Analysis of Nonuniform Transmission Lines With a Perturbation Technique in Time Domain

Zhang, Yin; Liao, Cheng; Rui, Huan; Shang, Yuping; Zhou, Haijing

doi:10.1109/temc.2019.2906251

Cited by 12 publications

(9 citation statements)

References 24 publications

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“…Reference [8] mentions that the Moment Method does not achieve very good accuracy, which is mainly due to the following two reasons. On one hand, the Moment Method assumes that the input and output are in a linear relationship, which leads to calculation error of sensitivity S(i) in formula (1). On the other hand, this formula only considers the disturbance quantity when it is greater than the average value, the sensitivity estimated does not represent the whole situation at this time.…”

Section: Sensitivity Analysis Based On the Richardson Extrapolation M...mentioning

confidence: 99%

“…Uncertainty analysis methods can be divided into two categories. In one class, some of the methods need to change the original solver, such as the Perturbation Method [1], the Stochastic Galerkin Method [2,3], and the Stochastic Testing Method [4]. In general, to describe complex electromagnetic compatibility problems in practical engineering environment, the finite element analysis method is used to construct model parameters, and then commercial simulation software is needed.…”

Section: Introductionmentioning

confidence: 99%

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Reduction of Random Variables in EMC Uncertainty Simulation Model

Bai

Wan²,

Li³

et al. 2023

ACES Journal

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To improve the reliability of simulation results, uncertainty analysis methods were developed in the Electromagnetic Compatibility (EMC) field. Random variables are used to describe random events. The more random variables you have, the less efficient the simulation is. Therefore, many high-accuracy methods have the problem of dimensional disaster, which means the calculation efficiency decreases exponentially with the increase of the number of random variables. A random variable reduction strategy based on sensitivity analysis method is proposed in this paper, so as to improve the computational efficiency of the global uncertainty analysis method.

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Section: Sensitivity Analysis Based On the Richardson Extrapolation M...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reduction of Random Variables in EMC Uncertainty Simulation Model

Bai

Wan²,

Li³

et al. 2023

ACES Journal

View full text Add to dashboard Cite

show abstract

“…Another characteristic of EMC simulation is that its calculation needs the help of commercial simulation software in most cases. On this premise, the uncertainty analysis method which needs to change the previous solver cannot be used normally, such as the perturbation method [4], the stochastic Galerkin method [5,6], and the stochastic testing method [7]. At the same time, there are still some uncertainty analysis methods, such as the moment method [8] and the stochastic reduced order models [9].…”

Section: Introductionmentioning

confidence: 99%

Application of the Multi-element Grid in EMC Uncertainty Simulation

Bai

Guo

Sun³

et al. 2022

ACES Journal

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Uncertainty analysis is a research hotspot in the field of electromagnetic compatibility (EMC) simulation. The stochastic collocation method (SCM) is considered particularly suitable for uncertainty analysis in the EMC field because it is characterized by a high level of computational efficiency and accuracy while requiring no replacement solver. However, the post-processing process of the SCM is too complex, which will seriously limit its application in many industrial environments such as real-time simulation analysis. Multi-element grid (MEG) is a novel uncertainty analysis method recently for successful application in another area. It is proved that its calculation accuracy is same as the SCM, and its post-processing process is facile. This paper introduces the MEG to the EMC field and makes a detailed comparison between it and the SCM in performance, aiming to apply uncertainty analysis to solve more practical EMC engineering problems.

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“…Subsequently, some efficient uncertainty analysis methods, such as Direct Solution Technique (DST) [11], Unscented Transforms (UT) [12,13], and Perturbation Method (PM) [14], have received increasing attention, but they have not been widely applied due to their poor accuracy.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Analysis Method of Computational Electromagnetics Based on Clustering Method of Moments

Bai¹,

Wang²,

Li³

2022

PIER M

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Uncertainty analysis is one of the hot research issues in the field of computational electromagnetics in the past five years. The Method of Moments is a non-embedded uncertainty analysis method with relatively high computational efficiency and has the unique advantage of not being affected by the "curse of dimensionality". However, when the nonlinearity between the simulation input and output is large, the accuracy of the Method of Moments is not ideal, which severely limits its application in the field of computational electromagnetics. In this paper, an improved strategy based on the central clustering algorithm is proposed to improve the expected value prediction results of the Method of Moments, thereby improving the accuracy of the overall uncertainty analysis. At the same time, the co-simulation technology of MATLAB software and COMSOL software is completed, then the accuracy and computational efficiency of the proposed algorithm in this paper are quantitatively verified. In this case, the clustering Method of Moments is effectively popularized in commercial electromagnetic simulation software.

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Analysis of Nonuniform Transmission Lines With a Perturbation Technique in Time Domain

Cited by 12 publications

References 24 publications

Reduction of Random Variables in EMC Uncertainty Simulation Model

Reduction of Random Variables in EMC Uncertainty Simulation Model

Application of the Multi-element Grid in EMC Uncertainty Simulation

Uncertainty Analysis Method of Computational Electromagnetics Based on Clustering Method of Moments

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