Uncertainty analysis of 2 port measurement

[Radiosan]

I analyzed uncertainty analysis of 2 port measurement. I referenced 2 book

"Transmission Reflection and Short Circuit Line Methods for Measuring Permittivity and Permeability"
at pages 31 equation(2.83)

"Transmission and Reflection and SCL Permittivity Measurements" at pages 44 equation(2.67)

You can google 2 book name to find them.

I plot equation(2.83) and equation(2.67) but they look different.

blue line is equation(2.67) and green line is equation(2.67)

Do they describe the same thing? Why are the results different?

 

[Achy47]

Thank you for sharing your analysis on uncertainty analysis of 2 port measurement and referencing the two books. I understand that you have plotted equations (2.83) and (2.67) from the two books and have noticed that the results are different.

To answer your question, yes, both equations describe the same thing, which is the measurement of permittivity and permeability using the transmission, reflection, and short circuit line methods. However, the difference in the results could be due to various factors such as the measurement setup, equipment used, and experimental conditions.

It is important to note that equations (2.83) and (2.67) may have been derived using different assumptions and approximations, leading to variations in the results. Additionally, the equations may have been validated using different experimental data, which can also contribute to the differences in the results.

Furthermore, the accuracy of the results also depends on the precision and accuracy of the measurement equipment and the techniques used in the measurement process. Even small errors in the setup or calibration of the equipment can significantly impact the results.

In conclusion, while equations (2.83) and (2.67) describe the same thing, the differences in the results could be due to various factors such as experimental conditions, equipment used, and measurement techniques. It would be helpful to further analyze the equations and understand the underlying assumptions and experimental setups to better understand the differences in the results.