how_to_use_a_property_model.rst

How to use a property model

The example below shows how to use a property model and display outputs for a state block. Property models allow users to model the chemical and physical properties of simple systems without the use of unit models.

.. testsetup::

   # quiet idaes logs
   import idaes.logger as idaeslogger
   idaeslogger.getLogger('ideas.core').setLevel('CRITICAL')
   idaeslogger.getLogger('idaes.init').setLevel('CRITICAL')

.. testcode::

    # Import concrete model from Pyomo
    from pyomo.environ import ConcreteModel
    # Import flowsheet block from IDAES core
    from idaes.core import FlowsheetBlock
    # Import solver from IDAES core
    from idaes.core.solvers import get_solver
    # Import NaCl property model
    import watertap.property_models.NaCl_prop_pack as props
    # Import utility tool for calculating scaling factors
    import idaes.core.util.scaling as iscale

    # Create a concrete model, flowsheet, and NaCl property parameter block.
    m = ConcreteModel()
    m.fs = FlowsheetBlock(dynamic=False)
    m.fs.properties = props.NaClParameterBlock()

    # Build the state block and specify a time (0 = steady state).
    m.fs.state_block = m.fs.properties.build_state_block([0])

    # Specify the state variables of the stream.
    feed_flow_mass = 1
    feed_mass_frac_NaCl = 0.035
    feed_mass_frac_H2O = 1 - feed_mass_frac_NaCl
    feed_pressure = 50e5
    feed_temperature = 298.15

    m.fs.state_block[0].flow_mass_phase_comp['Liq', 'NaCl'].fix(feed_flow_mass * feed_mass_frac_NaCl)
    m.fs.state_block[0].flow_mass_phase_comp['Liq', 'H2O'].fix(feed_flow_mass * feed_mass_frac_H2O)
    m.fs.state_block[0].pressure.fix(feed_pressure)
    m.fs.state_block[0].temperature.fix(feed_temperature)

    # Set scaling factors for component mass flowrates (variable * scaling factor should be between 0.01 and 100).
    m.fs.properties.set_default_scaling('flow_mass_phase_comp', 1, index=('Liq', 'H2O'))
    m.fs.properties.set_default_scaling('flow_mass_phase_comp', 1e2, index=('Liq', 'NaCl'))
    iscale.calculate_scaling_factors(m.fs)

    # "Touch" build-on-demand variables so that they are created. If these properties are not touched before running the solver, they will not be calculated, and the output would only display their initial values instead of their actual values.
    m.fs.state_block[0].dens_mass_phase['Liq']
    m.fs.state_block[0].conc_mass_phase_comp['Liq', 'NaCl']
    m.fs.state_block[0].flow_vol_phase['Liq']
    m.fs.state_block[0].molality_phase_comp['Liq', 'NaCl']
    m.fs.state_block[0].visc_d_phase['Liq']
    m.fs.state_block[0].diffus_phase_comp['Liq', 'NaCl']
    m.fs.state_block[0].enth_mass_phase['Liq']
    m.fs.state_block[0].pressure_osm_phase['Liq']

    # Create the solver object.
    solver = get_solver()

    # Solve the model and display the output.
    solver.solve(m, tee=False)
    m.fs.state_block[0].display()

A portion of the displayed output is shown below.

.. testoutput::

   Block fs.state_block[0]

     Variables:
       flow_mass_phase_comp : Mass flow rate
           Size=2, Index=fs.properties.phase_list*fs.properties.component_list, Units=kg/s
           Key             : Lower : Value : Upper : Fixed : Stale : Domain
            ('Liq', 'H2O') :   0.0 : 0.965 :  None :  True :  True : NonNegativeReals
           ('Liq', 'NaCl') :   0.0 : 0.035 :  None :  True :  True : NonNegativeReals
       temperature : State temperature
           Size=1, Index=None, Units=K
           Key  : Lower  : Value  : Upper  : Fixed : Stale : Domain
           None : 273.15 : 298.15 : 373.15 :  True :  True : NonNegativeReals
       ...