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Added note on PML with fractal distributions
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craig-warren committed Apr 15, 2024
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4 changes: 4 additions & 0 deletions docs/source/input_api.rst
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Expand Up @@ -175,6 +175,10 @@ Fractal Box
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.. autoclass:: gprMax.cmds_geometry.fractal_box.FractalBox

.. note::

* Currently (2024) we are not aware of a formulation of Perfectly Matched Layer (PML) absorbing boundary that can specifically handle distributions of material properties (such as those created by fractals) throughout the thickness of the PML, i.e. this is a required area of research. Our PML formulations can work to an extent depending on your modelling scenario and requirements. You may need to increase the thickness of the PML and/or consider tuning the parameters of the PML (:ref:`pml-tuning`) to improve performance for your specific model.

Add Grass
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.. autoclass:: gprMax.cmds_geometry.add_grass.AddGrass
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4 changes: 4 additions & 0 deletions docs/source/input_hash_cmds.rst
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Expand Up @@ -620,6 +620,10 @@ Allows you to introduce an orthogonal parallelepiped with fractal distributed pr

For example, to create an orthogonal parallelepiped with fractal distributed properties using a Peplinski mixing model for soil, with 50 different materials over a range of water volumetric fractions from 0.001 - 0.25, you should first define the mixing model using: ``#soil_peplinski: 0.5 0.5 2.0 2.66 0.001 0.25 my_soil`` and then specify the fractal box using ``#fractal_box: 0 0 0 0.1 0.1 0.1 1.5 1 1 1 50 my_soil my_fractal_box``.

.. note::

* Currently (2024) we are not aware of a formulation of Perfectly Matched Layer (PML) absorbing boundary that can specifically handle distributions of material properties (such as those created by fractals) throughout the thickness of the PML, i.e. this is a required area of research. Our PML formulations can work to an extent depending on your modelling scenario and requirements. You may need to increase the thickness of the PML and/or consider tuning the parameters of the PML (:ref:`pml-tuning`) to improve performance for your specific model.

#add_surface_roughness:
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