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Ranking and selection (R&S) procedures are powerful tools to enhance the efficiency of simulation-based optimization. In this paper, we consider the R&S problem subject to stochastic constraints and seek to improve the selection efficiency by incorporating the information from across the domain into quadratic regression metamodels. To better fulfill the quadratic assumption of the regression metamodel used in this paper, we divide the solution space into adjacent partitions such that the underlying functions of both the objective and constraint measures in each partition are approximately quadratic with homogeneous noise. Using the large deviations theory, we characterize the asymptotically optimal allocation rule by maximizing the rate at which the probability of false selection tends to zero. Numerical experiments demonstrate that our approach dramatically improves the selection efficiency by 50%–90% on some typical selection examples compared with the existing approaches. Note to Practitioners—Simulation is widely used for designing and analyzing complex discrete-event systems such as manufacturing production systems, transportation systems, and supply chain operations. However, efficiency is still a significant concern when using simulation for stochastic optimization problems, especially in the presence of stochastic constraints. This paper was motivated by the problem of selecting the best feasible design (solution) from a finite set of alternatives given anobjective and stochastic constraints, where the performances of the objective and constraint measures can be estimated via simulation. Different from the existing approaches in the literature, in this paper, we propose a new R&S procedure using regression metamodels. Given a fixed amount of computing budget, our approach determines the asymptotic optimal number of simulation replications for each design. It can be shown through numerical experiments that the proposed approach can significantly improve the selection efficiency by more than 50% over the existing methods on some typical benchmark examples. [ABSTRACT FROM AUTHOR]

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

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

For distributed discrete-event systems (DESs), which are specified by a set of coupled automata, the centralized synthesis for a composed plant model is often undesired due to a high computational effort and the need to subsequently split the result into local controllers. This paper proposes modeling and synthesis procedures to obtain optimal decentralized controllers in state-feedback form for distributed DES. In particular, this paper addresses the DES with priority structures, in which subsystems with high priorities are supplied with the output of subsystems with lower priority. If the subsystem dependencies have linear or treelike structures, the synthesis of the subsystem controllers can be accomplished separately. Any local controller is computed by algebraic computations, it communicates with controllers of adjacent subsystems, and it aims at transferring the corresponding subsystem into goal states with a minimal sum of transfer costs. As is shown for an example, the computational effort can be significantly reduced compared with the synthesis of centralized controllers following the composition of all subsystem models. [ABSTRACT FROM AUTHOR]

This paper is devoted to the further development of a numerical model for the simulation of high-current vacuum arcs (HCVA) with cathode attachment in the form of multiple cathode spots. The model allows one to simulate different modes of HCVA and the transition between them. It is shown that the secondary plasma, arising from the anodic sputtering and nonadherence of the incident ions, affects the constriction of the plasma and the transition between the HCVA modes. [ABSTRACT FROM AUTHOR]

Analyzing the timing properties of asynchronous systems is essential for characterizing their performance and power. Previous work on timing showed that such systems under and-causality and fixed delay exhibit periodicity properties. We give a different graph-based rigorous proof of the exact timing behavior of more general classes of such systems, and conclude their exact periodicity property, where each of the signal transition will occur with the same period after finite occurrences. We established our results under weaker assumption about system connectivity/topology, and this paper provides the theoretical foundation, for the exact periodicity property to be applied and exploited in circuits containing a combination of synchronous and asynchronous components. We provide simulation-based results for several typical asynchronous circuit topologies to quantify this time period in practical circuits. We also provide an extension of our analysis and methods to the case of bounded delay systems. A key result that is a consequence of our analysis is that asynchronous circuits can be integrated with synchronous logic via a metastability-free interface, thereby eliminating the high-overhead synchronizers when an asynchronous circuit is fully surrounded by synchronous logic. [ABSTRACT FROM PUBLISHER]

The interest in the use of atmospheric-pressure plasma jets (APPJs) is constantly growing. APPJs offer various ranges for applications, such as wound healing, cancer treatment, and dental care. The complex plasma chemistry plays an important role in each of these fields but is often poorly understood. In this paper, the production of atomic oxygen in a radio frequency helium–oxygen plasma is investigated by means of a numerical simulation. A 1-D discharge of an atmospheric-pressure plasma jet is created with the plasma module of COMSOL Multiphysics, using a set of 25 reactions. Many 1-D simulations usually cannot estimate the power deposition in a correct way because of suspected arising losses, such as radiation and inefficiencies of the external circuit. In order to match the experimental power deposition of 13 W, high voltages (855 V) are required in the model. Such high voltages cause changes in the plasma characteristics like a switch in the glow mode. The impact of the voltage on the plasma is investigated by the comparison of a low-voltage (325 V) simulation, which matches the experimental oxygen production, and a high-voltage (855 V) simulation, which matches the experimental power deposition. Outcomes of this paper further support the idea that the power deposition measured in experiments is higher than the actual power deposition coupled to the plasma. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMC) are presently the converter topology of choice for voltage-source converter high-voltage direct-current (VSC-HVDC) transmission schemes due to their very high efficiency. These converters are complex, yet fast and detailed electromagnetic transients simulation models are necessary for the research and development of these transmission schemes. Excellent work has been done in this area, though little objective comparison of the models proposed has yet been undertaken. This paper compares for the first time, the three leading techniques for producing detailed MMC VSC-HVDC models in terms of their accuracy and simulation speed for several typical simulation cases. In addition, an improved model is proposed which further improves the computational efficiency of one method. This paper concludes by presenting evidence-based recommendations for which detailed models are most suitable for which particular studies. [ABSTRACT FROM AUTHOR]

Accurate modeling of soft- and hard-magnetic materials for the numerical simulation of rotating electrical machines is required to allow predictions on the operational characteristics along the torque–speed map, already in the design stage. The full potential of most appropriate material selection and concurrent geometry adaption can only be utilized if models can represent actual material behavior. The accurate prediction of iron losses of soft-magnetic materials for various frequencies and magnetic flux densities, as well as the degradation due to manufacturing is eminent for the design of electrical machines. Therefore, advanced material models need to be adapted and their accuracy examined to further improve the modeling and enable progression. This paper will give an overview of the current modeling approaches applied at the Institute of Electrical Machines for soft- and hard-magnetic materials in the simulation of rotating electrical machines. A case example in the form of a traction drive is presented to which the models are applied. For the machine modeling, the inhouse solver pyMOOSE is utilized. In order to determine the losses with regard to manufacturing processes, the iron-loss model with material degradation is used in combination with a machine simulation scheme of the entire operating range of the machine. Here, various simulation approaches are combined to form the entire computational toolchain to obtain accurate results in the entire operational range. [ABSTRACT FROM AUTHOR]

The fourteen papers in this special section provides an overview of some of the leading current research themes in validation of computational electromagnetics. Over the last two decades, the power of affordable computing has dramatically increased. In addition to computational horsepower, the capabilities of available electromagnetic simulation packages have improved. Hence, there has been a significant increase in the reliance on numerical modeling in electromagnetic compatibility and signal integrity design and analysis. Such increased reliance makes it vital to be able to demonstrate that the models provide a reasonable simulation of the system being modeled. In 2008, the IEEE Standard 1597.1 was published that provided the first ever approach to formalized validation of computer modeling. Since that time, there has been an increase in interest in validation and more research on the methods and applications of formalized validation. [ABSTRACT FROM PUBLISHER]

For many real-world optimization problems, evaluating a solution involves running a computationally expensive simulation model. This makes it challenging to use evolutionary algorithms that usually have to evaluate thousands of solutions before converging. On the other hand, in many cases, even a prematurely stopped run of the simulation may serve as a cheaper, albeit less accurate (low fidelity), estimate of the true fitness value. For evolutionary optimization, this opens up the opportunity to decide about the simulation run length for each individual. In this paper, we propose a mechanism that is capable of learning the appropriate simulation run length for each solution. To test our approach, we propose two new benchmark problems, one simple artificial benchmark function and one benchmark based on a computational fluid dynamics (CFDs) simulation scenario to design a toy submarine. As we demonstrate, our proposed algorithm finds good solutions much more quickly than always using the full CFDs simulation and provides much better solution quality than a strategy of progressively increasing the fidelity level over the course of optimization. [ABSTRACT FROM PUBLISHER]

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]

Efficient performance modeling of today’s analog and mixed-signal circuits is an important yet challenging task, due to the high-dimensional variation space and expensive circuit simulation. In this paper, we propose a novel performance modeling algorithm that is referred to as Bayesian model fusion (BMF) to address this challenge. The key idea of BMF is to borrow the information collected from an early stage (e.g., schematic level) to facilitate efficient performance modeling at a late stage (e.g., post layout). Such a goal is achieved by statistically modeling the performance correlation between early and late stages through Bayesian inference. Furthermore, to make the proposed BMF method of practical utility, four implementation issues, including: 1) prior mapping; 2) missing prior knowledge; 3) fast solver; and 4) prior and hyper-parameter selection, are carefully considered in this paper. Two circuit examples designed in a commercial 32 nm CMOS silicon on insulator process demonstrate that the proposed BMF method achieves up to $9\times $ runtime speed-up over the traditional modeling technique without surrendering any accuracy. [ABSTRACT FROM AUTHOR]

Traditional 3D model-based bas-relief modeling methods are often limited to model-dependent and monotonic relief styles. This paper presents a novel method for digital bas-relief modeling with intuitive style control. Given a composite normal image, the problem discussed in this paper involves generating a discontinuity-free depth field with high compression of depth data while preserving or even enhancing fine details. In our framework, several layers of normal images are composed into a single normal image. The original normal image on each layer is usually generated from 3D models or through other techniques as described in this paper. The bas-relief style is controlled by choosing a parameter and setting a targeted height for them. Bas-relief modeling and stylization are achieved simultaneously by solving a sparse linear system. Different from previous work, our method can be used to freely design bas-reliefs in normal image space instead of in object space, which makes it possible to use any popular image editing tools for bas-relief modeling. Experiments with a wide range of 3D models and scenes show that our method can effectively generate digital bas-reliefs. [ABSTRACT FROM AUTHOR]

In this paper, novel models for electronically coupled distributed energy resources (ECDERs) for online fault calculations of large-scale systems are proposed. ECDERs have different fault responses than traditional synchronous and induction (AC) machines, and generally accepted models for these emerging DERs do not exist. The deployment of ECDERs is constantly increasing worldwide and there is an urgent need for developing appropriate models for fault calculations. In order to have fast calculations, applicable to large-scale systems, the dynamic behavior of traditional AC machines have been approximated in three steady state time-periods (sub-transient, transient, and steady-state). Accordingly, the online fault calculations of large-scale systems have been conducted for these three periods. To simulate the ECDERs’ dynamic behavior, and develop models that are compliant with traditional fault calculations, fault models of ECDERs in the sub-transient, transient, and steady-state periods are proposed, with a short peak current period included in the proposed models during the sub-transient period. To validate the proposed models, they are integrated into recently developed online fault calculations, and tested on various large-scale systems. Results from computer simulations are compared with results obtained using state-of-the-art laboratory equipment, as well as with relevant reports on fault current contributions of ECDERs. The results match very well, further validating the proposed models. [ABSTRACT FROM AUTHOR]

This paper presents several methods for motivating students taking a power system protection (PSP) course. The paper reviews the laboratory activities developed for the PSP course at Curtin University, Australia; these methods are applicable and can be used for PSP course instruction at any institution. These activities were developed to improve the learning experience of the electrical engineering undergraduate and postgraduate students enrolled in this course. Initially, the PSP course at Curtin University consisted of lectures and tutorials accompanied by two sessions of software-based simulations and one session of laboratory demonstration. To motivate the students, several computer-based simulations and practical laboratory experiments were developed. PSCAD and ETAP power system analysis software tools are introduced and used to demonstrate the performance and coordination of different protection relays from steady-state and dynamic points of view. Also, a practical setup composed of a LabVolt power system simulator and industrial relays is used to carry out several practical experiments. The experiments help students observe the performance of protection systems for transformers and induction motors during faults and abnormal operating conditions. Finally, the concept of relay testing and commissioning is introduced by relay standalone experiments using a secondary injection relay test set. The results of these activities were evaluated according to the students’ satisfaction, comments, total scores, and interest in PSP. [ABSTRACT FROM PUBLISHER]

The term “In Silico Trial” indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative. [ABSTRACT FROM AUTHOR]

This paper addresses an NP-hard problem, refered to as Network Topology Design with minimum Cost subject to a Reliability constraint (NTD-CR), to design a minimal-cost communication network topology that satisfies a pre-defined reliability constraint. The paper describes a dynamic programming (DP) scheme to solve the NTD-CR problem, and proposes a DP approach, called Dynamic Programming Algorithm to solve NTD-CR (DPCR-ST), to generate the topology using a selected sequence of spanning trees of the network, STXmin. The paper shows that our DPCR-ST approach always provides a feasible solution, and produces an optimal topology given an optimal order of spanning trees. The paper proves that the problem of optimally ordering the spanning trees is NP-complete, and proposes three greedy heuristics to generate and order only k spanning trees of the network. Each heuristic allows the DPCR-ST approach to generate STXmin using only k spanning trees, which improves the time complexity while producing a near optimal topology. Simulations based on fully connected networks that contain up to 2.3\times 10^9 spanning trees show the merits of using the ordering methods and the effectiveness of our algorithm vis-à-vis to four existing state-of-the-art techniques. Our DPCR-ST approach is able to generate 81.5% optimal results, while using only 0.77% of the spanning trees contained in networks. Further, for a typical 2\,\times\,100 grid network that contains up to 1.899^102 spanning trees, DPCR-ST approach requires only k=1214 spanning trees to generate a topology with a reliability no larger than 5.05% off from optimal. [ABSTRACT FROM PUBLISHER]

An effective computational tool for the simulation and design of voltage dividers has been realized. It takes advantage of a finite-element procedure for the accurate computation of the divider stray capacitances. These latter are then the input of a circuit solver procedure based on the modified node potential technique, which provides the divider frequency response. Furthermore, a test divider has been set up for the purpose of the tool validation. A very good agreement has been found between measured and computed results. This paper highlights that a correct representation of the resistors is necessary in the finite-element method (FEM) model, during the computation of the stray parameters. This issue has been clarified for the first time in this paper. In addition, a comparison between the FEM and boundary-element method has been carried out before the implementation of the numerical code, stating the superior effectiveness of FEM. The computational tool has been finally tested on a real voltage divider. Good results have been found in terms of computational accuracy. Limited discrepancies between measured and computed results have been found up to 10 kHz, with 5.7% for the scale factor and less than 24 mrad for the phase error. [ABSTRACT FROM PUBLISHER]

Computer science (CS) is becoming an increasingly diverse domain. This paper reports on an initiative designed to introduce underrepresented populations to computing using an eclectic, multifaceted approach. As part of a yearlong computing course, students engage in Maker activities, participatory simulations, and computing projects that foreground the social and collaborative aspects of CS. Collectively, these activities are designed to introduce learners to the growing diversity of what CS looks like in the 21st century. This paper lays out the practical and theoretical motivations for the Computational Thinking for Girls (CT4G) project, specifically highlighting the use of Making through physical and social computing as ways to engage students in CS. A snapshot of one activity from the program is provided—Wearing the Web—in which students use open-hardware programmable badges to explore the underlying structure and technology that enables the Internet. Data from the first year of the CT4G program are presented to show the positive effects that this diverse introduction to CS is having on the students with respect to their attitudes toward CS. [ABSTRACT FROM PUBLISHER]

This paper proposes to use deep reinforcement learning for the simulation of physics-based musculoskeletal models of both healthy subjects and transfemoral prostheses’ users during normal level-ground walking. The deep reinforcement learning algorithm is based on the proximal policy optimization approach in combination with imitation learning to guarantee a natural walking gait while reducing the computational time of the training. Firstly, the optimization algorithm is implemented for the OpenSim model of a healthy subject and validated with experimental data from a public data-set. Afterwards, the optimization algorithm is implemented for the OpenSim model of a generic transfemoral prosthesis’ user, which has been obtained by reducing the number of muscles around the knee and ankle joints and, specifically, by keeping only the uniarticular ones. The model of the transfemoral prosthesis’ user shows a stable gait, with a forward dynamic comparable to the healthy subject’s, yet using higher muscles’ forces. Even though the computed muscles’ forces could not be directly used as control inputs for muscle-like linear actuators due to their pattern, this study paves the way for using deep reinforcement learning for the design of the control architecture of transfemoral prostheses. [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]

The High Efficiency International Klystron Activity (HEIKA) was initiated at CERN in 2014 to evaluate and develop new klystron bunching technologies for high-efficiency klystrons in application to the large-scale scientific projects such as the Compact Linear Collider (CLIC) and the Future Circular Collider (FCC). The success of such development strongly depends on the availability of the specialized klystron computer codes. Unfortunately, the accurate and efficient 2-D large-signal codes are proprietary and are not freely available to the wide klystron community. The new 1.5-D klystron code called KlyC has been developed as an attempt to bridge the gap between fast, but approximate 1-D models and time/resources consuming particle-in-cell (PIC) codes. KlyC simulates the specific physical processes such as the current emission from the metal surface, the space charge depression along the klystron, and the residual RF current modulation of the spent beam. KlyC internal eigenmode solver allows fast simulations of the 2-D complex electromagnetic (EM) field in the axis-symmetrical cavity with the arbitrary cavity profile. The internal KlyC optimizer module can help the designer to speed up the klystron development process. In this paper, the theoretical model, general review of the code performance, and benchmarking between KlyC, AJDisk/1-D, PIC code MAGIC/2-D, and CST/3-D are presented using FCC klystrons as an example. [ABSTRACT FROM AUTHOR]

A multiscale modeling platform that supports the “virtual” qualification of commercial-off-the-shelf parts is presented. The multiscale approach is divided into two modules. The first module generates information related to the bipolar junction transistor gain degradation that is a function of fabrication process, operational, and environmental inputs. The second uses this information as inputs for radiation-enabled circuit simulations. The prototype platform described in this paper estimates the total ionizing dose and dose rate responses of linear bipolar integrated circuits for different families of components. The simulation and experimental results show good correlation and suggest this platform to be a complementary tool within the radiation-hardness assurance flow. The platform may reduce some of the costly reliance on testing for all systems. [ABSTRACT FROM AUTHOR]

This paper presents the results of predictive calculations of the parameters of pulses of soft X-ray radiation (SXR) on a four-module electrophysical facility GAMMA-4 (the current pulse amplitude is ~3 MA with rise time of ~60 ns) that has been constructed in Russia. Scaling numerical simulation of implosion of a cylindrical single and nested multiwire array in 0-D, 2-D, and 3-D radiation magnetohydrodynamic– approximations is performed, taking into account, the updated double-loop equivalent electrical circuit of the GAMMA-4. The main purpose of the conducted studies was the numerical optimization of the multiwire array parameters to obtain the best characteristics of the SXR pulse generated as a result of Z-pinch implosion on the axis of the system. [ABSTRACT FROM AUTHOR]

How accurately can one estimate a deterministic parameter subject to other unknown deterministic model nuisance parameters? The most popular answer to this question is given by the Cramér–Rao bound (CRB). The main assumption behind the derivation of the CRB is local unbiased estimation of all model parameters. The foundations of this paper rely on doubting this assumption. Generally, in multivariate parameter estimation, each parameter in its turn can be treated as a single parameter of interest, whereas the other model parameters are treated as nuisance, as their misknowledge interferes with the estimation of the parameter of interest. This approach is utilized in this paper to provide a fresh look at deterministic parameter estimation. A new Cramér–Rao (CR) type bound is derived without assuming unbiased estimation of the nuisance parameters. Rather than that, we apply Lehmann's concept of unbiasedness for a risk that measures the distance between the estimator and the locally best unbiased estimator, which assumes perfect knowledge of the nuisance parameters. The proposed risk-unbiased CRB (RUCRB) is proven to be asymptotically attainable by the maximum likelihood estimator while being tighter than the conventional CRB. Furthermore, simulations verify the asymptotic achievability of the RUCRB by the maximum likelihood estimator for an array processing problem. [ABSTRACT FROM AUTHOR]

In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the $m$ -waypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds’ rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, the model predictive current control is introduced in the semicontrolled open-winding permanent magnet synchronous motor (OW-PMSM) generation system with a common dc bus to suppress the zero-sequence current for the first time. Particularly, the basic voltage vectors of the semicontrolled OW-PMSM, which are synthesized by the three-phase full-controlled converter and the three-phase uncontrollable diode bridge, is analyzed and their influences on the zero-sequence current are investigated for the first time in this paper. Then the current-error-based cost function that includes dq-axis current error and zero-sequence current error is designed to evaluate all the voltage vectors. Moreover, to further improve the steady-state control performance of the whole generation system, a zero-sequence current suppression method based on the uncontrollable side voltage vector adjustment, which has the advantage of low computation burden, is developed. In this method, two voltage vectors of the controllable converter are applied during one control period. Based on the distribution character of the basic voltage vector in the semicontrollable OW-PMSM generation system, the first voltage vector is selected according to the three-phase current direction to adjust equivalent vector of the uncontrollable diode bridge, whereas for the second voltage vector, the selection method based deadbeat voltage vector sector is designed to reduce the range of the candidate voltage vector. In addition, the vector durations are also computed. Finally, simulation and experiment are carried out to validate the proposed control approaches. [ABSTRACT FROM PUBLISHER]

This paper presents the results of a comparative analysis among three methods for attributing responsibilities of voltage unbalance in the electrical network, namely, the IEC, three-phase power flow, and conforming and nonconforming currents methods. To do this, computational and experimental simulations are carried out based on employing a system comprised of a perfectly transposed transmission line and two loads that are not always balanced. The cases selected for this study also permit the identification of the main advantages and disadvantages of each method under evaluation. This work is characterized as a topic of great interest to the regulatory agencies responsible for establishing regulations, and for utilities and consumers. It is relevant because by using the methods investigated in this paper, the identification of the sources, which generates unbalance, the division of responsibilities, and the application of penalties due to limit transgression will be possible. [ABSTRACT FROM AUTHOR]

This paper presents a modified method for power system transient stability analysis, allowing the reduction of the computational requirements while retaining important system dynamics. The approach formulates the power balance equations depending on the area of interest. The detailed ac model, including full real and reactive power equations, is used for the area in which high accuracy is required, while the simpler dc model, including linear real power equation, is used for more remote areas where real power dynamics dominate. A high level of accuracy can be achieved using the ac model in the area of interest, and computational complexity can be reduced with the less detailed dc model in the remainder of the system. In order to prevent the loss of simulation accuracy, this paper proposes a way to compensate line losses neglected using the dc model. Case studies with the IEEE 118-bus system are provided to validate the performance of the proposed method. [ABSTRACT FROM PUBLISHER]

Compact modeling of phase-locked loop (PLL) frequency synthesizer is proposed to reduce transient phase noise and jitter simulation time. Conventional small-signal noise assumption based frequency-domain simulation approach produces inaccurate results for nonlinear PLLs. Accurate analysis of nonlinear PLL are possible through time-domain, or transient noise simulation but time-domain simulation is computation-intensive and time-consuming. This paper presents a practical solution for transient phase noise and jitter analysis using compact modeling techniques. It features an autoregressive moving average process modeled voltage-controlled oscillator with fractional calculus and wavelet transform for phase noise decomposition and reconstruction, thereby reducing the phase noise and jitter simulation time to 25.8% of the transistor-level simulation with 0.4 dB @ 1 MHz phase noise error and 0.3 ps long-term jitter error for a 2 GHz PLL frequency synthesizer in a 65 nm CMOS process. [ABSTRACT FROM PUBLISHER]

This paper describes a new model for a set of test sequences where a set $S$ is described by a single functional test sequence $T$ . Using this model, a procedure that compacts $T$ compacts all the sequences in $S$ simultaneously. This enhances the ability of the procedure to compact the set compared with procedures that consider the sequences in the set individually. It also allows the test sequences in $S$ to be redefined. If different sequences in $S$ have substantially different lengths, repartitioning $T$ allows new sequences with more uniform lengths to be obtained. After repartitioning, additional test compaction can be achieved. This paper describes a test compaction procedure that includes these operations based on the modeling of a set as a single sequence. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a k-out-of-n load-sharing system with n identical components sharing a certain amount of load. Each time a component fails, its load is distributed to the remaining components; we assume an increase in load increases the hazard rates of the remaining components. The system is periodically inspected to detect failed components. Two cases may occur in an inspection interval: if the number of failed components is less than n-k+1, then the failed components are only rectified at periodic inspections; if the number of failures reaches n-k+1, then the system fails, and at this time, all the failed components are inspected and rectified. A failed component is replaced or minimally repaired according to a probability which depends on its age at the failure time. The components' failures follow a Non-Homogenous Poisson Process (NHPP), and their intensity functions depend on their ages and the loads to which they are exposed at any moment. In this paper, we develop a model to find the optimal inspection interval for such a system, which minimizes the total expected cost incurred over the system lifecycle. We derive the analytical solution for the special case of a 1-out-of-2 system, and discuss its computational difficulties. We then present a simulation algorithm to find the required expected values in the objective function. Several numerical examples are presented to illustrate the proposed model. [ABSTRACT FROM AUTHOR]

The investigation of the performance of different positron emission tomography (PET) reconstruction and motion compensation methods requires accurate and realistic representation of the anatomy and motion trajectories as observed in real subjects during acquisitions. The generation of well-controlled clinical datasets is difficult due to the many different clinical protocols, scanner specifications, patient sizes, and physiological variations. Alternatively, computational phantoms can be used to generate large data sets for different disease states, providing a ground truth. Several studies use registration of dynamic images to derive voxel deformations to create moving computational phantoms. These phantoms together with simulation software generate raw data. This paper proposes a method for the synthesis of dynamic PET data using a fast analytic method. This is achieved by incorporating realistic models of respiratory motion into a numerical phantom to generate datasets with continuous and variable motion with magnetic resonance imaging (MRI)-derived motion modeling and high resolution MRI images. In this paper, data sets for two different clinical traces are presented, 18F-FDG and 68Ga-PSMA. This approach incorporates realistic models of respiratory motion to generate temporally and spatially correlated MRI and PET data sets, as those expected to be obtained from simultaneous PET–MRI acquisitions. [ABSTRACT FROM PUBLISHER]

This paper presents a dielectric simulation approach for predicting withstand voltage of air insulated power devices. The paper gives an overview of typical evaluation procedures for the basic discharge stages including inception, streamer propagation and leader transition. For selected test arrangements, we compare the results of lightning impulse tests with simulations. The simulations utilize a new approach that combines the well-established empirical procedure with numerical computations for arbitrary geometries. We introduce a new formulation for evaluation of saturation charge density, which enables a revision of the streamer inception conditions due to surface charging and an estimation of the leader transition characteristics including the surface capacitance. [ABSTRACT FROM PUBLISHER]

Simulated ultrasound data is a valuable tool for development and validation of quantitative image analysis methods in echocardiography. Unfortunately, simulation time can become prohibitive for phantoms consisting of a large number of point scatterers. The COLE algorithm by Gao et al. is a fast convolution-based simulator that trades simulation accuracy for improved speed. We present highly efficient parallelized CPU and GPU implementations of the COLE algorithm with an emphasis on dynamic simulations involving moving point scatterers. We argue that it is crucial to minimize the amount of data transfers from the CPU to achieve good performance on the GPU. We achieve this by storing the complete trajectories of the dynamic point scatterers as spline curves in the GPU memory. This leads to good efficiency when simulating sequences consisting of a large number of frames, such as B-mode and tissue Doppler data for a full cardiac cycle. In addition, we propose a phase-based subsample delay technique that efficiently eliminates flickering artifacts seen in B-mode sequences when COLE is used without enough temporal oversampling. To assess the performance, we used a laptop computer and a desktop computer, each equipped with a multicore Intel CPU and an NVIDIA GPU. Running the simulator on a high-end TITAN X GPU, we observed two orders of magnitude speedup compared to the parallel CPU version, three orders of magnitude speedup compared to simulation times reported by Gao et al. in their paper on COLE, and a speedup of 27000 times compared to the multithreaded version of Field II, using numbers reported in a paper by Jensen. We hope that by releasing the simulator as an open-source project we will encourage its use and further development. [ABSTRACT FROM AUTHOR]

Power system loads are one of the crucial elements of modern power systems and, as such, must be properly modelled in stability studies. However, the static and dynamic characteristics of a load are commonly unknown, extremely nonlinear, and are usually time varying. Consequently, a measurement-based approach for determining the load characteristics would offer a significant advantage since it could update the parameters of load models directly from the available system measurements. For this purpose and in order to accurately determine load model parameters, a suitable parameter estimation method must be applied. The conventional approach to this problem favors the use of standard nonlinear estimators or artificial intelligence (AI)-based methods. In this paper, a new solution for determining the unknown load model parameters is proposed—an improved particle swarm optimization (IPSO) method. The proposed method is an AI-type technique similar to the commonly used genetic algorithms (GAs) and is shown to provide a promising alternative. This paper presents a performance comparison of IPSO and GA using computer simulations and measured data obtained from realistic laboratory experiments. [ABSTRACT FROM AUTHOR]

Critical infrastructure (CI) modeling and analysis is a very challenging research topic. One of the most pressing issues is to find an effective representation for addressing the system vulnerabilities caused by interdependencies, which, if exploited, could result in nontrivial accident scenarios. Until now, this question has been tackled for different sector-specific infrastructures (electricity grid, telecommunications networks, supply chains, etc.), and very few generalizable analysis tools have been developed. However, all CI share some features that can be leveraged in order to build a common modeling framework. This paper identifies these common features, which it exploits to develop a modeling language: the infrastructure resilience-oriented modeling language (I $ \circledR $ ML). I $ \circledR $ ML is designed to facilitate the analysis of operational interdependencies among the infrastructure components and overall resilience, i.e., the ability of the infrastructure to withstand and recover under off-nominal (anomalous) conditions. A number of examples are used to illustrate the modeling concepts and highlight the analytical capability of I $ \circledR $ ML. [ABSTRACT FROM AUTHOR]

Stalling of residential air conditioners (RACs) following a transient fault can delay the voltage recovery ranging from 3 to 20 seconds. This phenomenon is referred to as fault-induced delayed voltage recovery (FIDVR). Several aggregated RAC models have been presented to replicate the actual FIDVR events. However, they usually have two main drawbacks as: i) considering independent stalling voltage and stalling time for all RACs, ii) resulting in only two ultimate modes; either 100% stalled or 100% normal running. This paper amends the abovementioned shortcomings by proposing a simple and effective performance-based RAC model. The proposed model utilizes a simple explicit relation between the stalling voltage and its required time to stall the RAC, furthermore, it can stall a fraction of RACs based on the voltage dip characteristics. The experimental results support the proposed model and computer simulations employing the IEEE 118-bus test system and Iran's electricity grid reveal the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research communities might not be appropriate. In this paper we propose a theoretical framing for assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models. [ABSTRACT FROM AUTHOR]

Active cell balancing improves the performance of a battery pack by transferring charge from one cell to another. Associated design questions require multiple simulations with 100 cells over several hours. Since the most efficient transfer methods switch between phases in the kilohertz range, these simulations require high computational effort or reduced accuracy. To enable detailed analysis on a large scale, this paper includes state-of-the-art electrical battery models in active balancing simulation while keeping the computation effort for one transfer in the low millisecond range. This is achieved in three steps. First, we model the dynamics of each transfer phase using standard equivalent circuit abstraction. Next, we find closed form equations for the so-defined phase dynamics, yielding an iterative approach that saves computation time by replacing the numerical solver. Finally, we employ error control techniques to aggregate phases in that iteration, systematically reducing the millions of phase evaluations that would be necessary otherwise. Our experiments show that the speedup from equivalent circuit dynamics to error-controlled aggregation almost reaches five orders of magnitude while introducing virtually no additional error. This enables simulations of realistic balancing scenarios in less than a second and is hence suitable for design space exploration. [ABSTRACT FROM PUBLISHER]

With ever increasing design complexities, traditional cycle-accurate or instruction-set simulations are often too slow or too inaccurate for system prototyping in early design stages. As an alternative, host-compiled or source-level software simulation has been proposed, but existing approaches have largely focused on timing simulation only. In this paper, we propose a novel source-level simulation infrastructure that provides a full range of performance, energy, reliability, power and thermal (PERPT) estimation. Using a fully automated, retargetable back-annotation framework, intermediate representation code is statically annotated with timing, energy and resource accesses information obtained from low-level references at basic block granularity. The annotated model is natively compiled and combined with a cache model and occupancy analyzer to provide target performance, energy, soft-error vulnerability and power estimations. Finally, generated power traces are fed into thermal models for further temperature estimation. Comprehensive evaluations of our source-level models for PERPT estimations are performed. We applied our approach to PowerPC targets running various industry benchmark suites. source-level simulations are evaluated for different PERPT metrics and with cache models at various levels of detail to explore the speed and accuracy tradeoffs. More than 90% accuracy can be achieved for timing, energy, reliability and power estimation, and an average error of 0.05 K exists in steady-state thermal estimation. Simulation speeds range from 180 to 5740 MIPS for different types of metrics at different abstraction levels. [ABSTRACT FROM AUTHOR]

This is Part II of a series of two papers where we address sequential estimation of wide-sense stationary autoregressive moving average (ARMA) state processes by particle filtering. In Part I, we considered a state-space model where the state was an ARMA process of known order and where the parameters of the process could be known or unknown. In this paper, we extend our work from Part I by considering the same type of models, with the added complexity that the ARMA processes are now of unknown order. Instead of working on a scheme that first tracks the state by operating with different assumed models, and then selects the best model by using a predefined criterion, we present a method that directly estimates the state without the need of knowing the model order. We derive the transition density of the state for unknown ARMA model order, and propose a particle filter based on that density and the empirical Bayesian methodology. We demonstrate the performance of the proposed method with computer simulations and compare it with the methods from Part I. [ABSTRACT FROM PUBLISHER]

Protocol sequences have recently been studied in collision channels without feedback for dynamic multiple-access mobile applications, such as wireless sensor and vehicular ad hoc networks. In this paper, a method of systematically adding mark chips into some families of prime sequences for the construction of protocol sequences with adjustable duty factors is investigated. Not relying on computer simulation only, new theoretical models of throughput and its variance are formulated to analyze the sequence performance by means of average hit probabilities. Numerical studies and computer simulations are performed to validate the new analytical models. With adjustable duty factors, these protocol sequences support flexible exchange between throughput and the number of active users. [ABSTRACT FROM PUBLISHER]

In this paper, the principles of finite-element modeling for the electroacoustic simulation of bulk-acoustic-wave devices will be summarized. We will outline the model setup including governing equations and boundary conditions, as well as its efficient computer implementation. Particular emphasis will be given to tailoring the model dimension to the specific requirements of the desired investigation. As 3-D simulations still require a major effort, it will be illustrated that various aspects of device physics and design can already be addressed by fast and efficient 2-D simulations. Multiple theoretical and experimental evidence will be presented to demonstrate the validity of the modeling concepts. Based on various examples, it will be sketched how to benefit from numerical simulations for understanding fundamental effects, designing devices for actual products, and exploring novel technologies. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) have become the converter topology of choice for voltage-source converter–high-voltage direct-current systems. Excellent work has previously been conducted to develop much needed average value models (AVM) for these complex converters; however, there a number of limitations as highlighted in this paper. This paper builds on the existing models, proposing numerous modifications and resulting in an enhanced MMC-AVM, which is significantly more accurate and which can be used for a wider range of studies, including DC faults. [ABSTRACT FROM PUBLISHER]

In this paper, we propose the use of a p+ core in the core–shell nanowire (CS NW) architecture to significantly reduce the gate induced drain leakage and therefore, increase the ON-state to OFF-state current ratio ( $I_{{\mathrm{\scriptscriptstyle ON}}}/I_{{\mathrm{\scriptscriptstyle OFF}}}$ ) in n-NW junctionless FETs (NWJLFETs). We show that the lateral band-to-band tunneling induced parasitic bipolar junction transistor action is diminished in the CSJLFET due to an enhanced tunneling width and a higher source to channel barrier height. Further, we also demonstrate that the p+ core helps to realize efficient volume depletion in NWJLFETs with large NW width. Using calibrated 3-D simulations, we show that the CSJLFET exhibits a significantly high ON-state to OFF-state current ratio ( $I_{{\mathrm{\scriptscriptstyle ON}}}/I_{{\mathrm{\scriptscriptstyle OFF}}}$ ) of \sim 10^{7} even for a channel length of 7 nm. [ABSTRACT FROM AUTHOR]

Loewner matrix (LM) interpolation-based macromodeling methods can generate an accurate macromodel for large and complex structures. However, there is less flexibility in the choice of the macromodel order due to the need to ensure passivity. In this paper, an algorithm is proposed to obtain a reduced order model based on LM interpolation while still maintaining the passivity of the macromodel. This is achieved by first relaxing the passivity requirement during the order selection process; then a new passivity enforcement scheme with significantly improved speed and convergence properties is applied. The proposed approach results in a significantly reduced macromodel size while maintaining accuracy and passivity conditions. The efficiency of the new approach is shown in the examples. [ABSTRACT FROM PUBLISHER]

This paper conducts a probabilistic assessment of the dynamic primary frequency response characteristic (the PFRC is also known as $\beta$ in practice) for thermal unit. The PFRC is time-varying as it is sensitive to the steam pressure and valve opening that naturally vary with the generator loading. To depict the dynamic PFRC in a probabilistic manner, an analytical expression of the PFRC is first derived by establishing a low-order primary frequency response model that considers heat storage dynamic. Based on which, the point estimate method that is capable of managing the correlation is adopted to portray the probabilistic features of time-varying PFRC for thermal unit. Numerical simulations are presented to validate the proposed low-order primary frequency response model and different solutions are applied for the probabilistic assessment of the PFRC, where the obtained results show that the proposed point estimate method can achieve satisfactory performance owing to its accuracy and efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient method for extracting the coupling capacitance between through-silicon via (TSV) and the adjacent redistribution layer (RDL) interconnections based on the scalar potential integral equation and cylindrical accumulation mode basis functions. As the numerical integration of capacitance is very complicated, we employed an approximation based on the use of double-exponent transformation and the segmentation method to improve the calculation efficiency. The maximum deviation is less than 5%. The scalability of the proposed model is verified by performing parametric studies on different physical design parameters; the results show good agreement between the proposed model and the numerical simulation. Additionally, we studied several different structures of TSVs with and without RDLs to explain the influence of the coupling capacitance between TSVs and RDLs on crosstalk noise. [ABSTRACT FROM AUTHOR]