introduces i) Switching-Network Partitioning (SNP) method which is tailored for PECs representation in FPGA and ii) Reformulated Modified Nodal Analysis (RMNA) method to enable computational parallelism between the solution of network and component models in FPGA. SNP enables solution-level partitioning of the PECs and the rest of the system. The developed DRTS platform enables sub-microsecond simulation time-step and provides a fixed hardware irrespective of the system configuration. Performance of the platform is evaluated for a study system and verified versus off-line simulation studies. [ABSTRACT FROM AUTHOR]

The haze problem in cities poses a great threat to human health. Although there are many factors that cause fog and haze, the main reason is the increase of the PM2.5 concentration. Due to the complexity of the particles motion, it is difficult to use traditional methods obtain information about PM2.5 (including its sources, influencing factors, and distribution forecast). This paper presents a cellular automata (CA) model based on a multivariate regression model and several physical models to analyze the generation and diffusion of PM2.5. In Beijing for example, after the researches, the multiple regression confirmed that the major source of PM2.5 is vehicle pollution, which accounts for 39.2% of the pollution generated in Beijing. The secondary source is from the residential areas, accounting for 27.5% in the winter. Besides, 32% of the total pollution comes from nearby areas. In addition, it is also confirmed that the weather factors, such as, temperature, wind, pressure and relative humidity, and radiation are all have a great impact on PM2.5. The CA model is demonstrated to be an effective simulation and prediction method for PM2.5 since it allows for the estimation of the governance results by simulating the control scheme and predicting the concentration of PM2.5 accurately in the next 48 h. In the prediction experiment, 77.5% of prediction error is less than $20~ {\mu }\text{g} / {\text {m}}^{3}$. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of channel simulation via interactive communication, known as the coordination capacity, in a two-terminal network. We assume that two terminals observe independent identically distributed (i.i.d.) copies of two random variables and would like to generate i.i.d. copies of two other random variables jointly distributed with the observed random variables. The terminals are provided with two-way communication links, and shared common randomness, all at limited rates. Two special cases of this problem are the interactive function computation studied by Ma and Ishwar, and the tradeoff curve between one-way communication and shared randomness studied by Cuff. The latter work had inspired Gohari and Anantharam to study the general problem of channel simulation via interactive communication stated above. However, only inner and outer bounds for the special case of no shared randomness were obtained in their work. In this paper, we settle this problem by providing an exact computable characterization of the multiround problem. To show this we employ the technique of output statistics of random binning that has been recently developed by the authors. [ABSTRACT FROM AUTHOR]

This paper proposes a startup sequence for a modular multilevel converter (MMC) HVDC-connected offshore wind farm (OWF) and demonstrates how it can be simulated using an electromagnetic transient-type tool. The objective is to analyze inrush currents of transformers and cables (HVAC and HVDC). Modeling accuracies and computational performances are examined using three existing modeling methods for the MMCs. [ABSTRACT FROM PUBLISHER]

In this paper, characteristic model-based modeling and control approaches for complex dynamical networks based on sampled data are studied. It shows that the characteristic model, in which underline network topological structures are simplified, can provide a straightforward and implicit description for network dynamics. The induced parameter estimation method can further make the model adaptive and purely data-driven. Moreover, a control law based on this model is also proposed to govern the network dynamics. Finally, the theoretical results are verified through numerical simulations of modeling and stabilizing a dynamical network. [ABSTRACT FROM AUTHOR]

This paper proposes a new dynamic behavior model for single-electron transistors (SETs). A comprehensive review of modeling techniques and previous models was carried out aiming to remark the originality of the new proposed technique. Once established that SET is a nonlinear system, five classes of nonlinear models were simulated and compared to each other. Characteristic SET curves obtained using Simulation of Nanostructures were used as benchmark. The mean squared error (mse) was used as metric, and the simulation time was computed for each model. Regarding these two criteria—least mse and least simulation time—the Hammerstein–Wiener model outperformed the others models. [ABSTRACT FROM AUTHOR]

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]

In this paper, a new continuous multilevel compact model for phase-change memory (PCM) is proposed. It is based on the modified rate equations with the introduction of a variable related to material melting. The model is evaluated using a large set of dynamic measurements and shows a good accuracy with a single model card. All fitting parameters are discussed, and their impacts are detailed. Full circuit simulation is performed. Good convergence and fast simulation time suggest that this new compact model can be exploited for PCM circuit design. [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]

In this paper, a novel approach for simulating phenomena accompanying internal arc ignition is proposed. This method is based on the cellular automata (CA) algorithm, where physical equations correspond to cell states and transition rules. In the proposed model, the cell states consist of pressure, temperature, gas velocity, and so on. Each cell has its own neighborhood defined. The present state of each cell depends on its former value, the actual values from neighboring cells, and on transition rules. At each time step, the cell states are updated. Thanks to the proposed methodology, it is possible to simulate internal arc-connected phenomena for very sophisticated shapes of electrical equipment simply by dividing the shape into discrete cells. The proposed approach can be used as an alternative for commonly used methodologies: for simplified approaches (where simplified equations are used for field calculations in averaged volumes) as well as for computational fluid dynamic method (where advanced mathematical and physical apparatus is employed). In this paper, the results show the comparison between the proposed methodology and both of these solutions. The proposed approach can be applied in, e.g., gas-insulated switchgear and transformer applications. [ABSTRACT FROM PUBLISHER]

The proper modeling of the transient thermal behavior of mutual heating effects between underground power cables is very important for the rating of transmission and distribution cables. The IEC standards proposed an accurate model based on exponential integrals that it can be difficult to implement in basic electrical software. The model is not consistent with the layered modeling of the cable thermal resistances. In this paper, a simple and easy-to-use alternative model is presented. It consists of injecting the correct current at the right position of the RC circuit representing the soil. The new model can accurately reproduce the full physics of the transient phenomenon and is consistent with the modeling of the cable used in the IEC standards themselves. The new model is tested and validated against numerous finite-element simulations for realistic cable installations. [ABSTRACT FROM AUTHOR]

Emergency responders are typically notified immediately after a major earthquake strikes. However, a time delay, called the travel time, is usually experienced between the notification and the arrival of the responders on the scene. The reparative work necessary after the responders arrive takes an additional amount of time, called the response time, depending on the nature of the damage and the volume of resources available. In a smart city, the restoration time, which is the sum of the travel and response times, should be minimized. A new discrete-event-based simulation (DEBS) model is presented in this paper to estimate the restoration time needed to bring the situation under control after notifying the response center. The DEBS model not only relaxes restrictive assumptions on travel time made by the Markov chain models from the existing literature, but it can also quantify the impact of resource volumes on restoration times. Additionally, the DEBS model is very useful for training purposes. The DEBS model was employed on a case study from the state of Missouri (U.S.). The experiments demonstrate that numerical results with the model take a short amount of computational time and that it can be implemented on a real-time basis in a smart-city infrastructure. [ABSTRACT FROM AUTHOR]

The layout-induced cylindrical breakdown may occur as a result of the multifinger or circular layout-induced 3-D curvature effect resulting in the breakdown voltage reduction of the power device significantly. In this paper, by using effective doping concentration (EDC) concept, the inherent 3-D problem is simplified as a 1-D problem. Based on the EDC concept, a 1-D analytical model is presented to qualitatively and quantitatively explore the impact of curvature effect on the breakdown mechanism of SOI lateral double diffused MOS. The analytical solutions are found out to be consistent with the simulation results well obtained from MEDICI, a commercial technology computer-aided design tool. To the best of our knowledge, the proposed model is the first 1-D model which can accurately describe the 3-D curvature effect. [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]

Real-time (RT) simulation plays a fundamental role in the design and validation of hardware and software for power electronic converters and electric drives. In this paper, a field-programmable gate array (FPGA)-based RT platform for simulation of power converters and electric machines is presented. Strategies for modeling power electronic devices are explained and compared. In addition, a Thevenin-based equivalent model of a switch is enhanced to model the on characteristics of these devices. This motivates the design of an electrothermal algorithm for FPGA implementation. With respect to electric machines, different methods for modeling of the saturation characteristics are evaluated for their use in RT simulation. A procedure to efficiently compute the saturation characteristics is proposed. Finally, a hardware-in-the-loop model of an electric vehicle drive is used to illustrate the machine saturation. [ABSTRACT FROM PUBLISHER]

Co-simulation opens new opportunities to combine mature electromagnetic transients (EMT) and phasor-mode (PM) solvers, and takes advantage of their respective high accuracy and execution speed. In this paper, a relaxation approach is presented, iterating between an EMT and a PM solver. This entails interpolating over time the phasors of the PM simulation, extracting phasors from the time evolutions of the EMT simulation, and representing each subsystem with a proper multiport equivalent when simulating the other subsystem. Various equivalents are reviewed and compared in terms of convergence of the PM-EMT iterations. The paper also considers the update with frequency of the Thévenin impedances involved in the EMT simulation, the possibility to compute the EMT solution only once per time step, and the acceleration of convergence through a prediction over time of the boundary variables. Results are presented on a 74-bus, 23-machine test system, split into one EMT and one PM subsystem with several interface buses. [ABSTRACT FROM PUBLISHER]

The Wiener–Hammerstein (W–H) system is a popular and easy to understand class of Volterra nonlinear dynamical system. It consists of a static nonlinearity positioned between two dynamical subsystems. The main identification challenge resides in separating two linear filters as a rational form of poles and zeros. According to previous studies, an initial guess of the separated dynamics is made by browsing through all possible combinations of pole–zero. Then, based on the root-mean-square error (RMSE), good partitions are selected and later all parameters are optimized mutually to determine the best model. As the RMSE before and after optimization behaves erratically, this paper proposes the use of the Spearman correlation to select good models for optimizing. The proposed technique avoids the estimation of the local nonlinearity for each partition and optimizes only few good models. Thus, a massive speedup in processing time is achieved without any prior knowledge about the system. The theoretical verification complies with the simulation study and the measurement analysis. [ABSTRACT FROM AUTHOR]

Combined transmission and distribution systems (CoTDS) simulation for power systems requires development of algorithms and software that are numerically stable and at the same time accurately simulate dynamic events that can occur in practical systems. The time scales of simulation can be orders of magnitude apart making the combined simulation extremely challenging. This has led to increased research in applying co-simulation techniques for integrated simulation of the two systems. In this paper, two methods for dynamic co-simulation of CoTDS are proposed using parallel and series computation of the transmission system and distribution systems. The convergence of numerical methods in co-simulation is addressed from a fundamental mathematical perspective and the impact of the integration time-step is studied on proposed CoTDS dynamic co-simulation methods. Both these co-simulation methods are validated against total system simulation in a single time-domain simulation environment. The proposed CoTDS co-simulation method is also validated against commercial EMTP dynamic simulation. CoTDS dynamic co-simulation is further demonstrated on a New England 39-bus transmission system with ten load buses replaced by distribution systems including a 5780-node distribution system on one load bus for a detailed fault-induced delayed voltage recovery simulation study. [ABSTRACT FROM AUTHOR]

Uncertainty quantification of a technical system can be done using density estimation. We usually start with a stochastic model, which is fitted to the technical system, and the density estimation is done using data from this stochastic model. However, in any application, such a stochastic model will not be perfect, and the estimation of the density should take into account the inadequacy of the stochastic model. In this paper, we show how observed data of the real system together with an imperfect simulation model can be used to derive confidence bands for the density of the technical system. Our main result is that the newly introduced confidence bands allow to derive lower and upper bounds on the probability of intervals in the technical system. Furthermore, we present an upper bound on the area of the confidence band in case of a smooth density. The results are illustrated by applying the estimates to simulated and real data. [ABSTRACT FROM AUTHOR]

Biogeography-based optimization (BBO) is a population-based evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the science and study of the geographical distribution of biological organisms. In BBO, problem solutions are analogous to islands, and the sharing of features between solutions is analogous to the migration of species. This paper derives Markov models for BBO with selection, migration, and mutation operators. Our models give the theoretically exact limiting probabilities for each possible population distribution for a given problem. We provide simulation results to confirm the Markov models. [ABSTRACT FROM AUTHOR]

AC losses in superconductors are generated every time a time-varying current/field is present. Engineers must be able to predict these losses as accurately as possible during the design phase of power applications. The electrodynamics of superconductors can be formulated as a nonlinear eddy current problem in which the resistivity of the superconducting region is a highly nonlinear function of the current density. In 3-D finite-element simulations, it leads to time-consuming simulations and convergence issues. In this paper, we compare two different $E$ – $J$ constitutive equations, namely: 1) power law model and 2) the percolation model (PM), programmed within both the $H$ – $\phi $ and $T$ – $\phi $ formulations. Based on the 3-D case of a three-filament twisted superconducting wire, the numerical performance of all these formulations/material models is compared in terms of accuracy, computation times, number of time steps, and number of Newton iterations for different relaxation methods. It is shown that the combination of the $T$ – $\phi $ formulation and the $E$ – $J$ PM works fine and should be further developed, as it seems to constitute the best modeling option from both a numerical and physical point of view. [ABSTRACT FROM AUTHOR]

With the steady growth of chip complexity and shrinking feature size, multiple challenges are emerging for transistor level circuit simulation. Compact SPICE models are a fundamental part of circuit verification, serving as a bridge between the semiconductor design and foundry. It is also an integral part of SPICE simulators, which directly affects tool performance and therefore design schedule. While the advanced 3-D technology nodes deliver superior level of scalability, simulation cost is rapidly increasing due to the computational complexity introduced by device model equations and the number of iterations required for numerical methods. In this paper, an efficient solution is proposed to reduce the computational cost associated with UC Berkeley BSIM-CMG device model evaluation, by applying robust Verilog compiler and computer algebra techniques to the device model equations. As a result of this implementation, simulation time reduction is up to 72% for complex blocks of the latest generation processor design. [ABSTRACT FROM PUBLISHER]

In spite of the wide improvement in computer simulation packages, analyzing, and optimizing the simulation model, particularly under uncertainty can still be computationally expensive and time-consuming. This paper aims to tackle these features by proposing a comprehensive methodology applied to black-box stochastic simulation models under uncertainty. For this purpose, the common surrogate model as Kriging metamodel is served to fit the simulation input–output data produced by Latin hypercube sampling experimental design. Taguchi terminology of robust design enables the optimization methods to control uncertainty and uncontrollable environmental factors. So as to formulate robust counterpart optimization, three different models in the class of dual-response surface are integrated with metamodel and robust design. Leave-one-out cross-validation is applied to validate the Kriging metamodel. Finally, a numerical case study as a direct speed control of dc motor under uncertainty is served to demonstrate the applicability of the proposed method in real engineering problems. This simplified and practical mechatronics case illustrates how the proposed procedure can be expanded for analyzing and optimizing the real complex systems. [ABSTRACT FROM AUTHOR]

The proper generalized decomposition (PGD) is a model order reduction method which allows to reduce the computational time of a numerical problem by seeking for a separated representation of the solution. The PGD has been already applied to study an electrical machine but at standstill without accounting the motion of the rotor. In this paper, we propose a method to account for the rotation in the PGD approach in order to build an efficient metamodel of an electrical machine. Then, the machine metamodel will be coupled to its electrical and mechanical environment in order to obtain accurate results with an acceptable computational time on a full simulation. [ABSTRACT FROM AUTHOR]

The simulation of electrical discharges has been attracting a great deal of attention. In such simulations, the electric field computation dominates the computational time. In this paper, we propose a fast tree algorithm that helps to reduce the time complexity from O(N^2) (from using direct summation) to $O(N\log N)$ . The implementation details are discussed and the time complexity is analyzed. A rigorous error estimation shows the error of the tree algorithm decays exponentially with the number of truncation terms and can be controlled adaptively. Numerical examples are presented to validate the accuracy and efficiency of the algorithm. [ABSTRACT FROM AUTHOR]

Near-threshold and sub-threshold voltage designs have been identified as possible solutions to overcome the limitations introduced by energy consumption in modern very large scale integration circuits. However, as we approach sub-10 nm transistor technology, aggressive voltage, and gate length scaling will reduce the reliability of logic circuits due to the increasing impact of noise and variability effects. Therefore, designers need new tools to simulate logic circuits in the presence of noise. Time-domain analysis helps understand how transient faults affect a circuit and can guide designers in producing noise-resistant circuitry. However, standard approaches to modeling intrinsic noise sources in the time domain are computationally expensive. Moreover, small noise-driven fluctuations in electron occupation of circuit nodes introduce time-varying biasing point fluctuations, increasing the modeling complexity. To address these challenges, this paper introduces a new approach to modeling thermal noise and random telegraph signal noise directly in the time domain by developing and solving a series of stochastic differential equations. In comparisons to traditional SPICE-based simulations, our approach can provide three orders of magnitude speedup in simulation time without sacrificing accuracy. Moreover, we introduce a novel, iterative threshold-crossing algorithm, aimed at the efficient sampling of rare noise transients. We show that Monte-Carlo simulations based on this approach can detect rare high-amplitude single event transients that would be impossible to uncover with standard transient simulators. [ABSTRACT FROM PUBLISHER]

Analog components are fundamental blocks of smart systems, as they allow a tight interaction with the environment, in terms of both sensing/actuation and communication. This impacts on the design of the overall system, and mainly on the validation phase, that thus requires the joint simulation of digital and analog aspects. In this scenario, this paper proposes the automatic conversion of analog models to C++-based languages, to remove the overhead of co-simulation with traditional virtual platform tools. The proposed methodology allows to convert a given analog description to either: 1) a fully equivalent description or 2) an abstract representation for faster simulation which models only the aspects of interest. Effectiveness and correctness have been proved on a number of case studies that highlight the effectiveness and potentiality of the proposed methodology. [ABSTRACT FROM AUTHOR]

The objective of this paper is to determine an optimal plan for expanding the capacity of a power grid in order to minimize the likelihood of a large cascading blackout. Capacity-expansion decisions considered in this paper include the addition of new transmission lines and the addition of capacity to existing lines. We embody these interacting considerations in a simulation optimization model, where the objective is to minimize the probability of a large blackout subject to a budget constraint. The probability of a large-scale blackout is estimated via Monte Carlo simulation of a probabilistic cascading blackout model. Because the events of interest are rare, standard simulation is often intractable from a computational perspective. We apply a variance-reduction technique within the simulation to provide results in a reasonable time frame. Numerical results are given for some small test networks including an IEEE 14-bus test network. A key conclusion is that the different expansion strategies lead to different shapes of the tails of the blackout distributions. In other words, there is a tradeoff between reducing the frequency of small-scale blackouts versus reducing the frequency of large-scale blackouts. [ABSTRACT FROM PUBLISHER]

A new, nonlinear, frequency-domain behavioral model, based on Padé approximation theory, is presented in this paper. The new Padé model is similar in concept to the X-parameter method, but it uses a rational function instead of the X-parameter model's polynomial expression. The basic theory of the proposed Padé model and the model extraction methodology are provided. The proposed Padé approach increases the available modeling space beyond that available to the X-parameter method, and the performance of a selection of this family of models under various loading conditions is described in this paper. Along with the examples displaying the ability of the new model to predict fundamental frequency behavior, a second-harmonic example is also provided, with simulation results presented in both the frequency domain and the time domain. Based on the simulation studies and experimentally measured results, the new Padé model shows good accuracy and a high level of stability. All of these characteristics show that the proposed Padé model has high potential in RF design. [ABSTRACT FROM AUTHOR]

Reliable and accurate photovoltaic (PV) models are essential for simulation of PV power systems. A solar cell is typically represented by a single diode equivalent circuit. The circuit parameters need to be estimated accurately to get an accurate model. However, one circuit parameter was assumed because of the limited information provided by commercial manufacturing datasheets, and thus the model accuracy is affected. This paper proposes a parameterization approach for PV models to improve modeling accuracy and reduce implementation complexity. It develops a method to accurately estimate circuit parameters, and thus improving the overall accuracy, relying only on the points provided by all commercial modules datasheet. The proposed modeling approach results in two simplified models demonstrating the advantage of fast simulation. The effectiveness of the modeling approach is thoroughly evaluated by comparing the simulation results with experimental data of solar modules made of mono-crystalline, multi-crystalline, and thin film. [ABSTRACT FROM PUBLISHER]

Simulation scheme constructed by transient models is widely used for interconnected power system studies. However, it has shortcomings when used in automatic generation control (AGC) and AGC relevant fields. In this paper, a novel simulation scheme designed for AGC and its relevant studies is presented. The scheme uses dynamic energy balancing equation and a single central frequency as core algorithm. Moreover, models described by algebraic equations are adopted instead of transient models described by differential equations. The simplified models reduce computational power requirement to about 3% of transient models and require fewer parameters. By ignoring transient dynamics and inter-area oscillations which are insignificant in AGC timescale, the presented scheme achieves high computational efficiency and acceptable accuracy making it acceptable for up to year-long simulation. At the end of the paper, comparative tests are performed to provide differences, validity and accuracy of proposed scheme. [ABSTRACT FROM PUBLISHER]

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 proposes a new method of decoupling and subdividing electrical circuits, containing power-electronics devices, in order to achieve fast and accurate real-time simulation. In this technique, each state variable can be discretized using different discretization methods. Combining implicit and explicit ODE solvers, state-space equations are decoupled while remaining accurate and stable. Unlike most traditional decoupling techniques previously proposed, the proposed one does not require artificial delay or supplementary states to be added in order to decouple the system. Furthermore, this technique is meant to be implemented with commercially available simulation software. By doing so, a large and complex circuit containing several hundreds of state variables can be easily and accurately simulated with minor modification to the existing models. Finally, stability and accuracy of the proposed technique are thoroughly demonstrated in a numerical example during steady state and under faulty conditions. [ABSTRACT FROM PUBLISHER]

Many computational models of visual attention performing well in predicting salient areas of 2D images have been proposed in the literature. The emerging applications of stereoscopic 3D display bring an additional depth of information affecting the human viewing behavior, and require extensions of the efforts made in 2D visual modeling. In this paper, we propose a new computational model of visual attention for stereoscopic 3D still images. Apart from detecting salient areas based on 2D visual features, the proposed model takes depth as an additional visual dimension. The measure of depth saliency is derived from the eye movement data obtained from an eye-tracking experiment using synthetic stimuli. Two different ways of integrating depth information in the modeling of 3D visual attention are then proposed and examined. For the performance evaluation of 3D visual attention models, we have created an eye-tracking database, which contains stereoscopic images of natural content and is publicly available, along with this paper. The proposed model gives a good performance, compared to that of state-of-the-art 2D models on 2D images. The results also suggest that a better performance is obtained when depth information is taken into account through the creation of a depth saliency map, rather than when it is integrated by a weighting method. [ABSTRACT FROM AUTHOR]

This paper deals with the development of a hardware-in-the-loop (HIL) real-time simulation setup for vehicular systems. In modeling a vehicular drivetrain, the battery model poses the greatest challenge. Mathematical battery models suitable for real-time and transient simulation are often inaccurate due to internal electrochemical reactions in the battery and external factors such as loading conditions. To model these phenomena precisely while maintaining low computational intensity as required for real-time simulation is a prohibitively difficult task. In lieu of a mathematical model, this paper presents a simulation setup where actual batteries are interfaced with a real-time simulator. It provides a platform to test the emerging battery technologies for which dependable models may not be readily accessible. Results are presented for an HIL model of a planetary-gear-system hybrid electric vehicle with actual batteries in the loop of the simulation. [ABSTRACT FROM PUBLISHER]

This paper presents the evaluation of the performance, in terms of uncertainty, of a tool designed to estimate the main parameters of a model of a photovoltaic panel (PVP) under real and/or simulated working conditions. The presented tool permits the characterization of the panel, and it is useful to predict its behavior in whatever working condition; in this way, it is possible to compare the actual and expected performance to prevent any decrease in the output power, so permitting the replacement of the monitored module before it goes out of order or its efficiency falls under a given threshold. The well-known two-diode model is used to estimate the parameters of the electrical equivalent circuit of the PVP and to simulate the I–V and P–V characteristic curves in any given environmental condition of irradiance and/or temperature. The model and the estimation algorithm are implemented with MATLAB functions, whereas data acquisition and result presentation are managed by a LabVIEW graphics user interface. The presented tool has been validated against an experimentally characterized PVP. The environmental parameters of the model such as irradiance and temperature have been set (with their respective uncertainties) during simulations or directly measured during the outdoor tests, whereas the others parameters have been evaluated using a best-fit algorithm on the measured data. The estimation is based on the minimization of a new objective function and on a modified expression of the model resistances, which differ from those mentioned in the available literature. After a review of the state of the art, this paper provides the description of the estimation technique and its validation by means of simulations and experiments. Some results are also provided to illustrate the performance of the proposed test method. [ABSTRACT FROM AUTHOR]

The efficiency of multiterminal dc (MTDC) grid simulation decreases with an expansion of its scale and the inclusion of accurate component models. Thus, the variable time-stepping scheme is proposed in this paper to expedite the electromagnetic transient computation. A number of criteria are proposed to evaluate the time-step and regulate it dynamically during simulation. Meanwhile, as the accuracy of results is heavily reliant on the switch model in the modular multilevel converter, the nonlinear behavioral model with a greater accuracy is proposed in addition to the classic ideal model, and their corresponding variable time-stepping schemes are analyzed. Circuit partitioning is effective in accelerating the MTDC grid simulation via fine-grained separation of nonlinearities. A subsequent large number of identical circuits enabled a massively parallel implementation on the graphics processing unit, which achieved a remarkable speedup over the CPU-based implementation. The inclusion of variable time-stepping schemes eventually makes the simulation of MTDC grid with highly detailed nonlinear switch models feasible. The results are validated by commercial device-level and system-level simulation tools. [ABSTRACT FROM AUTHOR]

The modular multilevel converter (MMC) has attracted extensive research in recent years. An appropriate model is necessary to analyze stability or to design MMC controllers. Several published MMC models have been derived in single-phase form to simplify the modeling mathematics. However, little attention is given to the zero-sequence voltage, which introduces coupling in the single-phase model and leads to significant error. In this paper, after revealing the mechanism behind the zero-sequence voltage, a more accurate generalized single-phase MMC model is proposed, which eliminates the zero-sequence voltage coupling effect and is linearized based on harmonic state space (HSS) theory to precisely characterize the internal harmonic features of MMC. A systematic HSS modeling process is presented for both open-loop and closed-loop conditions. And the proposed model is generalized as it can incorporate different control strategy by controller transfer function substitution. Hence it is valuable to analyze MMC stability and dynamics. Model effectiveness is verified by simulation results. [ABSTRACT FROM AUTHOR]

This paper presents a computationally efficient two-dimensional (2-D) steady-state model for fuel cell real-time control implementation. Both the fluid and electrochemical physical domains are considered in the proposed real-time model. The fuel cell under-rib convection is fully described by considering the geometry of serpentine channel. In addition, in order to solve the implicit activation voltage loss and further explore the computational performance, three numerical root-searching algorithms: bisection, secant, and Newton–Raphson methods are applied to the proposed implicit iterative solver and compared. The preferred secant method has been proven to effectively improve both the efficiency and robustness performance of the proposed real-time fuel cell model. Moreover, a computational fluid dynamic based COMSOL fuel cell model is used to validate the calculation accuracy. Furthermore, the practical feasibility of the presented real-time model has been verified using an RT-LAB simulator platform from Opal-RT. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for modeling the deployment of implantable devices used in minimally invasive vascular interventions. Motivated by the clinical need to perform preinterventional rehearsals of a stent deployment, we have developed methods enabling virtual device placement inside arteries, under the constraint of real-time application. This requirement of rapid execution narrowed down the search for a suitable method to the concept of a dynamic mesh. Inspired by the idea of a mesh of springs, we have found a novel way to apply it to stent modeling. The experiments conducted in this paper investigate properties of the stent models based on three different spring types: lineal, semitorsional, and torsional springs. Furthermore, this paper compares the results of various deployment scenarios for two different classes of devices: a stent graft and a flow diverter. The presented results can be of a high-potential clinical value, enabling the predictive evaluation of the outcome of a stent deployment treatment. [ABSTRACT FROM PUBLISHER]

This paper presents a new nonlinear model of the normal force that arises during compliant contact between two spheres, or between a sphere and a flat plate. It differs from a well-known existing model by only a single term. The advantage of the new model is that it accurately predicts the measured values of the coefficient of restitution between spheres and plates of various materials, whereas other models do not. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the design of a reduced-order discontinuous Galerkin (DG) method based on the proper orthogonal decomposition (POD) method for electromagnetic simulation. A centered flux approximation for surface integral and a second-order leap-frog scheme for advancing in time are applied in the classical DG method. The POD basis is created by the eigensystem of the correlation matrix, which is generated by the snapshot matrix whose columns are the snapshot vectors extracted from the high-fidelity DG simulation. The POD discontinuous Galerkin time-domain formulation with lower dimension and sufficiently high accuracy is established by applying a Galerkin projection for the semidiscrete DG scheme. The overall goal is to reduce the computational cost while maintaining an acceptable level of accuracy. Numerical experiments for electromagnetic problems illustrate the performance of the proposed reduction method. [ABSTRACT FROM AUTHOR]

Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels. [ABSTRACT FROM AUTHOR]

Road traffic simulation is a useful tool for studying road traffic and evaluating solutions to traffic problems. Large-scale agent-based road traffic simulation is computationally intensive, which triggers the need for conducting parallel simulation. This paper deals with the synchronization problem in parallel agent-based road traffic simulation to reduce the overall simulation execution time. We aim to reduce synchronization operations by introducing some redundant computation to the simulation. There is a trade-off between the benefit of reduced synchronization operations and the overhead of redundant computation. The challenge is to minimize the total overhead of redundant computation and synchronization. First, to determine the amount of redundant computation, we proposed a way to define extended layers of partitions in the road network. The sizes of extended layers are determined by the behavior of agents and the topology of road networks. Second, due to the dynamic nature of road traffic, a heuristic was proposed to adjust the amount of redundant computation according to traffic conditions during simulation run-time to minimize the overall simulation execution time. The efficiency of the proposed method was investigated in a parallel agent-based road traffic simulator using real-world network and trip data. Results have shown that the method can reduce synchronization overhead and improve the overall performance of the parallel simulation significantly. [ABSTRACT FROM PUBLISHER]

In this paper, the balance control of a ball and beam system is considered. Based on the T-S fuzzy modeling, the dynamic model of the ball and beam system is formulated as a strict feedback form with modeling errors. Then, an adaptive dynamic surface control (DSC) is utilized to achieve the goal of ball positioning subject to parameter uncertainties. The robust stability of the closed-loop system is preserved by using the Lyapunov theorem. In addition to simulation results, the proposed T-S fuzzy model-based adaptive dynamic surface controller is applied to a real ball and beam system for practical evaluations. Simulation and experimental results illustrate that the proposed control scheme has much better performance than that of conventional DSC. Furthermore, parameter uncertainties and external disturbance are considered to highlight the robustness of the proposed control scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we present an accurate and computationally efficient model for circuit simulation of ultrathin-body silicon-on-insulator MOSFETs with strong back-gate control. This work advances previous works in terms of numerical accuracy, computational efficiency, and behavior of the higher order derivatives of the drain current. We propose a consistent analytical solution for the calculation of front- and back-gate surface potentials and inversion charge. The accuracy of our surface potential calculation is on the order of nanovolts. The drain current model includes velocity saturation, channel-length modulation, mobility degradation, quantum confinement effect, drain-induced barrier lowering, and self-heating effect. The model has correct behavior for derivatives of the drain current and shows an excellent agreement with experimental data for long- and short-channel devices with 8-nm-thin silicon body and 10-nm-thin BOX. [ABSTRACT FROM AUTHOR]