import numpy as np
from openpnm.models.phase import _phasedocs
__all__ = [
'water_correlation',
'gas_pure_gismr',
'liquid_pure_gismr',
'liquid_pure_sr',
'gas_mixture_whz',
'liquid_mixture_DIPPR9H',
]
[docs]
@_phasedocs
def water_correlation(
phase,
T="pore.temperature",
salinity="pore.salinity",
):
r"""
Calculates thermal conductivity of pure water or seawater at atmospheric
pressure using the correlation given [1].
Values at temperature higher the normal boiling temperature are calculated
at the saturation pressure.
Parameters
----------
%(phase)s
%(T)s
%(salinity)s
Returns
-------
value : ndarray
A numpy ndarray containing thermal conductivity of water/seawater in [W/m.K]
Notes
-----
T must be in K, and S in g of salt per kg of phase, or ppt (parts per
thousand). The correlation is valid for 273 < T < 453 K and
0 < S < 160 g/kg within 3 percent accuracy.
References
----------
[1] D. T. Jamieson, and J. S. Tudhope, Desalination, 8, 393-401, 1970.
"""
T = phase[T]
if salinity in phase.keys():
S = phase[salinity]
else:
S = 0
T68 = 1.00024 * T # convert from T_90 to T_68
SP = S / 1.00472 # convert from S to S_P
k_sw = 0.001 * (
10
** (
np.log10(240 + 0.0002 * SP)
+ 0.434
* (2.3 - (343.5 + 0.037 * SP) / T68)
* ((1 - T68 / (647.3 + 0.03 * SP))) ** (1 / 3)
)
)
value = k_sw
return value
[docs]
@_phasedocs
def gas_pure_gismr(
phase,
T='pore.temperature',
MW='param.molecular_weight',
Tb='param.boiling_temperature',
Pc='param.critical_pressure',
omega='param.acentric_factor',
):
r"""
Calculate the thermal conductivty of a pure gas using the correlation in
[1]
Parameters
----------
%(phase)s
%(T)s
%(MW)s
%(Tb)s
%(Pc)s
%(omega)s
Returns
-------
References
----------
[1] gharagheizi method: doi:10.1002/aic.13938
"""
T = phase[T]
MW = phase[MW]
Tb = phase[Tb]
# The following correction suggested by chemicals package author
Pc = phase[Pc]/10000
omega = phase[omega]
B = (T + (2.0*omega + 2.0*T - 2.0*T*(2.0*omega + 3.2825)/Tb + 3.2825)
/ (2.0*omega + T - T*(2.0*omega + 3.2825)/Tb + 3.2825)
- T*(2.0*omega + 3.2825)/Tb)
A = (2*omega + T - (2*omega + 3.2825)*T/Tb + 3.2825)/(0.1*MW*Pc*T) \
* (3.9752*omega + 0.1*Pc + 1.9876*B + 6.5243)**2
k = 7.9505e-4 + 3.989e-5*T - 5.419e-5*MW + 3.989e-5*A
return k
[docs]
@_phasedocs
def liquid_pure_gismr(
phase,
T='pore.temperature',
MW='param.molecular_weight',
Tb='param.boiling_temperature',
Pc='param.critical_pressure',
omega='param.acentric_factor',
):
r"""
Calculates the thermal conductivity of a pure liquid using the correlation
in [1]
Parameters
----------
%(phase)s
%(T)s
%(MW)s
%(Tb)s
%(Pc)s
%(omega)s
Returns
-------
References
----------
[1] gharagheizi method: doi:10.1002/aic.13938
"""
T = phase[T]
MW = phase[MW]
Tb = phase[Tb]
Pc = phase[Pc]/100000
omega = phase[omega]
B = 16.0407*MW + 2.0*Tb - 27.9074
A = 3.8588*(MW**8)*(1.0045*B + 6.5152*MW - 8.9756)
k = (1e-4)*(10*omega + 2*Pc - 2*T + 4 + 1.908*(Tb + 1.009*(B**2)/(MW**2))
+ 3.9287*(MW**4)/(B**4) + A/(B**8))
return k
[docs]
@_phasedocs
def liquid_pure_sr(
phase,
T="pore.temperature",
Tc='param.critical_temperature',
MW='param.molecular_weight',
Tb='param.boiling_temperature',
):
r"""
Calculates the thermal conductivity of a pure liquid using the correlation
in [1]
Parameters
----------
%(phase)s
%(T)s
%(Tc)s
%(MW)s
%(Tb)s
Returns
-------
value : ndarray
A numpy ndarray containing thermal conductivity values in [W/m.K]
References
----------
[1] Sato et al
"""
T = phase[T]
Tc = phase[Tc]
MW = phase[MW]
Tbr = phase[Tb]/Tc
Tr = T / Tc
value = ((1.1053 / ((MW) ** 0.5)) * (3 + 20 * (1 - Tr) ** (2 / 3))
/ (3 + 20 * (1 - Tbr) ** (2 / 3)))
return value
@_phasedocs
def liquid_mixture_DIPPR9I(
phase,
rhos='pore.density.*',
ks='pore.thermal_conductivity.*',
MWs='param.molecular_weight.*',
):
r"""
Calculates the thermal conductivity of a liquid mixture using the
correlation in [1]
Parameters
----------
%(phase)s
%(rhos)s
%(ks)s
%(MWs)s
Returns
-------
References
----------
[1] DIPPR9I
"""
raise NotImplementedError("This function is not ready yet")
from chemicals import rho_to_Vm
xs = phase['pore.mole_fraction']
kLs = phase.get_comp_vals(ks)
# kL = numba_vectorized.DIPPR9I(xs, kLs) # Another one that doesn't work
Vm = [rho_to_Vm(c.get_comp_vals(rhos), c.get_comp_vals(MWs))
for c in phase.components.keys()]
denom = np.sum([xs[i]*Vm[i] for i in range(len(xs))], axis=0)
phis = np.array([xs[i]*Vm[i] for i in range(len(xs))])/denom
kij = 2/np.sum([1/kLs[i] for i in range(len(xs))], axis=0)
kmix = np.zeros_like(xs[0])
N = len(xs)
for i in range(N):
for j in range(N):
kmix += phis[i]*phis[j]*kij
return kmix
[docs]
@_phasedocs
def liquid_mixture_DIPPR9H(
phase,
ks='pore.thermal_conductivity.*',
MWs='param.molecular_weight.*',
):
r"""
Calculates the thermal conductivity of a liquid mixture using the
correlation in [1]
Parameters
----------
%(phase)s
%(ks)s
%(MWs)s
Returns
-------
References
----------
[1] DIPPR9H
"""
xs = phase['pore.mole_fraction']
MW = phase.get_comp_vals(MWs)
ks = phase.get_comp_vals(ks)
num = np.vstack([xs[k]*MW[k]/(ks[k]**2) for k in xs.keys()]).sum(axis=0)
denom = np.vstack([xs[k]*MW[k] for k in xs.keys()]).sum(axis=0)
temp = num/denom
kmix = (1/temp)**0.5
return kmix
[docs]
@_phasedocs
def gas_mixture_whz(
phase,
T='pore.temperature',
ks='pore.thermal_conductivity.*',
MWs='param.molecular_weight.*',
):
r"""
Calculates the viscosity of a gas mixture using the correlation in [1]
Parameters
----------
%(phase)s
%(T)s
%(ks)s
%(MWs)s
Returns
-------
References
----------
[1] Wassiljew, Herning & Zipperer
"""
T = phase[T]
ys = phase['pore.mole_fraction']
kGs = phase.get_comp_vals(ks)
MWs = phase.get_comp_vals(MWs)
kmix = np.zeros_like(T)
for i, ki in enumerate(ys.keys()):
num = ys[ki]*kGs[ki]
denom = 0.0
for j, kj in enumerate(ys.keys()):
A = np.sqrt(MWs[kj]/MWs[ki])
denom += ys[ki]*A
kmix += num/denom
return kmix
