mirror of
https://github.com/CoolProp/CoolProp.git
synced 2026-01-19 19:09:00 -05:00
8a32d79ba4
See https://github.com/CoolProp/CoolProp/issues/280 Signed-off-by: Ian Bell <ian.h.bell@gmail.com>
208 lines
6.2 KiB
ReStructuredText
208 lines
6.2 KiB
ReStructuredText
.. _high_level_api:
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********************
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High-Level Interface
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********************
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PropsSI function
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----------------
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For many users, all that is needed is a simple call to the ``PropsSI`` function for pure fluids, pseudo-pure fluids and mixtures. For humid air properties, see :ref:`Humid air properties <Humid-Air>`. An example using ``PropsSI``:
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.. ipython::
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# Import the PropsSI function
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In [1]: from CoolProp.CoolProp import PropsSI
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# Saturation temperature of Water at 1 atm in K
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In [2]: PropsSI('T','P',101325,'Q',0,'Water')
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More information:
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* :ref:`Table of inputs to PropsSI function <parameter_table>`
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* :ref:`More examples of the high-level API <Props_Sample>`
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* :cpapi:`Documentation for all high-level functions exposed <CoolPropLib.h>`
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All :ref:`the wrappers <wrappers>` wrap this function in exactly the same way.
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For pure and pseudo-pure fluids, two state points are required to fix the state. The equations of state are based on :math:`T` and :math:`\rho` as state variables, so :math:`T, \rho` will always be the fastest inputs. :math:`P,T` will be a bit slower (3-10 times), and then comes inputs where neither :math:`T` nor :math:`\rho` are given, like :math:`p,h`. They will be much slower. If speed is an issue, you can look into table-based interpolation methods using TTSE or bicubic interpolation.
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PhaseSI function
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----------------
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It can be useful to know what the phase of a given state point is. A high-level function called ``PhaseSI`` has been implemented to allow for access to the phase.
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.. ipython::
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In [1]: import CoolProp
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In [5]: CoolProp.CoolProp.PhaseSI('P',101325,'Q',0,'Water')
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The phase index (as floating point number) can also be obtained using the PropsSI function. In python you would do:
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.. ipython::
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In [1]: import CoolProp
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In [5]: CoolProp.CoolProp.PropsSI('Phase','P',101325,'Q',0,'Water')
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where you can obtain the integer indices corresponding to the phase flags using the ``get_phase_index`` function:
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.. ipython::
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In [1]: import CoolProp
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In [6]: CoolProp.CoolProp.get_phase_index('phase_twophase')
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# Or for liquid
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In [6]: CoolProp.CoolProp.get_phase_index('phase_liquid')
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For a given fluid, the phase can be plotted in T-p coordinates:
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.. plot::
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import matplotlib
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import numpy as np
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import CoolProp as CP
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import matplotlib.pyplot as plt
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import scipy.interpolate
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Water = CP.AbstractState("HEOS", "Water")
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pc = Water.keyed_output(CP.iP_critical)
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Tc = Water.keyed_output(CP.iT_critical)
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Tmin = 200
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Tmax = 1000
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pmax = Water.keyed_output(CP.iP_max)
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pt = 611.657
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Tt = 273.16
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fillcolor = 'g'
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fig = plt.figure(figsize = (6,6))
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ax = fig.add_subplot(111)
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lw = 3
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# --------------
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# Melting curve
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# --------------
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melt_args = dict(lw = lw, solid_capstyle = 'round')
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TT = []
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PP = list(np.logspace(np.log10(pt), np.log10(pmax),1000))
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for p in PP:
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TT.append(Water.melting_line(CP.iT, CP.iP, p))
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#Zone VI
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for T in np.linspace(max(TT), 355):
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TT.append(T)
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theta = T/273.31
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pi = 1-1.07476*(1-theta**4.6)
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p = pi*632.4e6
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PP.append(p)
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plt.plot(TT,PP,'darkblue',**melt_args)
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# ----------------
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# Saturation curve
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# ----------------
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Ts = np.linspace(273.16, Tc, 1000)
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ps = CP.CoolProp.PropsSI('P','T',Ts,'Q',[0]*len(Ts),'Water',[1])
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# ------
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# Labels
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# ------
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plt.plot(Ts,ps,'orange',lw = lw, solid_capstyle = 'round')
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# Critical lines
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plt.axvline(Tc, dashes = [2, 2])
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plt.axhline(pc, dashes = [2, 2])
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# Labels
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plt.text(850, 1e8, 'supercritical',ha= 'center')
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plt.text(850, 1e5, 'supercritical_gas', rotation = 90)
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plt.text(450, 1e8, 'supercritical_liquid', rotation = 0, ha = 'center')
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plt.text(350, 3e6, 'liquid', rotation = 45)
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plt.text(450, 5e4, 'gas', rotation = 45)
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plt.ylim(611,1e9)
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plt.gca().set_yscale('log')
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plt.gca().set_xlim(240, 1000)
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plt.ylabel('Pressure [Pa]')
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plt.xlabel('Temperature [K]')
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plt.tight_layout()
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.. _predefined_mixtures:
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Predefined Mixtures
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-------------------
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A number of predefined mixtures are included in CoolProp. You can retrieve the list of predefined mixtures by calling ``get_global_param_string("predefined_mixtures")`` which will return a comma-separated list of predefined mixtures. In Python, to get the first 5 mixtures, you would do
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.. ipython::
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In [1]: import CoolProp as CP
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In [1]: CoolProp.CoolProp.get_global_param_string('predefined_mixtures').split(',')[0:6]
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and then to calculate the density of air using the mixture model at 1 atmosphere (=101325 Pa) and 300 K, you could do
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.. ipython::
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In [1]: import CoolProp as CP
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In [1]: CoolProp.CoolProp.PropsSI('D','P',101325,'T',300,'Air.mix')
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Exactly the methodology can be used from other wrappers.
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C++ Sample Code
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---------------
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.. literalinclude:: snippets/propssi.cxx
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:language: c++
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C++ Sample Code Output
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----------------------
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.. literalinclude:: snippets/propssi.cxx.output
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.. _Props_Sample:
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Sample Code
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-----------
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.. ipython::
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In [1]: import CoolProp as CP
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In [1]: print CP.__version__
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In [1]: print CP.__gitrevision__
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#Import the things you need
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In [1]: from CoolProp.CoolProp import PropsSI
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# Specific heat (J/kg/K) of 20% ethylene glycol as a function of T
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In [2]: PropsSI('C','T',298.15,'P',101325,'INCOMP::MEG-20%')
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# Density of Air at standard atmosphere in kg/m^3
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In [2]: PropsSI('D','T',298.15,'P',101325,'Air')
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# Saturation temperature of Water at 1 atm
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In [2]: PropsSI('T','P',101325,'Q',0,'Water')
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# Saturated vapor density of R134a at 0C
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In [2]: PropsSI('H','T',273.15,'Q',1,'R134a')
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# Using properties from CoolProp to get R410A density
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In [2]: PropsSI('D','T',300,'P',101325,'HEOS::R32[0.697615]&R125[0.302385]')
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# Using properties from REFPROP to get R410A density
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In [2]: PropsSI('D','T',300,'P',101325,'REFPROP::R32[0.697615]&R125[0.302385]')
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# Check that the same as using pseudo-pure
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In [2]: PropsSI('D','T',300,'P',101325,'R410A')
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.. _parameter_table:
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Table of string inputs to PropsSI function
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------------------------------------------
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.. include:: parameter_table.rst.in |