def __call__(self):
zin = np.array([self.LC, (1. - self.LC)])
z, z_mass = Tools_Convert.frac_input(self.MM, zin, self.base)
return (self.p, self.T, z, z_mass)
===================================
@(PRESSURE, TEMPERATURE, GLOBAL MOLAR FRACTION): These are the conditions you are interested to evaluate
===================================
LEGEND:
p: Interested pressure (evaluate the enthalpy for this pressure) [Pa]
T: Interested temperature (evaluate the enthalpy considering this isotherm) [K]
OCR: oil-circulation ratio [-]: it is a mass fraction of oil per total mass mixture
z_mass: global mass fraction
z: global molar fraction
'''
p = 0.3e5 # <=============================== change here
T = (30. + 273.15) # <=============================== change here
LC, base = 0.40, 'mass' # <=============================== change here
zin = np.array([LC, (1. - LC)])
z, z_mass = Tools_Convert.frac_input(MM, zin, base)
'''
=======================================
CREATING OBJECTS - [to a better identification, all objects' names are followed by "_obj"]
=======================================
'''
rr_obj = RachfordRice()
eos_obj = PengRobinsonEos(pC, Tc, AcF, omega_a, omega_b, kij)
michelsen_obj = Michelsen()
flash_obj = Flash(max_iter=50, tolerance=1.0e-13, print_statistics=False)
prop_obj = Properties(pC, Tc, AcF, omega_a, omega_b, kij)
def getting_the_results_from_FlashAlgorithm_main(p, T, pC, Tc, AcF, z):
initial_K_values = calculate_K_values_wilson(p, T, pC, Tc, AcF)
Building the isotherm and molar concentration to feed the code. Why does it necessary?
Because Pb = Pb @(T, z): We want Pb for a specific global molar fraction and isotherm
=========================================================================================================
LEGEND:
T: Interested temperature (evaluate the enthalpy considering this isotherm) [K]
LC: Lighter component of your binary mixture
base: It is the base of your fraction, i.e., you must specify 'molar' ou 'mass'
z_mass: global {mass} fraction
z: global {molar} fraction
'''
T = 520. #(40. + 273.15) # <=================================== change here
LC, base = 0.10, 'mass' # <=============================== change here
zin = np.array([LC, (1. - LC)])
z, z_mass = Tools_Convert.frac_input(BubbleP.MM, zin, base)
'''
=========================================================================================================
CHANGE HERE (II)
BUILDING A RANGE: this 4 lines below it is necessary to create a range of pressure necessary in...
... executable() function.
To do this it's necessary to import the function calculate_pressure_guess()...
... from BubbleP.py
VERY IMPORTANT!: the step size determines how close we are to the correct root. So,
smaller step produces more precise results
=========================================================================================================
LEGEND:
pG: Guess pressure [Pa] - It is necessary to initialize the search for correct bubble pressure