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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 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]

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]

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 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]

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]

Objective: Surgeons have no direct objective feedback on cochlear-implant electrode array (EA) positioning during insertion, yet optimal hearing outcomes are contingent on placing the EA as close as feasible to viable neural endings. This paper describes a system to non-invasively determine intracochlear positioning of an EA, without requiring any modifications to existing commercial EAs themselves. Methods: Electrical impedance has been suggested as a way to measure EA proximity to the inner wall of the cochlea that houses auditory nerve endings—the modiolus. In this paper, we extend prior work and demonstrate for the first time the relationship between bipolar access resistance and proximity of the EA to the modiolus (E-M proximity). We also evaluate two methods for producing direct, real-time estimates of E-M proximity from bipolar impedance measurements. Results: We show that bipolar access resistance is highly correlated with E-M proximity and can be approximately modeled by a power law function. This one dimensional model is shown to be capable of producing accurate real-time estimates of E-M proximity, but its simplicity also limits the potential for future improvement. To address this challenge, we propose a new prediction approach based on a recurrent neural network, which generated an overall prediction accuracy of 93.7%. Conclusion: Bipolar access resistance is highly correlated with E-M proximity, and can be used to estimate EA positioning. Significance: This work shows how impedance sensing can be used to localize an EA during insertion into the small, enclosed cochlear environment, without requiring any modifications to existing clinically used EAs. [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]

In recent years, very high frequency (VHF) converter has attracted much attention. However, with rich parasitic parameters and complex resonance links, there are some great difficulties to the modeling of such systems. Taking the on-off controlled VHF resonant boost converter as an example, this paper presents an accurate modeling and analysis method that considers multiple parasitic parameters. First, the closed-loop VHF converter system is divided into a main network and a parasitic oscillation network. Then, based on the operation analysis, an equivalent circuit model characterized by a time-varying input voltage source and two variable duty-cycle controlled switches is proposed. It worth noting that both the time-varying input and the controlled switches take into account the influences of the parameters. Furthermore, the periodic approximate analytical solution of the output voltage in the on stage is obtained by using the equivalent small parameter method to the proposed circuit model. And then combining the solution of the parasitic oscillation network and on-off state switching conditions, the steady-state waveform of output voltage can be obtained quickly. Finally, a prototype with operating frequency of 21.44 MHz is built to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Human Body Communication (HBC) is an alternative to radio wave-based Wireless Body Area Network (WBAN) because of its wide bandwidth leading to enhanced energy efficiency. Designing Modern HBC devices need the accurate electrical equivalent of the HBC channel for energy efficient communication. The objective of this paper is to present an improved lumped element-based detailed model of Galvanic HBC channel which can be used to explain the dependency of the channel behaviour on the internal body dependent parameters such as electrical properties of skin and muscle tissue layers along with the external parameters such as electrode size, electrode separation, geometrical position of the electrodes and return-path or parasitic capacitances. The model considers the frequency-dependent impedance of skin and muscle tissue layers and the effect of various coupling capacitances between the body and Tx/Rx electrodes to the Earth-Ground. A 2D planar structure of skin and muscle tissue layers is simulated using a Finite Element Method (FEM) tool to prove the validity of the proposed model. The effect of symmetry and asymmetry at the transmitter and receiver ends is also explained using the model. The model become very useful for fast calculation of Galvanic channel response without using any FEM tool. Experimental results show that the galvanic response is not only a function of channel length but also depends on the mismatch at the transmitter and receiver end. In case of a very high mismatch scenario, the channel behavior is dominated by the capacitive HBC, even for a galvanic excitation and termination. [ABSTRACT FROM AUTHOR]

The notion of correlation immune functions has been introduced by Siegenthaler (1984) in symmetric cryptography in the framework of stream ciphers. At the conference CRYPTO’91 by Camion et al., it has been pointed out that this notion existed in statistics and combinatorics. It has recently been highlighted that such functions also play an important role in a new framework related to side-channel attack counter-measures. Since then, the interest in correlation immune Boolean functions has been renewed, and new challenges regarding these functions have appeared. Specifically, low Hamming weight correlation immune functions have been selected as useful for counter-measures to side-channel attacks. Despite their importance, the literature is not abundant in this research direction. Two very interesting articles in which such correlation immune functions were nicely explored, given this novel use of them. Carlet initiated the first one in 2013, and the second one is due to Carlet and Chen (2018). This paper deals with correlation immune Boolean functions aiming to produce more candidates of those processing low Hamming weights. We shall focus on correlation immune Boolean functions with Hamming weights power of 2 (which offer a flexibility to control the correlation immunity aspects) and present several methods of designing them. Some design methods are efficient and could be employed to derive such functions. Consequently, given two positive integers $n$ and $m$ , we derive new effective constructions of correlation immune Boolean functions with Hamming weight power of 2. Furthermore, an upper bound on the correlation immunity of the newly constructed $n$ -variable Boolean functions with Hamming weight $2^{m}$ was determined for $n-m\ge 0$. Besides, exact values and lower bounds on the maximum correlation immunity of those functions are explored and discussed, mainly when the values of $n$ and $m$ are very close. This paper also exhibits explicit examples of those correlation immune functions that illustrate our methods. [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 increasing complexity of modern AC/DC power systems poses a significant challenge to a fast solution of large-scale transient stability simulation problems. This paper proposes the hybrid parallel-in-time-and-space (PiT+PiS) transient simulation on the CPU-GPU platform to thoroughly exploit the parallelism from time and spatial perspectives, thereby fully utilizing parallel processing hardware. The respective electromechanical and electromagnetic aspects of the AC and DC grids demand a combination of transient stability (TS) simulation and electromagnetic transient (EMT) simulation to reflect both system-level and equipment-level transients. The TS simulation is performed on GPUs in the co-simulation, while the Parareal parallel-in-time (PiT) scheduling and EMT simulation are conducted on CPUs. Therefore, the heterogeneous CPU-GPU scheme can utilize asynchronous computing features to offset the data transfer latency between different processors. Higher scalability and extensibility than GPU-only dynamic parallelism design is achieved by utilizing concurrent GPU streams for coarse-grid and fine-grid computation. A synthetic AC/DC grid based on IEEE-118 Bus and CIGRÉ DCS2 systems showed a good accuracy compared to commercial TSAT software, and a speedup of 165 is achieved with 48 IEEE-118 Bus systems and 192 201-Level detail-modeled MMCs. Furthermore, the proposed method is also applicable to multi-GPU implementation where it demonstrates decent efficacy. [ABSTRACT FROM AUTHOR]

The intelligent omni-surface (IOS) is a dynamic metasurface that has recently been proposed to achieve full-dimensional communications by realizing the dual function of anomalous reflection and anomalous refraction. Existing research works provide only simplified models for the reflection and refraction responses of the IOS, which do not explicitly depend on the physical structure of the IOS and the angle of incidence of the electromagnetic (EM) waves. Therefore, the available reflection-refraction models are insufficient to characterize the performance of full-dimensional communications. In this paper, we propose a complete and detailed circuit-based reflection-refraction model for the IOS, which is formulated in terms of the physical structure and equivalent circuits of the IOS elements, as well as we validate it with the aid of full-wave EM simulations. Based on the proposed circuit-based model for the IOS, we analyze the asymmetry between the reflection and transmission coefficients. Moreover, the proposed circuit-based model is utilized for optimizing the hybrid beamforming of IOS-assisted networks and hence improving the system performance. To verify the circuit-based model, the theoretical findings, and to evaluate the performance of full-dimensional beamforming, we implement a prototype of IOS and deploy an IOS-assisted wireless communication testbed to experimentally measure the beam patterns and to quantify the achievable rate. The obtained experimental results validate the theoretical findings and the accuracy of the proposed circuit-based reflection-refraction model for IOSs. [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]

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]

This paper presents a passive lumped model for DC cables and overhead lines, taking into account the frequency dependency of the per-unit-length parameters due to the skin and proximity effects. In comparison to distributed parameter line models, such as the Frequency-Dependent Phase model of PSCAD, the proposed model does not require line propagation delay extraction and does not impose any restrictions on the simulation timestep. As a result, for electrically short lines, the introduced model is more computationally efficient than distributed parameter models as it enables simulation using larger timesteps. The performance of the proposed model is evaluated in comparison with the PI model and the Frequency-Dependent Phase model through time-domain simulations of a DC microgrid and a radial DC distribution feeder. The studies performed in PSCAD focus on fault-induced transients. The results indicate that for electrically short lines the developed model is significantly more accurate compared to the PI model and provides similar accuracy with more computational efficiency compared to the Frequency-Dependent Phase model. [ABSTRACT FROM AUTHOR]

An amplitude demodulator, using an on-line MEMS power sensor is studied in this paper. The model of the equivalent circuit of on-line structure is solved, and the heat transfer model related to the thermopile is proposed and also simulated to verify the feasibility of AM demodulation. Experiments are also performed to verify the proposed models. The microwave performance shows that the device has a return loss that is better than 20 dB, and an insertion loss of less than 0.5 dB up to 10 GHz. Both the model and the experimental results show that the MEMS device can perform demodulation of an AM signal with carrier frequency of 0.01–10 GHz and signal frequency of under 1kHz. [2021-0261] [ABSTRACT FROM AUTHOR]

Instance-wise contrastive learning (Instance-CL), which learns to map similar instances closer and different instances farther apart in the embedding space, has achieved considerable progress in self-supervised video representation learning. However, canonical Instance-CL does not handle properly the temporal similarities between different videos, limiting the representation capabilities of learned models. This paper presents a novel two-stage framework that combines Instance-CL and unsupervised clustering to progressively learn desirable temporal representations with high intra-class compactness. Specifically, (a) we first introduce a new consistency-preserving sampling strategy to generate positive/negative pairs. Compared to the traditional sampling methods, our sampling strategy focuses more on motion dynamics, resulting in more temporal-related feature representations. (b) To further explore the temporal similarities between videos so as to encourage intra-class compactness, we set temporal representations extracted from Instance-CL as an initializer, and iteratively use k-means clustering to generate pseudo-labels for training the encoder. We term our method as Improved Instance-CL with Deep Clustering (ICDC) and apply it to two downstream tasks, including action recognition and video retrieval. Extensive experimental results show that ICDC gains considerable improvements compared to the existing self-supervised methods. [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]