Accounting for Wire Coating in the Modeling of Field Coupling to Twisted-Wire Pairs

Yuan, Keliang; Grassi, Flavia; Spadacini, Giordano; Pignari, Sergio A.

doi:10.1109/temc.2017.2707666

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…The next step in the developing the cable model is the incorporation of the twisting effects into the model. As in a similar method used to model helical antenna structures [6], we investigate the presentation of the self‐inductance of a circular conducting wire loop. The external inductance of the loop shown in Figure 2 is given by [15]:

\begin{matrix} true \\ right \begin{matrix} left false[L_{c o i l_e x t} \\ left = \frac{μ_{o} D^{2}}{4 π} \int_{0}^{2 π} \int_{0}^{2 π} \frac{\cos false(θ_{1} - θ_{0} false) \partial θ_{0} \partial θ_{1}}{[2 D (D - d) + d^{2} - 2 D (D - d) \cos (θ_{1} - θ_{0})]^{0.5}} . \end{matrix} \end{matrix}

Through a change of variables and the use of elliptic integrals, the following result is obtained:

L_{c o i l_e x t} = \frac{μ_{o} D}{2} (\ln \frac{8 D}{d} - 2) .

…”

Section: Broadband Twisted Pair Cable Modelmentioning

confidence: 99%

Measurement and causal modelling of twisted pair copper cables

Yoho¹,

Riad

Muqaibel

2021

IET Science Measure & Tech

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The modelling of twisted pair copper cables has been under investigation in recent years with the emergence of several forms of digital subscriber line broadband access technology including G.fast. Designers of these communication systems implement these models to prototype early system architectures as well as simulate feasibility trials on the existing subscriber loop infrastructure. Previous attempts at modelling these cables have been limited because of the challenges associated with acquiring physical measurement and the inaccuracies of simulators to model effects such as the skin effect, which is significant when using these cables in high-speed systems. These previous modelling attempts employed empirical formulas to match the measured primary transmission line parameters (RLCG) of the cables and generally failed to meet the Kramer-Kronig causality relationships. This paper presents a measurement setup for the electrical properties of twisted pair copper cables as well as a realizable RLCG model for the cables. This model is based on electromagnetic theory considering the model causality, the skin effect, and the twisting of the cable.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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\begin{matrix} true \\ right \begin{matrix} left false[L_{c o i l_e x t} \\ left = \frac{μ_{o} D^{2}}{4 π} \int_{0}^{2 π} \int_{0}^{2 π} \frac{\cos false(θ_{1} - θ_{0} false) \partial θ_{0} \partial θ_{1}}{[2 D (D - d) + d^{2} - 2 D (D - d) \cos (θ_{1} - θ_{0})]^{0.5}} . \end{matrix} \end{matrix}

Through a change of variables and the use of elliptic integrals, the following result is obtained:

L_{c o i l_e x t} = \frac{μ_{o} D}{2} (\ln \frac{8 D}{d} - 2) .

…”

Section: Broadband Twisted Pair Cable Modelmentioning

confidence: 99%

Measurement and causal modelling of twisted pair copper cables

Yoho¹,

Riad

Muqaibel

2021

IET Science Measure & Tech

View full text Add to dashboard Cite

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“…We need to perform some slight modifications. Using and and the theories given in the previous study, and are revised as

\frac{normald V_{M}^{sct} ((), ℓ)}{normald ℓ} + normalj ω {\overset{L}{true}}_{boldM}_{p} I_{M} ((), ℓ) = E_{M} ((), ℓ)

\frac{normald I_{M} ((), ℓ)}{normald ℓ} + normalj ω {\overset{true¯}{bold-italicC}}_{{boldM}_{scriptp}}^{Coat} V_{M}^{sct} ((), ℓ) = bold0 .

where

{\overset{true¯}{bold-italicC}}_{{boldM}_{scriptp}}^{Coat}

is the averaged modal p.u.l. capacitance matrix when there is a coating with relative permittivity ϵ r and thickness t around all the wires.…”

Section: Modal Domain Decompositionmentioning

confidence: 99%

“…capacitance of a TWP is equal to the p.u.l. capacitance of a two‐parallel straight wire . The averaged diagonal modal capacitance matrix is calculated by

{\overset{true¯}{bold-italicC}}_{{boldM}_{scriptp}}^{Coat} bold-italic= diag ((),,,,,,,, {\overset{C}{true}}_{CM}^{coat}, {\overset{C}{true}}_{{DM}_{3}}^{coat}, {\overset{C}{true}}_{{DM}_{2, 1}}^{coat}, {\overset{C}{true}}_{{DM}_{2, 2}}^{coat}, {\overset{C}{true}}_{{DM}_{1, 1}}^{coat}, {\overset{C}{true}}_{{DM}_{1, 2}}^{coat}, {\overset{C}{true}}_{{DM}_{1, 3}}^{coat}, {\overset{C}{true}}_{{DM}_{1, 4}}^{coat})

…”

Section: Modal Domain Decompositionmentioning

confidence: 99%

“…capacitance of a two-parallel straight wire. 9 The averaged diagonal modal capacitance matrix is calculated by The solution of (44a) and (44b) takes the form given by the Thevenin equivalent circuit of Figure 6. However, the propagation constant k should be interchanged to β XM , and…”

Section: Dielectric Coating Effectsmentioning

confidence: 99%

“…The extension of the equivalent cable bundle method for modeling crosstalk in complex cable bundles was done in the previous study . More recently, Pignari et al have carried out very effective studies on modeling field‐to‐wire coupling in bundles of TWP with different geometries, respectively. Because of the geometrical feature of TWP as well as TWP bundles, both analytical and numerical methods can be implemented for predicting their input‐output responses or crosstalk among them, while analytical or semianalytical approaches can save much time for simulating many TWPs in comparison with the commercial software FEKO…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modeling electromagnetic wave coupling and mode conversion effects in multitwisted bundle of twisted‐wire pairs (MTB‐TWP) above ground plane

Gassab

Zhou

Wang

et al. 2018

Int J Numerical Modelling

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A multiconductor transmission line (MTL) model is developed for predicting electromagnetic wave coupling effects with multitwisted bundle of twisted‐wire pairs (MTB‐TWP) running above a ground plane. Such MTB‐TWP is described as a sequential repeated structure, where all its parameters are formulated in terms of sequences. In particular, the parametric equations of all the wires are derived and described by a set of generalized equations, where the unit tangent vector for each wire is also determined analytically. In addition, the averaged per‐unit‐length (p.u.l.) parameters are described by recurrence formulas. Further, the equivalent voltages for describing the field‐to‐wire coupling of MTB‐TWP are obtained and determined analytically. The modal domain decomposition is performed with special loading terminals to split out the common mode (CM) and differential mode (DM) signals, where the CM‐to‐DM conversions are further investigated in order to indicate the balanced property in such MTB‐TWP system. On the other hand, the effect of dielectric coatings of all the wires is also characterized, where the averaged modal p.u.l. capacitance matrix is obtained numerically. A comparison is performed with the other wiring structures to visualize the benefits of our MTB‐TWP model. An extended MTL model is also validated in comparison with the commercial software FEKO.

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Design of inverse multiquadric radial basis neural networks for the dynamical analysis of wire coating problem with Oldroyd 8-constant fluid

2022

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Wire coating is a commercial method to insulate wires for mechanical intensity and environmental protection. In this experimental study, the technique of computational intelligence is used for nonlinear wire coating analysis by soaking the wires in Oldroyd 8-constant fluid under a constant pressure gradient with the help of feed forward artificial neural networks (ANNs). The system of partial differential equations generated for the process of wire coating is transformed into a nonlinear dimensionless ordinary differential equation. One of the salient features of ANNs is the mathematical modeling of transformed equations by exploring the unsupervised error. A new scheme based on inverse multiquadric neural networks (IMQNNs) is used with a hybridization process of well-known genetic algorithms (GAs) and sequential quadratic programming (SQP) to obtain expeditious convergence, i.e., IMQNNs-GA-SQP. The applicability of the problem is investigated by altering the values of the dilatant constant, pressure gradient, shear stress, and pseudo-plastic constant, the outcome of which is in the form of varying polymer coating thickness. Comparison of highly accurate results in the shape of error analysis based on absolute errors of obtained results with those of the reference solution, calculated using the Adams numerical technique using MATHEMATICA software, statistical analysis such as root-mean-square error, Theil’s coefficient for inequality, E-R2 (error function based on the coefficient of determination), E-VAF (variance accounted for), E-NSE (Nash–Sutcliffe efficiency), mean absolute error, box plot analyses, and the cumulative distributive function through histogram analyses, is also carried out in this research, which guarantees the effectiveness of the used scheme.

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Accounting for Wire Coating in the Modeling of Field Coupling to Twisted-Wire Pairs

Cited by 11 publications

References 8 publications

Measurement and causal modelling of twisted pair copper cables

Measurement and causal modelling of twisted pair copper cables

Modeling electromagnetic wave coupling and mode conversion effects in multitwisted bundle of twisted‐wire pairs (MTB‐TWP) above ground plane

Design of inverse multiquadric radial basis neural networks for the dynamical analysis of wire coating problem with Oldroyd 8-constant fluid

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