Advanced Surrogate-Based EM Optimization Using Complex Frequency Domain EM Simulation-Based Neuro-TF Model for Microwave Components

Surrogate-based electromagnetic (EM) optimization techniques have become popular for microwave design. Neuro-transfer function (neuro-TF) is one of the effective surrogates to represent the EM behaviors for design optimization. In this article, we propose an advanced surrogate-based EM optimization using neuro-TF developed by complex frequency domain (CFD)-based EM simulations. For the first time, we develop and introduce the CFD-based EM simulation using fast frequency sweep. We propose a novel transfer function zero/pole extraction technique based on the magnitude of the S-parameter of CFD-based EM simulations. Two-step training process is used for developing the neuro-TF surrogate model with the extracted zero/poles. Using the proposed zero/pole extraction technique, the developed neuro-TF surrogate model can have larger geometrical range than that using vector fitting. Consequently, the surrogate-based EM optimization using neuro-TF developed by CFD-based EM simulation can achieve a speedup over the standard neuro-TF optimization. Two examples of EM optimizations of microwave components are used to demonstrate the proposed technique.

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Publication Details

Journal
IEEE Transactions on Microwave Theory and Techniques
Published
2024-10-25
DOI
https://doi.org/10.1109/tmtt.2024.3478765
Citations
10
Primary Topic
Microwave Engineering and Waveguides
Type
article
Field-Weighted Citation Impact
2.09

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Advanced Surrogate-Based EM Optimization Using Complex Frequency Domain EM Simulation-Based Neuro-TF Model for Microwave Components

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10 citations
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article

Advanced Surrogate-Based EM Optimization Using Complex Frequency Domain EM Simulation-Based Neuro-TF Model for Microwave Components

Jing Jin, Wei Liu, Xiaolong Li, Qijun Zhang, Li Ma, Kaixue Ma
article en
10 citations

Abstract

Surrogate-based electromagnetic (EM) optimization techniques have become popular for microwave design. Neuro-transfer function (neuro-TF) is one of the effective surrogates to represent the EM behaviors for design optimization. In this article, we propose an advanced surrogate-based EM optimization using neuro-TF developed by complex frequency domain (CFD)-based EM simulations. For the first time, we develop and introduce the CFD-based EM simulation using fast frequency sweep. We propose a novel transfer function zero/pole extraction technique based on the magnitude of the S-parameter of CFD-based EM simulations. Two-step training process is used for developing the neuro-TF surrogate model with the extracted zero/poles. Using the proposed zero/pole extraction technique, the developed neuro-TF surrogate model can have larger geometrical range than that using vector fitting. Consequently, the surrogate-based EM optimization using neuro-TF developed by CFD-based EM simulation can achieve a speedup over the standard neuro-TF optimization. Two examples of EM optimizations of microwave components are used to demonstrate the proposed technique.

IEEE Transactions on Microwave Theory and TechniquesVol. 73(4)
Tianjin University (CN), Central China Normal University (CN), Carleton University (CA)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 12%
Microwave Engineering and Waveguides
2.09
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