Inquiry about Importing a Spatially Varying Permittivity Field into gprMax

[xiang li]

Dear gprMax Development Team,

I hope this message finds you well.

I am a master's student at Jilin University, currently conducting research on subsurface pipeline leakage, seepage simulation, and the corresponding ground-penetrating radar (GPR) response.

In my study, I have obtained a 3D distribution of volumetric water content under pipeline leakage conditions using a seepage model. The dataset has a resolution of 301 × 301 × 301, totaling approximately 27 million data points. Using the empirical Topp equation, I converted this data into a corresponding 3D continuous dielectric permittivity field.

My goal is to use gprMax to simulate GPR wave propagation in this medium. However, I have encountered a challenge: it appears that the current version of gprMax primarily assigns dielectric parameters to discrete material blocks using the #material command. I have not found a way to directly import a continuously varying permittivity field.

Therefore, I would like to ask:

• Is there a method to batch import such a spatially varying permittivity field into gprMax?

• If not natively supported, would you recommend approximating the continuous field by generating a large number of #material definitions (e.g., assigning each voxel or sub-region a unique material)?

Thank you sincerely for developing and maintaining such a powerful simulation tool. I would greatly appreciate any guidance you could provide regarding import methods or modeling strategies.

[Antonis Giannopoulos]

Hi,

You can easily do what you need but you will need to do some scripting either in Python or any other language you use. Your dataset is not continuous as it is produced by another discrete model which is your seepage model. You can convert this to an input for gprMax in many ways. First you should not use 27 million different dielectric points as this is not needed in such resolution. You should bin your relative permittivities by a suitable discrete amount one easy way to do this is by rounding your Topp relative permittivities to their second decimal point. Even the first decimal point should be fine. As you realise this will restrict the number of different material in your model significantly as many points will have the same values. You can then create the spatial distribution of them using a small script and use the #geometry_object_read: command (http://docs.gprmax.com/en/latest/input.html#geometry-objects-read) to read your geometry and materials.

This has been done many times before to  in different ways. 

Good luck

Antonis

[xiang li]

  Dear Professor Giannopoulos, Thank you very much for your detailed and helpful reply. I truly appreciate your suggestions. I will follow your advice and try the approach of binning the relative permittivities and scripting the spatial distribution accordingly. Thanks again for your support and guidance! Best regards, xiang li