• Title/Summary/Keyword: Chebyshev Polynomial

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Punched-SIW Multi-Section E-Plane Transformer (천공된 기판 집적 도파관 다단 E-Plane 변환기)

  • Cho, Hee-Jin;Byun, Jindo;Lee, Hai-Young
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.3
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    • pp.259-269
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    • 2013
  • In this paper, we propose an SIW(Substrate Integrated Waveguide) multi-section E-plane transformer using air-holes for an SIW system with variable thicknesses. Air-holes are inserted into a SIW E-plane quarter wavelength transformer for matching an E-plane impedance discontinuity. A PSIW(Punched Substrate Integrated Waveguide) consisted of air-holes has an SIW characteristic impedance tunability because of reducing a equivalent shunt capacitance of the SIW. And, a PSIW multi-section E-plane transformer is implemented for improving a matching bandwidth by using the Chebyshev polynomial. The measurement results of PSIW double-section E-plane transformer show that the insertion loss($S_{21}$) is $1.57{\pm}0.11$ dB and input return loss($S_{11}$) is more than 15 dB from 11.45 GHz to 13.6 GHz.

Evaluation on Structure Design Sensitivity and Meta-modeling of Passive Type DSF for Offshore Plant Float-over Installation Based on Orthogonal Array Experimental Method (직교배열실험 방법 기반 해양플랜트 플로트오버 설치 공법용 수동형 DSF의 구조설계 민감도와 메타모델링 평가)

  • Lee, Dong-Jun;Song, Chang Yong
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.5
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    • pp.85-95
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    • 2021
  • Structure design sensitivity was evaluated using the orthogonal array experimental method for passive-type deck support frame (DSF) developed for float-over installation of the offshore plant. Moreover, approximation characteristics were also reviewed based on various meta-models. The minimum weight design of the DSF is significantly important for securing both maneuvering performance and buoyancy of a ship equipped with the DSF and guaranteeing structural design safety. The performance strength of the passive type DSF was evaluated through structure analysis based on the finite element method. The thickness of main structure members was applied to design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experimental method and analysis of variance. The optimum design case was also identified from the orthogonal array experiment results. Various meta-models, such as Chebyshev orthogonal polynomial, Kriging, response surface method, and radial basis function-based neural network, were generated from the orthogonal array experiment results. The results of the orthogonal array experiment were validated using the meta-modeling results. It was found that the radial basis function-based neural network among the meta-models could approximate the design space of the passive type DSF with the highest accuracy.

A Comparative Study on Approximate Models and Sensitivity Analysis of Active Type DSF for Offshore Plant Float-over Installation Using Orthogonal Array Experiment (직교배열실험을 이용한 해양플랜트 플로트오버 설치 작업용 능동형 DSF의 민감도해석과 근사모델 비교연구)

  • Kim, Hun-Gwan;Song, Chang Yong
    • Journal of the Korea Convergence Society
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    • v.12 no.3
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    • pp.187-196
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    • 2021
  • The paper deals with comparative study for characteristics of approximation of design space according to various approximate models and sensitivity analysis using orthogonal array experiments in structure design of active type DSF which was developed for float-over installation of offshore plant. This study aims to propose the orthogonal array experiments based design methodology which is able to efficiently explore an optimum design case and to generate the accurate approximate model. Thickness sizes of main structure member were applied to the design factors, and output responses were considered structure weight and strength performances. Quantitative effects on the output responses for each design factor were evaluated using the orthogonal array experiment. Best design case was also identified to improve the structure design with weight minimization. From the orthogonal array experiment results, various approximate models such as response surface model, Kriging model, Chebyshev orthogonal polynomial model, and radial basis function based neural network model were generated. The experiment results from orthogonal array method were validated by the approximate modeling results. It was found that the radial basis function based neural network model among the approximate models was able to approximate the design space of the active type DSF with the highest accuracy.