2013
DOI: 10.2528/pierm12121904
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Multiconductor Reduction Method for Modeling Crosstalk of Complex Cable Bundles in the Vicinity of a 60 Degree Corner

Abstract: Abstract-This paper presents a multiconductor reduction method for modeling electromagnetic crosstalk of complex cable bundles in the vicinity of a 60 degree corner. Based on the image theory and wide separation assumption, the per-unit-length parameters of the cable bundle can be obtained analytically. A modified six-step procedure is established to define the electrical and geometrical characteristics of the reduced cable bundle model compared with the original equivalent cable bundle method (ECBM). Numerica… Show more

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Cited by 5 publications
(8 citation statements)
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“…3(b) and the p.u.l. reduced matrices calculated by the ECBM shown as (7) and (8). Consequently, a second-order optimization result with a mean difference of 0.8% and 10.4% respectively for the [L reduced ] and [C reduced ] matrices is obtained in this paper [14].…”
Section: Validations Of the Proposed Methods For Crosstalk Prediction mentioning
confidence: 99%
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“…3(b) and the p.u.l. reduced matrices calculated by the ECBM shown as (7) and (8). Consequently, a second-order optimization result with a mean difference of 0.8% and 10.4% respectively for the [L reduced ] and [C reduced ] matrices is obtained in this paper [14].…”
Section: Validations Of the Proposed Methods For Crosstalk Prediction mentioning
confidence: 99%
“…In this section, compared with previous papers [1][2][3][4][5][6][7][8][9], the differences and also the challenging points of the proposed method are the grouping of conductors and the building of the cross-section geometry of the reduced cable bundle model, which are detailed in the following paragraph. As far as the EM crosstalk is concerned, the approximate assumptions including a) all conductors are PEC and the surrounded medium is lossless, b) only transverse electromagnetic (TEM) mode is considered.…”
Section: Presentation Of the Proposed Methods For Modeling Crosstalk Omentioning
confidence: 99%
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