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Novel designs of paper-based bandstop frequency-selective surfaces (FSSs) are presented in this article. The characteristics of the paper-based honeycomb structure are investigated first. One folded dipole resonator with first-order bandstop response is analyzed and further printed on the sidewalls of the honeycomb structure accordingly. A second-order response with two cascade FSSs is proposed with controllable bandwidth by the coupling coefficient of the resonators with the aid of the equivalent circuit model. Two paper-based FSS samples were fabricated and measured to demonstrate the validity of the proposed design strategies. Benefiting from the merits of lightweight and strong mechanical properties, the proposed paper-based FSS is a potential candidate for application in radar systems and aircraft. [ABSTRACT FROM AUTHOR]

Due to the increasing size of integrated circuits (ICs), their design and optimization phases (i.e., computer-aided design, CAD) grow increasingly complex. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. At run time, a large configuration space needs to be searched to find the best set of parameters (e.g., voltage/frequency) to further optimize the system. Both spaces are infeasible for exhaustive search typically leading to heuristic optimization algorithms that find some tradeoff between design quality and computational overhead. Machine learning (ML) can build powerful models that have successfully been employed in related domains. In this survey, we categorize how ML may be used and is used for design-time and run-time optimization and exploration strategies of ICs. A metastudy of published techniques unveils areas in CAD that are well explored and underexplored with ML, as well as trends in the employed ML algorithms. We present a comprehensive categorization and summary of the state of the art on ML for CAD. Finally, we summarize the remaining challenges and promising open research directions. [ABSTRACT FROM AUTHOR]

Chemical mechanical planarization (CMP) is vital for ensuring chip fabrication uniformity at nanometer scales. The emergence of a series of phenomenological CMP process models (Stine et al., 1997; Gbondo-Tugbawa, 2002; Xie, 2007; Vasilev, 2011) suggests that the existing model upgrade approach is largely based on a change in phenomenological model assumptions, demanding deep insights into complex process mechanisms and protracted period for accuracy improvements. To tackle this issue, this paper proposes a decoupling regression strategy for model upgrades. This strategy employs a data-driven approach to enhance the coupling relationships within the model, facilitating continuous improvement of simulation accuracy based on the existing model. It is capable of achieving improvements in model accuracy even in scenarios where modelers lack insight into complex process mechanisms. We validate our method by upgrading the Density Step Height (DSH) model to the Extend-DSH model to address poor erosion predictions at the 28nm node. Comparing model predictions with silicon data reveals that the Extend-DSH model aligns better with the measured data, reducing the root mean square error from 159.31Å to 6.89Å and increasing the coefficient of determination from -0.83561 to 0.6058, showcasing the effectiveness of the proposed chip-level CMP model upgrade method grounded in the decoupling regression strategy. [ABSTRACT FROM AUTHOR]

The simulation of electric field transients in HVDC cables can be a fundamental tool to support insulation system design when operation dynamics, which includes voltage polarity inversions and load variation, becomes significant during the expected cable life. The field behavior during voltage and temperature transients is associated with intrinsic and extrinsic ageing processes that can affect the cable design life. Traditional models employed for electric field simulations consider only the non–linear, steady–state dependence of conductivity on temperature and field magnitude, but they neglect the transient behavior of permittivity and conductivity, that is, polarization and charge trapping phenomena. These processes impact on the duration of the field transient and thus ageing. This paper discusses the numerical implementation of an electro–quasistatic model that can be used to perform transient simulations of electric fields in HVDC cables insulation. With respect to the model traditionally employed, the presented one is extended with Debye's equations for dielectric polarization processes. The model is implemented numerically using finite differences, or the Occhini equivalent circuit: this paper demonstrates that the two approaches are equivalent. Numerical simulations show that, during transients, polarization processes slow down the electric field dynamics and reduce its maximum intensity. [ABSTRACT FROM AUTHOR]

The Potential Transformer (PT) plays an important role in the measurement and monitoring of the power system. The accurate modeling of the PT is very important but not yet perfect. The stray capacitance will have a non-negligible effect on the performance of a PT. However, the influence of stray capacitance is rarely considered in existing models, which makes the broadband simulation performance weak and provides limited references in engineering. In this paper, a calculation method of PT stray capacitance is proposed to analyze the performance of the PT at different frequencies and extract the capacitive current of the PT port. This paper used a non-destructive method to obtain the test data of a PT, calculated the value of the stray capacitance, and drew the hysteresis loops of the iron core. A corresponding simulation model was established to predict the PT performance at different frequencies. The simulation results are in good agreement with the experimental data, which proves the accuracy of the modeling parameters. The data processing logic is clear and is easy to be simplified by programming, which makes it promising in engineering. [ABSTRACT FROM AUTHOR]

Cycle time, which is of order of ten weeks for most products in semiconductor wafer fabrication facilities (wafer fabs), must be explicitly considered in production planning models. Cycle times depend nonlinearly on the resource workload in a wafer fab. Different data-driven (DD) production planning formulations are studied in this paper. Such formulations are based on a set of system states representing the congestion behavior of a wafer fab with work in process (WIP) and resulting output levels. Different WIP-output relations in the DD formulations are investigated. In addition, different methods are proposed to gather representative sets of system states. The DD formulations are compared with the Allocated Clearing Function (ACF) formulation with respect to profit and cost values using simulation models of a scaled-down and a large-sized multi-product wafer fab, respectively. The simulation results show that some DD variants are able to outperform the ACF formulation under several experimental conditions. [ABSTRACT FROM AUTHOR]

The growth process of silicon single crystal (SSC) is a typical batch production process, which has the characteristics of batch size, variety, complex process, and intensive technology. In order to accurately control the diameter and thermal field temperature of the Czochralski (Cz) SSC batch production process to ensure that the actual production requirements of electronic-grade SSC are met, this paper proposes an iterative learning-based batch process predictive control strategy Model Predictive Control - Iterative Learning Control - Extended State Observer (MPC-ILC-ESO). The control strategy consists of two parts. The time axis is a dual Model Predictive Control (MPC) controller, which is mainly used to deal with disturbance suppression and constraints in the production process of a single batch of SSC. The iterative axis is the Extended State Observer (ESO) based Iterative Learning Control (ILC) control algorithm to deal with uncertainty and disturbance estimation and compensation in the multi-batch production process. The control effects of the time axis and the batch axis are superimposed as the final controlled object input to ensure the crystal diameter and stable thermal field temperature. Finally, the effectiveness of the proposed control strategy is verified based on the data analysis of the semiconductor industry production process. [ABSTRACT FROM AUTHOR]

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

The risk of unstable subsynchronous oscillations (SSO) in DFIG-based wind parks radially connected to transmission lines with series capacitive compensation is typically assessed with numerous electromagnetic transient (EMT) simulations, which is a time-consuming process. However, not all operating scenarios present risk of SSO and require such a detailed investigation. This paper proposes two charts based on impedance equivalents of wind generators obtained through frequency scans to quickly map which combinations of parameters can create unstable SSOs and which combinations are risk-free. With the information, engineers can immediately filter out scenarios with no risk of instability and conduct detailed studies on fewer scenarios that are truly critical. These charts can be obtained with simple equations that use only information readily available in practice to engineers, without the need to run any computer simulation. The charts also reveal the key operating conditions that can increase the risk of an unstable SSO and provide real-time quantitative insights into how close a wind park is to an instability. Application examples are provided to illustrate how this approach can help engineers speed up studies to identify the risk of SSO. [ABSTRACT FROM AUTHOR]

The penetration of inverter-based resources is growing rapidly around the globe. During a fault, the behavior of inverter-based resource is very different from a traditional synchronous machine based generation. As the penetration of inverter-based resources increases, there is an urgency for the industry to understand their behavior so that these resources can be accurately modeled and their impact on various protection schemes can be studied in detail. This path begins with standardizing the response of inverter-based resources to a fault. Additionally, this paper discusses issues with modeling inverter-based resources in a short circuit model which is developed for systems dominated by synchronous machines and finally a need for further research to understand impacts on traditional protection schemes as inverter-based resources continue to displace traditional generation. This paper does not offer solutions however, it is intended to encourage further study by industry professionals toward development of solutions. [ABSTRACT FROM AUTHOR]

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

The high penetration of renewables has sparked new oscillatory concerns in hybrid AC/DC grids. Knowledge of the oscillation regarding its source and propagation mechanism, is crucial to system operation. In this respect, the frequency-domain modal analysis (FMA) provides a way (e.g., participation factor) to extract these oscillation properties, and has been widely applied in converter-based AC grids. Compared to AC grids, oscillation properties of hybrid AC/DC grids are much more complex. Such complexity mainly originates from the diversity of oscillation propagation behaviors in hybrid AC/DC grids, where a distinctive local-area oscillation will emerge. Therefore, a dedicated oscillation propagation analysis for hybrid AC/DC grids is desired, which is the main focus of this paper. First, the mechanism of the distinctive local-area oscillation is analyzed considering AC/DC coupled dynamics of converters. Then, a systematic method for the oscillation propagation analysis is presented, where indices for characterizing the local-area oscillation and its impact area are established. Finally, some propagation properties are discussed, by which a strategy for the online oscillation source locating is designed. Case studies are carried out in a typical hybrid AC/DC grid to validate the propagation analysis in this paper. [ABSTRACT FROM AUTHOR]

The ongoing digitalization enables stable control processes and smooth operations of Industrial Control Systems (ICSs). A direct consequence of the highly interconnected architecture of ICSs is the introduced cyber vulnerability and increasing cyber security threats to ICSs. Numerous researches pay attention to the security problem of ICSs. However, most current studies face two challenges. First, the interaction problem between the cyber layer and the physical layer of ICSs may result in incorrect attack response strategies. Second, ICSs are real-time systems, but existing defense decision algorithms based on game theory or reinforcement learning techniques have high computational complexity, which prevents them from making decisions quickly. In this paper, we design a new multi-attribute based method for quantifying rewards and propose a multi-attribute based Q-learning algorithm to resolve the interaction problem. In addition, to overcome the limitation of slow convergence, we develop an effective parallel Q-learning (PQL) algorithm to quickly find the optimal strategy. The experimental results show the effectiveness of the PQL algorithm. Compared with the Q-learning algorithm (QL) and the deep Q-network (DQN) algorithm, our proposed solution can reduce the average completion time by 12.5 to 37 percent. [ABSTRACT FROM AUTHOR]

Single-photon avalanche diodes (SPADs) are widely used for weak light detection due to their high gain and high sensitivity. Unfortunately, SPAD devices have random telegraph signal (RTS) noise during the avalanche transition phase, which makes circuit design more difficult. Therefore, the modeling of RTS noise in SPAD devices is of great significance for the design of signal processing circuits. However, RTS noise is not included in the traditional equivalent circuit model. In response to the above problems, this paper implements an equivalent circuit model with RTS noise based on the Cadence. The model is built based on the basic components in the library, and it has strong application universality. The model is validated in a novel embedded photogate SPAD device (EP-SPAD). It accurately simulates the RTS noise and IV characteristics of the EP-SPAD device. In addition, the threshold voltage of EP-SPAD device operating in Geiger mode is precisely defined based on the characteristics of RTS noise. When the reverse bias voltage is increased from 0 V to 15 V, the IV characteristics of the model are consistent with the EP-SPAD device. [ABSTRACT FROM AUTHOR]

This paper presents a small-signal dynamic model for a modular multilevel converter (MMC) based HVDC grid, and then systematically i) identifies the system dominant oscillatory modes, ii) quantifies their propensity to instability phenomena, and iii) devises appropriate countermeasures. Based on the developed model, the eigen structure of an HVDC grid is characterized and the impact of the system parameters, configuration, AC system strength and operating point on the damping ratios of the oscillatory modes, and consequently the HVDC grid stability, are investigated. The model is also applied to systematically determine the sensitive parameters and optimize them to mitigate oscillatory modes and prevent instability. The eigen analysis results are verified based on time-domain simulation studies in the PSCAD/EMTDC platform. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear analysis model for predicting the performance of eddy current recoil brakes (ECRB) is proposed by combining the magnetic equivalent circuit (MEC) model and the subdomain model. The subdomain model introduces the equivalent region to improve the inherent shortcomings of the equivalent current sheet (ECS) method. The outer tube is divided into a magnetic saturated region and an unsaturated region in the subdomain model to simulate the magnetic saturation of the outer tube during recoil. The MEC model is applied to calculate the air gap magnetic flux density and the relative permeability of the equivalent region. Leakage flux and magnetic saturation are considered in the MEC model. The eddy current resistance of ECRB is calculated by the subdomain model. The model is verified by the finite element model, and it is able to predict the performance of ECRB with different structural parameters. In addition, the prototype of the ECRB was manufactured. A test was carried out on a 155 mm artillery to verify the accuracy of the proposed nonlinear analysis model. [ABSTRACT FROM AUTHOR]

With the widespread application of lithium-ion battery packs, it calls for efficient balancing methods to improve the performance of these battery systems. The relevant research has focused on the design of equalization circuits and control strategies while neglecting quantitative analysis and comparison of battery active equalization structures from the systematic level. In this paper, we propose an improved system-theoretic modeling approach for active equalization structures that takes into account the battery's constraints, including equalization current rate and SOC operation range. Accordingly, the mathematical models of various active equalization structures are derived that can describe their equalization dynamic behavior. Then, the analytical algorithms are developed to estimate the balancing time of active equalization structures online. Finally, extensive numerical simulations are conducted to evaluate and compare the average performance of these equalization systems in term of equalization time. It then comes up with a comprehensive comparison among them. Consequently, the Multicell-to-Multicell (MC2MC) balancing structure benefits the fast balancing speed and the lowest sensitive to initial batteries’ SOCs. The global structure has the lowest implementation cost and the series structure benefits the simplest control. Moreover, the module-based structures have faster balancing speed when each module contains about 4–6 batteries. [ABSTRACT FROM AUTHOR]

This paper studies the capacity of the two-user intensity-modulation/direct-detection (IM/DD) interference channel (IC), which is relevant in the context of multi-user optical wireless communications. Despite some known single-letter capacity characterizations for general discrete-memoryless ICs, a computable capacity expression for the IM/DD IC is missing. In this paper, we provide tight and easily computable inner and outer bounds for a general two-user IM/DD IC under peak and average optical intensity constraints. The bounds enable characterizing the asymptotic sum-rate capacity in the strong and weak interference regimes, as well as the generalized degrees of freedom (GDoF) in the symmetric case. Using the obtained bounds, the GDoF of the IM/DD IC is shown to have a ‘W’ shape similar to the Gaussian IC with power constraints. The obtained bounds are also evaluated numerically in different interference regimes to show their tightness, and used to study the performance of on-chip and indoor OWC systems. [ABSTRACT FROM AUTHOR]

Accurate fault location for underground cables in MMC-HVDC grids reduces the time finding faults as well as the system operational costs. For MMC-HVDC grids, the data window during faults is usually short. During such severe transients, the frequency dependent line parameters of the underground cables have strong influence on the fault location accuracy. In this paper, a novel fault location algorithm for underground cables in MMC-HVDC grids is proposed. First, a multi-layer model for the underground cable using partial differential equations is proposed, which considers the distributed and frequency dependent line parameters in time domain. Afterwards, the numerical finite difference solution of the multi-layer model is proposed to obtain the voltage distributions along the entire cable. Finally, the voltage method is applied to locate faults. Numerical experiments show that the multi-layer model accurately considers the frequency dependency of the cable parameters, and the solution of the model obtains accurate voltage distribution even during system transient. Extensive test cases prove that the proposed algorithm locates faults with less errors than the existing algorithm. The method is also compatible with a relatively low sampling rate (20 kHz) and a short data window (5 ms). [ABSTRACT FROM AUTHOR]

Electromagnetic Transient (EMT) simulation tools are typically developed using conventional procedural programming languages. On the other hand, modern high-level and equation-based programming languages, such as Modelica, are currently available. Modelica allows formulating models that are easy to develop, maintain and understand by expressing what needs to be computed without stating how it should be computed. This paper presents a Modelica-based simulator for electromagnetic transients. It is demonstrated that this approach offers significant advantages for developing sophisticated models. Computational performance and accuracy are compared to a conventional EMT-type simulation tool. [ABSTRACT FROM AUTHOR]

The aim of the paper is to define a limit performance of highly efficient battery electric quadricycles for urban mobility. The vehicle is employed for an energy efficiency competition in which urban concepts compete. A multi-physics (thermo-electro-mechanical) Tank To Wheels (TTW) model has been developed and validated. Given the information on the track route (track map and elevation) and on the throttle input command, the model computes the vehicle power demand and cruising speed. The model is validated by means of both indoor and outdoor experimental tests. The validated model is employed for the optimization of the transmission gear ratio and of the driving strategy to minimize the overall energy consumption on a given track. Design variables are related to the transmission gear ratio and to the throttle command profile. The algorithm aims to minimize the energy consumption, including constraints on the maximum current provided by the battery and on the maximum time available to complete the lap. Comparison with some common driving strategies confirmed the effectiveness of the proposed solution, with a foreseen 9% reduction of the vehicle overall energy demand. The single seater ultra-efficient electric vehicle, compared to other urban quadricycles, has a battery capacity ten times lower and a 50% longer driving range. [ABSTRACT FROM AUTHOR]

The difficulty in acquiring fault label data is a major obstacle to the application of data-driven fault isolation in DC microgrids. To remove this barrier, this paper introduces an approach of generating synthetic data with the line currents measured during normal operation as the substitute for fault label data in training an ensemble model, which is aimed to isolate line short-circuit faults in DC microgrids. Based on a high-frequency model of DC microgrids, we prove that the line currents during the closing of unloaded DC lines have similar high-frequency features as those during a line short-circuit fault. On this basis, the synthetic data are obtained through performing discrete wavelet packet transform on the line currents measured during the circuit breaker operation. With normal operating data and synthetic data, an ensemble model is trained as the fault classifier. In the verification tests of different fault scenarios in a three-terminal DC microgrid model, the detection rates of the proposed ensemble model are over 90% while the false positive rates are below 0.5%. These results prove the effectiveness of using synthetic data as the fault labels in the ensemble learning-based fault isolation in DC microgrids. [ABSTRACT FROM AUTHOR]

This paper introduces a novel frequency domain technique to globally evaluate the accuracy of electro-magnetic transient simulations. It is shown that simulation accuracy at low frequencies can sometimes be poorer than at high frequency. A modified approach which quantifies accuracy from a driving point as a function of frequency is also introduced that uses the Bilinear Transformation and Norton equivalents, to produce a “simulation accuracy spectrum”. This approach can be applied to large systems without explicitly forming state space equations. It also permits the accuracy analysis of networks with distributed components such as frequency dependent transmission lines. Two examples are used to verify the proposed technique, a small network with a frequency dependent transmission line modeled by the universal line model; and the IEEE 39 bus system connected with an LCC-HVdc system. [ABSTRACT FROM AUTHOR]

The high temperature superconducting (HTS) cable has shown promising prospects in megacities for the advantages of high transmission power density and low loss. However, when HTS cable is working on grid, various kinds of faults may cause irreversible damage, resulting in the failure of reclosing. In this paper, the resistive superconducting fault current limiter (R-SFCL) is introduced into the power system to cooperate with the HTS cable, so as to reduce the potential damage caused by fault current. Firstly, the equivalent circuit models are established, and then transient response of HTS cables under fault condition is analyzed, the recovery time of HTS tapes are used to define the design of R-SFCL. Finally, the operating reliability of HTS cable has been evaluated and measures about adaptive reclosing times were proposed under different fault currents. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has been regarded as a promising and revolutionary technology for future wireless communication systems owing to its capability of tailoring signal propagation environment in an energy/spectrum/ hardware-efficient manner. However, most existing studies on IRS optimizations are based on a simple and ideal reflection model that is impractical in hardware implementation, which thus leads to severe performance loss in realistic wideband/multi-band systems. To deal with this problem, in this paper we first propose a more practical and more tractable IRS reflection model that describes the difference of reflection responses for signals at different frequencies. Then, we investigate the joint transmit beamforming and IRS reflection beamforming design for an IRS-assisted multi-cell multi-band system. Both power minimization and sum-rate maximization problems are solved by exploiting popular second-order cone programming (SOCP), Riemannian manifold, minimization-majorization (MM), weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results illustrate the significant performance improvement of our proposed joint transmit beamforming and reflection design algorithms based on the practical reflection model in terms of power saving and rate enhancement. [ABSTRACT FROM AUTHOR]

In this paper, we propose a circuit yield prediction method to improve the efficiency of circuit yield prediction. Both traditional Monte Carlo simulation and the current popular machine learning for yield prediction require a large number of circuit simulation results, which increases production costs. This method finds the data boundary points through high-dimensional kernel density estimation, and performs simulation calculations on these boundary values instead of the overall simulation. Experiments show that, compared with machine learning and Monte Carlo methods, the proposed algorithm can efficiently predict the yield of circuits. [ABSTRACT FROM AUTHOR]