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Added notes for new incompressibles

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Jorrit Wronski
2019-04-13 14:45:20 +02:00
parent 5d3252d255
commit dae83fd2e2
1 changed files with 28 additions and 2 deletions
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Web/fluid_properties/Incompressibles.rst
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@@ -432,7 +432,7 @@ which can be used to model absorption chillers.
For slurry ice, the concentration :math:`x` refers to the solid content and the
heat capacity includes the heat of fusion. It might be necessary to adjust the
solid content during heat transfer. The implementation is based on the data
available in `SecCool <http://en.ipu.dk/Indhold/refrigeration-and-energy-technology/seccool.aspx>`_,
available in `SecCool <https://www.ipu.dk/products/seccool>`_,
which was originally recorded at the Danish Technological Institute `(DTI) <http://www.dti.dk/>`_.
@@ -444,4 +444,30 @@ which was originally recorded at the Danish Technological Institute `(DTI) <http
properties for all incompressible fluids covering the whole temperature range
for each fluid. The original
:download:`PDF version</_static/fluid_properties/incompressibles_consistency.pdf>`
is also available for download.
is also available for download.
Adding New Fluids
-----------------
To add a fluid to the backend for incompressible fluids, you have to have the tabulated
property data available. Pure fluids are added to the ``PureFluids.py`` and binary
mixtures, like aqueous mixtures, have to be added to the ``SolutionFLuids.py``.
The basic state variable for incompressible fluids is temperature, which should be provided
as a one-dimensional numpy array with length :math:`N`. For pure fluids, all properties should match
this temperature array in size since there is a 1-to-1 relation between the temperature points
and the other quantities.
For binary mixtures, you also need a composition vector to define the data points properly.
This composition vector is also a one-dimensional numpy array of the lenghth :math:`M` and forms the
second axis for your property space with :math:`N \times M` data points.
Note that all properties have to have the same grid in terms of temperature and composition.
Once you haver added your fluid data, you can regenrate the JSON files with the fitted
parameters by running the script located at ``dev/incompressible_liquids/all_incompressibles.py``.
Your new fluid is now part of the codebase and should be available to all CoolProp functions as
soon as you recompile the sources.