REFPROP-connector 0.3.13

Tools for launching REFPROP calculation and retrieving results from python

REFPROP connector

REFPROP connector is a tools developed by the SERG research group of the University of Florence for launching REFPROP calculation and retrieving results from python.

In order to use the code you must have both REFPROP and the REFPROP wrappers for Python installed and properly working.

The scope of this library is to make the usage of the refprop wrappers simpler.

Download and installation

The beta version can be downloaded using PIP:

pip install REFPROP_connector

First Steps

Once the installation has been completed the user can import the tool and initialize the connector itself.

from REFPROPConnector import ThermodynamicPoint

tp = ThermodynamicPoint(["air"], [1.])

An important aspects to keep in mind for the initialization:

• A file-dialog could appear the first time that the connector is imported asking the user to select the REFPROP installation folder (usually it's "C:\Program Files (x86)\REFPROP"). Once the executable path has been selected, the program will keep it in memory in order to avoid a new appearance of the file-dialog. The stored executable can be modified calling the following function:

from REFPROPConnector import retreive_RP_exec

retreive_RP_exec()

If you have multiple or conflicting REFPROP installations, you can force the program not to use the default executable path by using the option:

from REFPROPConnector import retreive_RP_exec

retreive_RP_exec(ignore_default=True)

Alternatively you can explicitly provide the installation folder path using

from REFPROPConnector import retreive_RP_exec

retreive_RP_exec(file_path="<your path to RP installation>")

IMPORTANT: Each time you run "retreive_RP_exec" open the program that is executing your python code (such as the Terminal, PyCharm or Spider) in administrator mode otherwise the call may not have any effect.

Basic Usage

Each ThermodynamicPoint class instance represent a thermodynamic state, hence you had to provide at least two indipendent state variables in order to calculate the others.

from REFPROPConnector import ThermodynamicPoint

tp = ThermodynamicPoint(["water"], [1.])

tp.set_variable("P", 0.101325)     # P in MPa (ambient pressure)
tp.set_variable("Q", 0.5)          # vapour quality for multiphase condition

T_sat = tp.get_variable("T")       # saturation temperature in celsius (100 °C)

Abstract Class

AbstractThermodynamicPoint is a class that can be overwritten in order to perform some calculation once both independent state variable have been set. It can be useful for example for the evaluation of the reynolds number for a fluid flowing in a pipe.

from REFPROPConnector import AbstractThermodynamicPoint, RefPropHandler, init_handler
import numpy as np


class TubeSection(AbstractThermodynamicPoint):

    def __init__(self, diam, flow_rate):
        
        self.diam = diam
        self.area = np.pi * np.power(diam / 2, 2)
        self.flow_rate = flow_rate
        self.Re = 0.
        
        refprop = init_handler(

            chosen_subclass=RefPropHandler,
            fluids=["air"], composition=[1]
            
        )

        super().__init__(refprop)

    def other_calculation(self):
        
        mu = self.get_variable("mu") / (10 ** 6)  # conversion uPa*s -> Pa*s
        self.Re = self.flow_rate * self.diam / (self.area * mu)

if __name__ == "__main__":

    section = TubeSection(0.5, 1)
    
    """
    
        The following line will return 0. as the function "other_calculation" 
        is called only when 2 independent state variables are provided 
        
    """
    print(section.get_variable("Re"))   
    
    section.set_variable("P", 0.5)
    section.set_variable("T", 20)
    
    """
    
        The following line will return the actual Reynolds number
        
    """
    print(section.get_variable("Re"))

Unit system and state variable list

Variable that can be calculated can be listed using list_properties method from both ThermodynamicPoint and AbstractThermodynamicPoint (the name is not case-sensitive). Finally, user can also select the unit system to be used in the calculation, a list of possible unit system can be revived calling the method list_unit_systems() (current unit_system will be highlighted):

from REFPROPConnector import ThermodynamicPoint

tp = ThermodynamicPoint(["water"], [1.], unit_system="MASS BASE SI")
tp.list_properties()
tp.list_unit_systems()

Default unit system is SI with C

Metastable Calculation

You can force the state to represent a metastable condition as follows:

from REFPROPConnector import ThermodynamicPoint

tp = ThermodynamicPoint(["water"], [1.], unit_system="MASS BASE SI")
tp.metastability = "liq" # or "vap" for vapour metastable condition

Acceptable keywords for metastability are ["liquid", "liq", "l", ">"] for the liquid metastable state, or ["vap", "vapour", "vapor", "v", "<"] for the vapour state (keywords are not case-sensitive).

Static and Stagnation condition evaluation

You can evaluate either the static point given the total condition and the speed or the stagnation condition given the static ones by using the following commands:

from REFPROPConnector import ThermodynamicPoint

tp = ThermodynamicPoint(["water"], [1.], unit_system="MASS BASE SI")
speed = 300     # m/s
static_point = tp.get_static_point(speed=speed)
total_point = tp.get_stagnation_point(speed=speed)

The speed value must be ginve in m/s!

Diagram Plotter

The DiagramPlotter class can be used to plot a specific state diagram that can be then used to describe state transformations. The diagram can be personalized using the DiagramPlotterOptions class. The following is an example on how to use the class.

from REFPROPConnector import (
    
    ThermodynamicPoint, 
    DiagramPlotter, 
    DiagramPlotterOptions

)

tp = ThermodynamicPoint(["Carbon Dioxide"], [1])
options = DiagramPlotterOptions(

    x_variable="T",
    x_var_range = (0, 150), x_var_log=False,
    y_var_range = (4, 15),
    isoline_ranges={

        "rho": (50, 1000, 25),
        "H": (200, 550, 25)

    }

)
plotter = DiagramPlotter(tp, options=options)
plotter.calculate()

fig, (ax_1) = plt.subplots(1, 1, dpi=200)
fig.set_size_inches(10, 5)
plotter.plot(ax_1)
plt.show()

-------------------------- !!! THIS IS A BETA VERSION !!! --------------------------

please report any bug or problems in the installation to [e-mail]