Characteristic impedance Result of Microstrip Transmission lines with 3D EM simulation tool

Characteristic impedance Result of Microstrip Transmission lines with 3D EM simulation tool

These data had been donated by Peyman Mahouti in 2019.

Donators note:

Please cite the following paper if you use this data set:

[1]      Mahouti P, Gunes F, Belen MA, Demirel S. Symbolic Regression for Derivation of an Accurate Analytical Formulation Using Big Data : An Application Example. ACES JOURNAL 2017; 32(5): 574-591.

In this data set:

The characteristic impedance Z0 value of microstrip transmission lines had been obtained via 3D simulations [1]. The data set is consist of 20440 number of samples which are depend on height of substrate h, die electric constant of substrate εr, width of the transmission line w, frequency f. these samples had been used in [2] for obtaining and analytical expression for Z0 of a microstrip transmission line depend on the variables given in samples. 4290 number of samples had been selected by taking most commonly used substrates such as Rogers, Duroid and FR4 as reference. Rest of the data is selected by authors for a better interpolation and extrapolation result in the obtained analytic expression. Z0 values obtained from simulation had been normalized by 50 Ohm for a better training results. More detailed description and application note can be found in [2].

 Data set description

Number of samples: 20440

Used Substrates:  Duroid 5880, Duroid 6006, FR4, Roger 3003, Roger 3006, and non-commercial with different combinations of design parameters.

Attributes number: 5

Attributes description:

1-      Height of substrate h

2-      Die electric constant of substrate εr,

3-      Width of the transmission line w,

4-      Frequency f,

5-      Normalized characteristic impedance Z0/50.

References

[1]- https://www.sonnetsoftware.com/

[2]- Mahouti P, Gunes F, Belen MA, Demirel S. Symbolic Regression for Derivation of an Accurate Analytical Formulation Using Big Data : An Application Example. ACES JOURNAL 2017; 32(5): 574-591.