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Line-commutated converters are extensively used as the interface between ac grids and classic HVDC systems. At the inverter side, commutation failure of switches is one of the most common faults that can pose threats to the system operation. Practical and reliable study of such phenomena relies on accurate and efficient converter models for simulations. Recently, a parametric average-value model (PAVM) has been presented for ac–dc rectifiers, which considers the internal faults of the converter. In this paper, the PAVM methodology is extended to the dc–ac inverter systems, including the commutation failure of switches. The proposed PAVM also augments an automatic fault detection technique to determine the faulty switches. Using comprehensive simulation studies, the developed model is verified to accurately predict the commutation failure of switches and reconstruct the waveforms consistent with the detailed switching models of inverters while being computationally more efficient. The proposed PAVM is envisioned to be an efficient and accurate asset for simulation of HVDC systems and inevitable when faults of switches need to be considered. [ABSTRACT FROM AUTHOR]

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]

In this paper, a coupled interaction matrix is proposed to describe the interactions between line outages and the load shed at buses. The coupled interaction matrix is effectively estimated by the Expectation Maximization algorithm. A highly probabilistic coupled interaction model is further proposed to efficiently generate cascades with both line outages and the load shed based on the coupled interaction matrix and the distribution of initial outages. To mitigate cascading failures, critical links are identified based on the coupled interaction matrix by calculating a comprehensive severity index that considers the consequences of both line outages and the load shed. Simulation results on the IEEE 300-bus system verify the effectiveness of the proposed approach. The cascades generated from the coupled interaction model match the statistics of the original cascades very well. The identified critical links based on the comprehensive severity index enable a proper tradeoff between reducing line outages and reducing the load shed, leading to a better mitigation effect than only considering either line outages or the load shed. [ABSTRACT FROM AUTHOR]

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]

Two challenges are combined when compressed tests are computed for path delay faults: 1) path delay faults that are important to detect are associated with long paths, and many of these faults are undetectable and 2) it may not be possible to compress a given test for a path delay fault. This paper addresses these challenges in the context of test data compression methods that are based on a linear-feedback shift-register (LFSR). The basic approach that this paper uses modifies initially random seeds for the LFSR into seeds that produce tests for detecting target faults. This approach can find seeds even if the available tests cannot be compressed into seeds. In addition, the procedure described in this paper also selects detectable path delay faults to address the presence of undetectable path delay faults in the set of target faults. For this purpose it uses a metric that measures the similarity between target and detected path delay faults, and attempts to compute seeds that increase the values of this metric. Experimental results are presented to demonstrate the ability of the procedure to detect path delay faults in benchmark circuits. [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]

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]

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]

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]

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]

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]

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]

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]

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]

Optimal control provides a systematic approach to control robots. However, computing optimal controllers for hardware-in-the-loop control is sensitively affected by modeling assumptions, computationally expensive in online implementation, and time-consuming in practical application. This makes the theoretical appeal of optimization challenging to exploit in real-world implementation. In this paper, we present a novel online optimal control formulation that aims to address the above-mentioned limitations. The formulation combines a model with measured state information to efficiently find near-optimal feedback controllers. The idea to combine a model with measurements from the actual motion is similar to what is used in model predictive control formulations, with the difference that here the model is not used for future prediction, the optimization is performed along the measured trajectory of the system, and the online computation is reduced to a minimum; it requires a small-scale, one time step, static optimization, instead of a large-scale, finite time horizon, dynamic optimization. The formulation can be used to solve optimal control problems defined with nonlinear cost, nonlinear dynamics, and box-constrained control inputs. Numerical simulations and hardware-in-the-loop experiments demonstrate the effectiveness of the proposed hardware-in-the-loop optimal control approach. [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]

How animals navigate in their cross-continental migration has puzzled scientists for centuries. To date, the mechanism behind this mysterious navigation remains unclear. In this paper, a hypothesis is developed and computer simulations have been performed to investigate long-distance animal navigation. Simulation results show that animals may be able to complete their long-distance navigation by observing a spatial angle included by the geomagnetic field line and a geographic direction, without necessarily knowing any prior landmark information. Our results not only match existing observation reports in detail on the long-distance migration routes of animals, but also are able to explain the conflicting evidence on the role of geomagnetic field in animal navigation. We think our results could help reveal the actual mechanism of animal navigation. This paper also provides a potential solution for global and local area navigation of mankind and machines assisted by artificial sensors. [ABSTRACT FROM AUTHOR]

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]

With the reduced noise margin brought by relentless technology scaling, power integrity assurance has become more challenging than ever. On the other hand, traditional design methodologies typically focus on a single design layer without much cross-layer interaction, potentially introducing unnecessary guard-band and wasting significant design resources. Both issues imperatively call for a cross-layer framework for the co-exploration of power delivery (PD) and system architecture, especially in the early design stage with larger design and optimization freedom. Unfortunately, such a framework does not exist yet in the literature. As a step forward, this paper provides a run-time simulation framework of both PD and architecture and captures their interactions. Enabled by the proposed recursive run-time PD model, it can achieve smaller than 1% deviation from SPICE for an entire PD system simulation. Moreover, with seamless interactions among architecture, power and PD simulators, it can simulate actual benchmarks within reasonable time. The experimental results of running PARSEC suite have demonstrated the framework’s capability to discover the co-effect of PD and architecture for early stage design optimization. Moreover, it also shows multiple over-pessimism in traditional PD methodologies. Finally, the framework is able to investigate the impact of dynamic noise on system level oxide breakdown reliability and shows 31%–92% lifetime estimation deviations from typical static analysis. [ABSTRACT FROM AUTHOR]

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]

In this paper, we present a decentralized load estimation approach to support real-time volt/var optimization in distribution networks with high penetration of distributed generation. The decentralized load estimation scheme relies on local information and on a limited amount of information from neighbor areas. We defined a procedure for measurement selection and feeder partitioning so as to limit communication needs and allow prioritizing the estimation accuracy for selected loads. The measurement selection and feeder partitioning methods are based on the mutual information and minimum-redundancy-maximum-relevance concepts. We tested the proposed approach with a modified radial IEEE 34-node test feeder and a weakly meshed IEEE 123-node test feeder. The effectiveness of the method is validated using a hardware-in-the-loop simulation platform. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm for the estimation of the longitudinal and lateral forces exerted at wheel level between tires and ground is presented. Starting from a modified version of the single track vehicle model, which also includes the steady-state effect of pitch and roll on the planar movement of the vehicle, the structure is designed as a cascade of two Sub-Optimal Second-Order Sliding-Mode (S-SOSM) observers, featuring an adaptive feedback that helps improving the accuracy of the estimation of the longitudinal forces. The presented approach is purposely designed so that only standard sensors, which are usually available in commercial vehicles, are exploited. In order to alleviate the high-frequency vibrations introduced by the Sliding-Mode technique, an EKF is added as a second step, which considers the output of the S-SOSM observer as a noisy measurement, hence the virtual sensor nomenclature. The method is evaluated on experimental data, displaying good performance both in terms of accuracy and chattering alleviation. [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]

Before a new airport runway is built, the electromagnetic compatibility of the instrument landing system (ILS) must be fully taken into consideration. The electromagnetic compatibility requirements for airports are becoming more and more complex, so rather than using traditional ray-tracing (RT) simulation models, a more accurate approach such as the finite-difference time domain (FDTD) is needed. The application of FDTD to ILS signal modeling suffers from an intensively high computation burden. The computation burden is owing to: 1) the FDTD has to loop a large number of time steps and 2) for every step, a huge number of cells has to be updated. This paper solves the above-mentioned issues by twofold. First, this model allows a large Courant–Friedrich–Levy number for the FDTD to reduce the total time step. This is achieved by combining the locally one-dimension (LOD) FDTD and the complex-envelope (CE) technique. The combination of CE, LOD, and FDTD (CE-LOD-FDTD) makes the model update with larger time step and retain the same level of accuracy. Second, we propose a set of novel GPU-based acceleration algorithms to update the field in parallel for reducing the computation time. By comparing the measurement results, it is shown that the FDTD model is more accurate than the traditional RT-based method. Our GPU-based CE-LOD-FDTD model is 22 times faster than the conventional parallel FDTD model in a multicore machine. [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]

As Vehicular Ad hoc Network (VANET) features random topology and accommodates freely connected nodes, it is important that the cooperation among the nodes exists. This paper proposes a trust model called Implicit Web of Trust in VANET (IWOT-V) to reason out the trustworthiness of vehicles. Such that untrusted nodes can be identified and avoided when we make a decision regarding whom to follow or cooperate with. Furthermore, the performance of Cooperative Intelligent Transport System (C-ITS) applications improves. The idea of IWOT-V is mainly inspired by web page ranking algorithms such as PageRank. Although there does not exist explicit link structure in VANET because of random topology and dynamic connections, social trust relationship among vehicles exists and an implicit web of trust can be derived. To accomplish the derivation, two algorithms are presented, i.e., BayesTrust and VehicleRank. They are responsible for deriving the local and global trust relationships, respectively. The simulation results show that IWOT-V can accurately identify trusted and untrusted nodes if enough local trust information is collected. The performance of IWOT-V affected by five threat models is demonstrated, and the related discussions are also given. [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]

Power converters in the system-level real-time simulation are usually emulated by L/C-based associated discrete circuit (L/C-ADC). However, the L/C-ADC approaches may suffer from two issues: How to mitigate the unacceptable virtual power loss especially in high-frequency applications, and how to tune LC parameters setting which is affected by the external circuit. This paper proposes a novel generalized associated discrete circuit (G-ADC) model with parameterized history current sources. By utilizing the stability region of the feasible parameter space, the optimized G-ADC models with the best damping characteristic are developed for both two-level and three-level converters. The analytical results also guarantee that the parameters of the optimized G-ADC model are independent of the external circuit for most power grid applications. Furthermore, an field programmable gate array (FPGA)-based real-time simulation platform is built to verify the feasibility of the proposed scheme. Extensive simulation and hardware-in-loop experiment results demonstrate the effectiveness and superiority of best-damped models as well as the modeling flexibility corresponding to insensitivity to operating conditions and external system parameters. [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]

Asynchronous multisensor systems have been widely equipped on various host platforms to meet the requirements of modern navigation campaigns. However, the existing asynchronous fusion algorithms are not efficient in many challenged environments, due to the limitations of communication condition, out-of-sequence observation, and computation affordance. To solve these problems, this paper proposes a batch state asynchronous fusion algorithm with feedback for distributed architecture systems. It is optimal in the sense of minimum mean-squared estimation and its fusion solution is rigorously derived by fully considering the correlations of sequential/cross channels and one-step prediction information. The final fusion solution is straightforward expressed with the combinations of multiple local Kalman filtering estimates outputs during one fusion period. Moreover, no additional interpolation, extrapolation or synchronization procedures are required. Furthermore, to alleviate the computational burden of our proposed algorithm, its approximation form is also given by replacing the weighting matrix by the weighting scalar. Simulations are carried out to illustrate the efficiency and the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Current nanometer CMOS circuits show an increasing sensitivity to deviations in first-order parameters and suffer from process variations during manufacturing. To properly assess and support test validation of digital designs, low-level fault simulation approaches are utilized to accurately capture the behavior of CMOS cells under parametric faults and process variations as early as possible throughout the design phase. However, low-level simulation approaches exhibit a high computational complexity, especially when variation has to be taken into account. In this paper, a high-throughput parallel fault simulation at switch level is presented. First-order electrical parameters are utilized to capture CMOS-specific functional and timing behavior of complex cells allowing to model faults with transistor granularity and without the need of logic abstraction. Furthermore, variation modeling in cells and transistor devices enables broad and efficient variation analyses of faults over many circuit instances for the first time. The simulation approach utilizes massive parallelization on graphics processing units by exploiting parallelism from cells, stimuli, faults, and circuit instances. Despite the lower abstraction levels of the approach, it processes designs with millions of gates and outperforms conventional fault simulation at logic level in terms of speed and accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a new simulation approach based on the functional mock-up interface standard for parallel and multistep simulation of electromagnetic transients in power grids with computationally expensive control systems. The control systems are represented by slave subsystems, which are decoupled in memory from the power network and encapsulated in functional mock-up units. The simulation modes are either asynchronous or synchronous. In the asynchronous mode, the subsystems are simulated in parallel, whereas in the synchronous mode, the simulation of each subsystem is executed in a sequential multistep environment. Considerable computation time gains in both modes have been observed in power system protection studies on large-scale networks with accuracy properly maintained. [ABSTRACT FROM AUTHOR]

This paper presents a new passivity enforcement technique for frequency-dependent network equivalents expressed as rational models. The main feature of the proposed technique is that only a few residues of the rational model are perturbed, so that the passivity enforcement procedure becomes computationally more efficient compared to existing methods. The proposed technique is verified on practical network cases. It is demonstrated that the accuracy of the perturbed model is maintained in frequency-domain fitting and time-domain simulations of transients. [ABSTRACT FROM AUTHOR]

Among the different types of bilayer tunneling field-effect transistors exploiting interband tunneling phenomena with tunneling directions aligned with gate-induced electric fields, the utilization of InAs/GaSb channels proves to be an appealing means to enhance ON-current levels. Ultrathin channel thicknesses make quantum confinement be the agent that closes the broken gap of the InAs/GaSb heterojunction leading to a staggered gap which blocks the tunneling current in the OFF state. In this paper, the gate leakage tunneling current is analyzed as one of the main critical processes degrading the performance of the proposed structure. Appropriate gate stacks of HfO2/Al2O3 combined with gate-to-drain underlaps are shown to effectively suppress this leakage tunneling, while at the same time, preserve an adequate electrostatic control over the channel. Simulation results for the most optimized configurations feature ON-state levels of up to $400\mu \text{A}/\mu \text{m}$ and subthreshold swings of $\approx 3$ mV/dec over more than 7 decades of current. [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]

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]

In recent studies, we introduced the concept of functionalized magnetic force as a method to prevent nanoparticles from sticking to vessel walls caused by extensive simulation and in vitro experiments involving a Y-shaped channel. In this paper, we further investigated the effectiveness of the functionalized magnetic force with a realistic 3-D vessel through simulations. For the simulations, we considered a more realistic continuous injection of particles with different magnetic forces and frequencies. Based on the results from our simulation studies, we performed in vivo mice experiments to evaluate the effectiveness of using a functionalized magnetic force to aid magnetic nanoparticles (MNPs) in crossing the blood–brain barrier (BBB). To implement the functionalized magnetic force, we developed an electromagnetic actuator regulated by a programmable direct current power supply. Our results indicate that a functionalized magnetic field (FMF) can effectively prevent MNPs from sticking, and also guide them across the BBB. We used 770 nm fluorescent carboxyl MNPs in this paper. Following intravenous administration of MNPs into mice, we applied an external magnetic field to mediate transport of the MNPs across the BBB and into the brain. Furthermore, we evaluated the differential effects of FMFs (0.25, 0.5, and 1 Hz) and constant magnetic fields (CMFs) on the transport of MNPs across the BBB. Our results showed that an FMF is more effective than a CMF in the transport and uptake of MNPs across the BBB in mice. In particular, applying an FMF with a 3 A current and 0.5 Hz frequency mediated the greatest transport and uptake of MNPs across the BBB in mice. [ABSTRACT FROM PUBLISHER]

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]

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]

Exploring the design space of computer architectures generally consists of a trial-and-error procedure where several architectural configurations are evaluated by using simulation techniques. The final goal of the multiobjective design space exploration (DSE) process is the identification of architectural configurations optimal for a set of target objective functions, typically power consumption, and performance. Simulations are computationally expensive making it rather hard to efficiently explore the design space to identify high-quality configurations in an acceptable exploration time when relying solely on a single-core machine to run simulations. To tackle this problem, engineers proposed solutions based on either: 1) the use of approximate analytic performance models to prune the suboptimal regions of the design space by reducing the number of simulations to run or 2) the use of parallel computing resources to run different simulations concurrently. In this paper we demonstrate that, to efficiently speedup the DSE process while fully exploiting the parallel computing infrastructure, we need to combine the two techniques together in a structured manner. In this paper, we investigate this issue and we propose a DSE solution that exploits approximate analytic prediction models to improve the simulation schedule on a parallel computing environment rather than to prune the number of simulations. Experimental results demonstrate that the proposed technique provides a speedup from 1.26\boldsymbol \times to 4\boldsymbol \times with respect to other parallel state-of-the art DSE techniques. [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 accuracy of two equivalent antenna representations, near-field sources and far-field sources (FFSs), is evaluated for an antenna installed on a simplified platform. We show that the accuracy of the installed far-field and surface current for the investigated weakly scattering platform depends strongly on the configurations associated with the equivalent antenna representation. The root-mean-square error for the installed far-field error varies between 4.4%–8.4% for the considered configurations of near-field equivalent representations installed on the investigated platform. When using FFSs, the design parameters have an even larger influence of the achieved accuracy. There is also a varying accuracy depending on the type of numerical method used. Based on the results, some recommendations on the choice of subdomain for the equivalent antenna representation are given associated with the platform. In industrial antenna applications, the accuracy in determining, e.g., installed far-fields and antenna isolation on large platforms is critical. Equivalent representations can reduce the fine-detail complexity of antennas and thus give an efficient numerical description to be used in large-scale simulations. The results, in this paper, highlight to antenna designers and system engineers the accuracy challenges associated with the use of equivalent antenna representations. [ABSTRACT FROM AUTHOR]

The problem of low-rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We show that such a hierarchical Gaussian prior has the potential to encourage a low-rank solution. Based on the proposed hierarchical prior model, we develop a variational Bayesian matrix completion method, which embeds the generalized approximate massage passing technique to circumvent cumbersome matrix inverse operations. Simulation results show that our proposed method demonstrates superiority over some state-of-the-art matrix completion methods. [ABSTRACT FROM AUTHOR]

Graph Pattern Matching (GPM) has been used in lots of areas, like biology, medical science, and physics. With the advent of Online Social Networks (OSNs), recently, GPM has been playing a significant role in social network analysis, which has been widely used in, for example, finding experts, social community mining, and social position detection. Given a query which contains a pattern graph $G_Q$ and a data graph $G_D$ , a GPM algorithm finds those subgraphs, $G_M$, that match $G_Q$ in $G_D$ . However, the existing GPM methods do not consider the multiple end-to-end constraints of the social contexts, like social relationships, social trust, and social positions on edges in $G_Q$ , which are commonly found in various applications, such as crowdsourcing travel, social network based e-commerce, and study group selection, etc. In this paper, we first conceptually extend Bounded Simulation to Multi-Constrained Simulation (MCS), and propose a novel NP-Complete Multi-Constrained Graph Pattern Matching (MC-GPM) problem. Then, to address the efficiency issue in large-scale MC-GPM, we propose a new concept called Strong Social Component (SSC), consisting of participants with strong social connections. We also propose an approach to identifying SSCs, and propose a novel index method and a graph compression method for SSC. Moreover, we devise a multithreading heuristic algorithm, called M-HAMC, to bidirectionally search the MC-GPM results in parallel without decompressing graphs. An extensive empirical study over five real-world large-scale social graphs has demonstrated the effectiveness and efficiency of our approach. [ABSTRACT FROM PUBLISHER]

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]