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PC_SAFT_v3.py
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PC_SAFT_v3.py
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import numpy as np
from scipy.optimize import root
class PCSAFT_v3:
a_ni = np.array([[0.9105631445, -0.3084016918, -0.0906148351],
[0.6361281449, 0.1860531159, 0.4527842806],
[2.6861347891, -2.5030047259, 0.5962700728],
[-26.547362491, 21.419793629, -1.7241829131],
[97.759208784, -65.255885330, -4.1302112531],
[-159.59154087, 83.318680481, 13.776631870],
[91.297774084, -33.746922930, -8.6728470368]])
a_ni = a_ni.T
b_ni = np.array([[0.7240946941, -0.5755498075, 0.0976883116],
[2.2382791861, 0.6995095521, -0.2557574982],
[-4.0025849485, 3.8925673390, -9.1558561530],
[-21.003576815, -17.215471648, 20.642075974],
[26.855641363, 192.67226447, -38.804430052],
[206.55133841, -161.82646165, 93.626774077],
[-355.60235612, -165.20769346, -29.666905585]])
b_ni = b_ni.T
kb = 1.380649e-23 # J/K
N_A = 6.0221e23 # 1/mol
R = 8.314 # J/mol-K
π = np.pi
def __init__(self, T, z, prop_dic, phase='liquid', η=None, P_sys=None):
m = prop_dic['m']
σ = prop_dic['s']
ϵ_k = prop_dic['e']
κ_AB = prop_dic['vol_a']
ϵ_AB_k = prop_dic['e_assoc']
k_ij = prop_dic['k_ij']
# Parameters
self.T = T
self.T_og = T
self.z = z
self.z_og = z
self.m = m
self.k = len(σ)
self.σ = σ
self.ϵ_k = ϵ_k
self.κ_AB = κ_AB
self.ϵ_AB_k = ϵ_AB_k
self.phase = phase
self.k = len(z)
k = self.k
# --------------------------------------- Intermediates --------------------------------------- #
self.σ_ij = np.array([[1 / 2 * (σ[i] + σ[j]) for j in range(k)] for i in range(k)])
self.ϵ_ij = np.array([[(ϵ_k[i] * ϵ_k[j]) ** (1 / 2) * (1 - k_ij[i][j]) for j in range(k)] for i in range(k)])
self.κ_AB_ij = np.array(
[[(κ_AB[i] * κ_AB[j]) ** (1 / 2) * ((σ[i] * σ[j]) / (1 / 2 * (σ[i] * σ[j]))) ** 3 for j in range(k)] for i
in range(k)])
self.ϵ_AB_ij = np.array([[(ϵ_AB_k[i] + ϵ_AB_k[j]) / 2 for j in range(k)] for i in range(k)])
if P_sys is not None:
self.P_sys = P_sys
self.f_find_η()
elif P_sys is None and η is not None:
self.η = η
self.ρ = self.f_ρ(z=z, T=T, η=η)
elif P_sys is None and η is None:
if phase == 'liquid':
self.η = .4
elif phase == 'vapor':
self.η = .01
print('''
Warning, a default η had to be defined based on the given phase
since so system pressure was given to iteratively find η
''')
def f_m_bar(self, z=None):
if z is None:
z = self.z
m = self.m
return sum(z * m)
def f_d(self, T=None):
if T is None:
T = self.T
σ = self.σ
ϵ_k = self.ϵ_k
return σ * (1 - .12 * np.exp(-3 * ϵ_k / T))
def f_ρ(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
d = self.f_d(T=T)
m = self.m
k = self.k
return 6 / self.π * η * (sum([z[i] * m[i] * d[i] ** 3 for i in range(k)])) ** (-1)
def f_v(self, ρ=None):
if ρ is None:
ρ = self.ρ
return self.N_A * 10 ** -30 / ρ
def f_ξ(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
d = self.f_d(T=T)
m = self.m
return np.array([self.π / 6 * ρ * np.sum([z[i] * m[i] * d[i] ** n for i in range(self.k)]) for n in range(4)])
def f_g_hs_ij(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
d = self.f_d(T=T)
ξ = self.f_ξ(z=z, T=T, ρ=ρ)
return np.array([[(1 / (1 - ξ[3])) +
((d[i] * d[j] / (d[i] + d[j])) * 3 * ξ[2] / (1 - ξ[3]) ** 2) +
((d[i] * d[j] / (d[i] + d[j])) ** 2 * 2 * ξ[2] ** 2 / (1 - ξ[3]) ** 3)
for j in range(self.k)]
for i in range(self.k)])
def f_d_ij(self, T=None):
if T is None:
T = self.T
d = self.f_d(T=T)
return np.array([[1 / 2 * (d[i] + d[j]) for j in range(self.k)] for i in range(self.k)])
def f_Δ_AB_ij(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
d_ij = self.f_d_ij(T=T)
g_hs_ij = self.f_g_hs_ij(z=z, T=T, ρ=ρ)
return np.array([[d_ij[i][j] ** 3 * g_hs_ij[i][j] * self.κ_AB_ij[i][j] * (np.exp(self.ϵ_AB_ij[i][j] / T) - 1)
for j in range(self.k)] for i in range(self.k)])
def f_a_hs(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
ξ = self.f_ξ(z=z, T=T, ρ=ρ)
return 1 / ξ[0] * (3 * ξ[1] * ξ[2] / (1 - ξ[3]) + ξ[2] ** 3 / (ξ[3] * (1 - ξ[3]) ** 2) + (
ξ[2] ** 3 / ξ[3] ** 2 - ξ[0]) * np.log(1 - ξ[3]))
def f_a_hc(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
k = self.k
m = self.m
m_bar = self.f_m_bar(z=z)
g_hs_ij = self.f_g_hs_ij(z=z, T=T, ρ=ρ)
a_hs = self.f_a_hs(z=z, T=T, ρ=ρ)
return m_bar * a_hs - sum([z[i] * (m[i] - 1) * np.log(g_hs_ij[i][i]) for i in range(k)])
def f_a_disp(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
a_ni = self.a_ni
b_ni = self.b_ni
π = self.π
k = self.k
m = self.m
η = self.f_ξ(z=z, T=T, ρ=ρ)[-1]
m_bar = self.f_m_bar(z=z)
ϵ_ij = self.ϵ_ij
σ_ij = self.σ_ij
a = a_ni[0] + (m_bar - 1) / m_bar * a_ni[1] + (m_bar - 1) / m_bar * (m_bar - 2) / m_bar * a_ni[2]
b = b_ni[0] + (m_bar - 1) / m_bar * b_ni[1] + (m_bar - 1) / m_bar * (m_bar - 2) / m_bar * b_ni[2]
I1 = [a[i] * η ** i for i in range(7)]
I2 = [b[i] * η ** i for i in range(7)]
I1 = np.sum(I1)
I2 = np.sum(I2)
Σ_i = 0
for i in range(k):
Σ_j = 0
for j in range(k):
Σ_j += z[i] * z[j] * m[i] * m[j] * (ϵ_ij[i][j] / T) * σ_ij[i][j] ** 3
Σ_i += Σ_j
Σ_1 = Σ_i
Σ_i = 0
for i in range(k):
Σ_j = 0
for j in range(k):
Σ_j += z[i] * z[j] * m[i] * m[j] * (ϵ_ij[i][j] / T) ** 2 * σ_ij[i][j] ** 3
Σ_i += Σ_j
Σ_2 = Σ_i
C1 = (1 + m_bar * (8 * η - 2 * η ** 2) / (1 - η) ** 4 + (1 - m_bar) * (
20 * η - 27 * η ** 2 + 12 * η ** 3 - 2 * η ** 4) / ((1 - η) * (2 - η)) ** 2) ** -1
return -2 * π * ρ * I1 * Σ_1 - π * ρ * m_bar * C1 * I2 * Σ_2
def f_a_assoc(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
k = self.k
ϵ_AB_k = self.ϵ_AB_k
Δ_AB_ij = self.f_Δ_AB_ij(z=z, T=T, ρ=ρ)
def XA_find(XA_guess, n, Δ_AB_ij, ρ, z):
# m = int(XA_guess.shape[1] / n)
AB_matrix = np.asarray([[0., 1.],
[1., 0.]])
Σ_2 = np.zeros((n,), dtype='float_')
XA = np.zeros_like(XA_guess)
for i in range(n):
Σ_2 = 0 * Σ_2
for j in range(n):
Σ_2 += z[j] * (XA_guess[j, :] @ (Δ_AB_ij[i][j] * AB_matrix))
XA[i, :] = 1 / (1 + ρ * Σ_2)
return XA
a_sites = 2 # 2B association?
i_assoc = []
for i in range(len(ϵ_AB_k)):
if ϵ_AB_k[i] != 0:
i_assoc.append(i)
z_new = []
for i in i_assoc:
z_new.append(z[i])
n_assoc = len(i_assoc)
if n_assoc == 0 or n_assoc == 1:
return 0
XA = np.zeros((n_assoc, a_sites), dtype='float_')
ctr = 0
dif = 1000.
XA_old = np.copy(XA)
while (ctr < 500) and (dif > 1e-9):
ctr += 1
XA = XA_find(XA, n_assoc, Δ_AB_ij, ρ, z_new)
dif = np.sum(abs(XA - XA_old))
XA_old[:] = XA
XA = XA.flatten()
return sum([z[i] * sum([np.log(XA[j] - 1 / 2 * XA[j] + 1 / 2) for j in range(len(XA))]) for i in range(k)])
def f_a_ion(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
return 0
def f_a_res(self, z=None, T=None, ρ=None):
if z is None:
z = self.z
if T is None:
T = self.T
if ρ is None:
ρ = self.ρ
a_hc = self.f_a_hc(z=z, T=T, ρ=ρ)
a_disp = self.f_a_disp(z=z, T=T, ρ=ρ)
a_assoc = self.f_a_assoc(z=z, T=T, ρ=ρ)
a_ion = self.f_a_ion(z=z, T=T, ρ=ρ)
return a_hc + a_disp + a_assoc + a_ion
def f_da_dη(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
δ = .01
h = η * δ
a_res_1 = self.f_a_res(z=z, T=T, ρ=self.f_ρ(z=z, T=T, η=η - 2 * h))
a_res_2 = self.f_a_res(z=z, T=T, ρ=self.f_ρ(z=z, T=T, η=η - 1 * h))
a_res_3 = self.f_a_res(z=z, T=T, ρ=self.f_ρ(z=z, T=T, η=η + 1 * h))
a_res_4 = self.f_a_res(z=z, T=T, ρ=self.f_ρ(z=z, T=T, η=η + 2 * h))
return (a_res_1 - 8 * a_res_2 + 8 * a_res_3 - a_res_4) / (12 * h)
def f_da_dT(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
δ = .01
h = T * δ
ρ = self.f_ρ(z=z, T=T, η=η)
a_res_1 = self.f_a_res(z=z, T=T - 2 * h, ρ=ρ)
a_res_2 = self.f_a_res(z=z, T=T - 1 * h, ρ=ρ)
a_res_3 = self.f_a_res(z=z, T=T + 1 * h, ρ=ρ)
a_res_4 = self.f_a_res(z=z, T=T + 2 * h, ρ=ρ)
return (a_res_1 - 8 * a_res_2 + 8 * a_res_3 - a_res_4) / (12 * h)
def f_da_dx(self, j, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
δ = .01
h = z[j] * δ
diff = [-2 * h, -h, h, 2 * h]
z_new = np.zeros((4, 3))
for n in range(4):
for i in range(len(z)):
if i == j:
z_new[n, i] = z[i] + diff[n]
else:
z_new[n, i] = z[i]
ρ = self.f_ρ(z=z, T=T, η=η)
a_res_1 = self.f_a_res(z=z_new[0], T=T, ρ=ρ)
a_res_2 = self.f_a_res(z=z_new[1], T=T, ρ=ρ)
a_res_3 = self.f_a_res(z=z_new[2], T=T, ρ=ρ)
a_res_4 = self.f_a_res(z=z_new[3], T=T, ρ=ρ)
return (a_res_1 - 8 * a_res_2 + 8 * a_res_3 - a_res_4) / (12 * h)
def f_Z(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
da_dη = self.f_da_dη(z=z, T=T, η=η)
return 1 + η * da_dη
def f_P(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
T = self.T
Z = self.f_Z(z=z, T=T, η=η)
ρ = self.f_ρ(z=z, T=T, η=η)
kb = self.kb
return Z * kb * T * ρ * 10 ** 30
def f_find_η(self):
def f(ηg):
ηg = float(ηg)
P = self.f_P(η=ηg)
P_sys = self.P_sys
return (P - P_sys) / 100000
phase = self.phase
if phase == 'liquid':
ηg = .5
elif phase == 'vapor':
ηg = 10e-10
else:
print('Phase spelling probably wrong or phase is missing')
ηg = .01
res = root(f, np.array([ηg]))
η = res.x[0]
message = res.message
if message != 'The solution converged.':
print(message)
self.η = η
self.ρ = self.f_ρ()
def f_h_res(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
Z = self.f_Z(z=z, T=T, η=η)
da_dT = self.f_da_dT(z=z, T=T, η=η)
return -T * da_dT + (Z - 1)
def f_s_res(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
a_res = self.f_a_res(z=z, T=T, η=η)
Z = self.f_Z(z=z, T=T, η=η)
da_dT = self.f_da_dT(z=z, T=T, η=η)
return -T * (da_dT + a_res / T) + np.log(Z)
def f_g_res(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
ρ = self.f_ρ(z=z, T=T, η=η)
a_res = self.f_a_res(z=z, T=T, ρ=ρ)
Z = self.f_Z(z=z, T=T, η=η)
return a_res + (Z - 1) - np.log(Z)
def f_μ_res(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
ρ = self.f_ρ(z=z, T=T, η=η)
a_res = self.f_a_res(z=z, T=T, ρ=ρ)
Z = self.f_Z(z=z, T=T, η=η)
da_dx = np.array([self.f_da_dx(i, z=z, T=T, η=η) for i in range(self.k)])
Σ = np.sum(z * da_dx)
μ_res = np.array([(a_res + (Z - 1) + da_dx[i] - Σ) * self.kb * T for i in range(len(z))])
return μ_res
def f_φ(self, z=None, T=None, η=None):
if z is None:
z = self.z
if T is None:
T = self.T
if η is None:
η = self.η
T = self.T
μ_res = self.f_μ_res(z=z, T=T, η=η)
Z = self.f_Z(z=z, T=T, η=η)
return np.exp(μ_res / self.kb / T - np.log(Z))
def flash_v3(x, y, T, P, prop_dic, flash_type='Bubble_T'):
def eqs_to_solve(x, y, T, P):
mix_l = PCSAFT_v3(T, x, prop_dic, phase='liquid', P_sys=P)
mix_v = PCSAFT_v3(T, y, prop_dic, phase='vapor', P_sys=P)
φ_l = mix_l.f_φ()
φ_v = mix_v.f_φ()
eqs = [(y[i] * φ_v[i] - x[i] * φ_l[i]) for i in range(len(y))]
if flash_type[:-2] == 'Bubble':
eqs.append(1 - np.sum([y[i] for i in range(len(y))]))
elif flash_type[:-2] == 'Dew':
eqs.append(1 - np.sum([x[i] for i in range(len(x))]))
else:
print('Wrong Flash Type')
return eqs
def f(w):
if flash_type == 'Bubble_T':
return eqs_to_solve(x, w[:-1], T, w[-1])
elif flash_type == 'Bubble_P':
return eqs_to_solve(x, w[:-1], w[-1], P)
elif flash_type == 'Dew_T':
return eqs_to_solve(w[:-1], y, T, w[-1])
elif flash_type == 'Dew_P':
return eqs_to_solve(w[:-1], y, w[-1], P)
else:
print('Wrong Flash Type')
return None
if flash_type == 'Bubble_T':
guesses = list(y) + [P]
elif flash_type == 'Bubble_P':
guesses = list(y) + [T]
elif flash_type == 'Dew_T':
guesses = list(x) + [P]
elif flash_type == 'Dew_P':
guesses = list(x) + [T]
else:
print('Wrong Flash Type')
guesses = []
options = {'xtol': 1e-4, }
ans = root(f, np.array([guesses]), options=options).x
y_CO2, y_MEA, y_H2O = ans[:-1]
P = ans[-1]
P_CO2 = y_CO2*P
return P_CO2
if __name__ == '__main__':
x = [.1, .3, .6]
T = 233.15
yg = [.1, .3, .6]
Pg = 1e5
prop_dic = {
'CO2': {'m_seg': 1, 'sigma': 3.7039, 'u_K': 150.03,
'kappa_AB': 0,
'eps_AB_k': 0},
'MEA': {'m_seg': 1.6069, 'sigma': 3.5206, 'u_K': 191.42,
'kappa_AB': 0, # .037470,
'eps_AB_k': 0, # 2586.3,
},
'H2O': {'m_seg': 2.0020, 'sigma': 3.6184, 'u_K': 208.11,
'kappa_AB': 0, # .04509,
'eps_AB_k': 0, # 2425.67
},
}
m = np.array([1, 1.6069, 2.0020]) # Number of segments
σ = np.array([3.7039, 3.5206, 3.6184]) # Temperature-Independent segment diameter σ_i (Aᵒ)
ϵ_k = np.array([150.03, 191.42, 208.11]) # Depth of pair potential / Boltzmann constant (K)
k_ij = np.array([[0.00E+00, 3.00E-04, 1.15E-02],
[3.00E-04, 0.00E+00, 5.10E-03],
[1.15E-02, 5.10E-03, 0.00E+00]])
print(flash_v3(x, yg, T, Pg, prop_dic, k_ij))