.. _high_level_api: ******************** High-Level Interface ******************** PropsSI function ---------------- 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 `. An example using ``PropsSI``: .. ipython:: # Import the PropsSI function In [1]: from CoolProp.CoolProp import PropsSI # Saturation temperature of Water at 1 atm in K In [2]: PropsSI('T','P',101325,'Q',0,'Water') More information: * :ref:`Table of inputs to PropsSI function ` * :ref:`More examples of the high-level API ` * :cpapi:`Documentation for all high-level functions exposed ` All :ref:`the wrappers ` wrap this function in exactly the same way. 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. PhaseSI function ---------------- 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. .. ipython:: In [1]: import CoolProp In [5]: CoolProp.CoolProp.PhaseSI('P',101325,'Q',0,'Water') The phase index (as floating point number) can also be obtained using the PropsSI function. In python you would do: .. ipython:: In [1]: import CoolProp In [5]: CoolProp.CoolProp.PropsSI('Phase','P',101325,'Q',0,'Water') where you can obtain the integer indices corresponding to the phase flags using the ``get_phase_index`` function: .. ipython:: In [1]: import CoolProp In [6]: CoolProp.CoolProp.get_phase_index('phase_twophase') # Or for liquid In [6]: CoolProp.CoolProp.get_phase_index('phase_liquid') For a given fluid, the phase can be plotted in T-p coordinates: .. plot:: import matplotlib import numpy as np import CoolProp as CP import matplotlib.pyplot as plt import scipy.interpolate Water = CP.AbstractState("HEOS", "Water") pc = Water.keyed_output(CP.iP_critical) Tc = Water.keyed_output(CP.iT_critical) Tmin = 200 Tmax = 1000 pmax = Water.keyed_output(CP.iP_max) pt = 611.657 Tt = 273.16 fillcolor = 'g' fig = plt.figure(figsize = (6,6)) ax = fig.add_subplot(111) lw = 3 # -------------- # Melting curve # -------------- melt_args = dict(lw = lw, solid_capstyle = 'round') TT = [] PP = list(np.logspace(np.log10(pt), np.log10(pmax),1000)) for p in PP: TT.append(Water.melting_line(CP.iT, CP.iP, p)) #Zone VI for T in np.linspace(max(TT), 355): TT.append(T) theta = T/273.31 pi = 1-1.07476*(1-theta**4.6) p = pi*632.4e6 PP.append(p) plt.plot(TT,PP,'darkblue',**melt_args) # ---------------- # Saturation curve # ---------------- Ts = np.linspace(273.16, Tc, 1000) ps = CP.CoolProp.PropsSI('P','T',Ts,'Q',[0]*len(Ts),'Water',[1]) # ------ # Labels # ------ plt.plot(Ts,ps,'orange',lw = lw, solid_capstyle = 'round') # Critical lines plt.axvline(Tc, dashes = [2, 2]) plt.axhline(pc, dashes = [2, 2]) # Labels plt.text(850, 1e8, 'supercritical',ha= 'center') plt.text(850, 1e5, 'supercritical_gas', rotation = 90) plt.text(450, 1e8, 'supercritical_liquid', rotation = 0, ha = 'center') plt.text(350, 3e6, 'liquid', rotation = 45) plt.text(450, 5e4, 'gas', rotation = 45) plt.ylim(611,1e9) plt.gca().set_yscale('log') plt.gca().set_xlim(240, 1000) plt.ylabel('Pressure [Pa]') plt.xlabel('Temperature [K]') plt.tight_layout() .. _predefined_mixtures: Predefined Mixtures ------------------- 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 .. ipython:: In [1]: import CoolProp as CP In [1]: CoolProp.CoolProp.get_global_param_string('predefined_mixtures').split(',')[0:6] and then to calculate the density of air using the mixture model at 1 atmosphere (=101325 Pa) and 300 K, you could do .. ipython:: In [1]: import CoolProp as CP In [1]: CoolProp.CoolProp.PropsSI('D','P',101325,'T',300,'Air.mix') Exactly the methodology can be used from other wrappers. C++ Sample Code --------------- .. literalinclude:: snippets/propssi.cxx :language: c++ C++ Sample Code Output ---------------------- .. literalinclude:: snippets/propssi.cxx.output .. _Props_Sample: Sample Code ----------- .. ipython:: In [1]: import CoolProp as CP In [1]: print CP.__version__ In [1]: print CP.__gitrevision__ #Import the things you need In [1]: from CoolProp.CoolProp import PropsSI # Specific heat (J/kg/K) of 20% ethylene glycol as a function of T In [2]: PropsSI('C','T',298.15,'P',101325,'INCOMP::MEG-20%') # Density of Air at standard atmosphere in kg/m^3 In [2]: PropsSI('D','T',298.15,'P',101325,'Air') # Saturation temperature of Water at 1 atm In [2]: PropsSI('T','P',101325,'Q',0,'Water') # Saturated vapor density of R134a at 0C In [2]: PropsSI('H','T',273.15,'Q',1,'R134a') # Using properties from CoolProp to get R410A density In [2]: PropsSI('D','T',300,'P',101325,'HEOS::R32[0.697615]&R125[0.302385]') # Using properties from REFPROP to get R410A density In [2]: PropsSI('D','T',300,'P',101325,'REFPROP::R32[0.697615]&R125[0.302385]') # Check that the same as using pseudo-pure In [2]: PropsSI('D','T',300,'P',101325,'R410A') .. _parameter_table: Table of string inputs to PropsSI function ------------------------------------------ .. include:: parameter_table.rst.in