def report_f_pure(data,options,title,print_options):
n = len(data[0])
f = np.array(menus.flatten(data[0]))
x = np.array(menus.flatten(data[1]))
rho = np.array(menus.flatten(data[2]))
header = str(';%s\n' % ';'.join(rho))
savedir = str('../output/%s' %title)
with open(savedir,'w') as file:
file.write(header)
for i in range(0,n):
lin1 = [str(round(rho[i],9)),str(round(f[i],9))]
lin = ('%s\n' % ';'.join(lin1))
file.write(lin)
def bCPA(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
bCPAs = []
for row in readCSV:
bCPA = float(row[9]) #bCPA parameter
#Organize read values to respective lists
bCPAs.append(bCPA)
#Finding specific bCPAs
bCPAs = menus.flatten(bCPAs)
bCPA_ID = []
#Organizing and fingind specific bCPA parameters
for i in comp:
bCPA_ID.append(bCPAs[i - 1])
return bCPA_ID
def omega(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
omegas = []
for row in readCSV:
omega = float(row[4]) #acentric factor
#Organize read values to respective lists
omegas.append(omega)
#Finding specific omegas
omegas = menus.flatten(omegas)
omega_ID = []
#Organizing and fingind specific acentric factors
for i in comp:
omega_ID.append(omegas[i - 1])
return omega_ID
def Pc(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
Pcs = []
for row in readCSV:
Pc = float(row[3]) #Critical pressure
#Organize read values to respective lists
Pcs.append(Pc)
#Finding specific Pcs
Pcs = menus.flatten(Pcs)
Pc_ID = []
#Organizing and fingind specific critical pressures
for i in comp:
Pc_ID.append(Pcs[i - 1])
return Pc_ID
def phi(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
phis = []
for row in readCSV:
phi = float(row[14]) #phi parameter
#Organize read values to respective lists
phis.append(phi)
#Finding specific phis
phis = menus.flatten(phis)
phi_ID = []
#Organizing and fingind specific phi parameters
for i in comp:
phi_ID.append(phis[i - 1])
return phi_ID
def Tc(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
Tcs = []
for row in readCSV:
Tc = float(row[2]) #Critical Temperature
#Organize read values to respective lists
Tcs.append(Tc)
#Finding specific Tcs
Tcs = menus.flatten(Tcs)
Tc_ID = []
#Organizing and fingind specific critical temperatures
for i in comp:
Tc_ID.append(Tcs[i - 1])
return Tc_ID
def beta(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
betas = []
for row in readCSV:
beta = float(row[12]) #beta parameter
#Organize read values to respective lists
betas.append(beta)
#Finding specific betas
betas = menus.flatten(betas)
beta_ID = []
#Organizing and fingind specific beta parameters
for i in comp:
beta_ID.append(betas[i - 1])
return beta_ID
def L(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
Ls = []
for row in readCSV:
L = float(row[13]) #L parameter
#Organize read values to respective lists
Ls.append(L)
#Finding specific Ls
Ls = menus.flatten(Ls)
L_ID = []
#Organizing and fingind specific L parameters
for i in comp:
L_ID.append(Ls[i - 1])
return L_ID
def c1(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
c1s = []
for row in readCSV:
c1 = float(row[10]) #c1 parameter
#Organize read values to respective lists
c1s.append(c1)
#Finding specific c1s
c1s = menus.flatten(c1s)
c1_ID = []
#Organizing and fingind specific c1 parameters
for i in comp:
c1_ID.append(c1s[i - 1])
return c1_ID
def en(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
ens = []
for row in readCSV:
en = float(row[11]) #en parameter
#Organize read values to respective lists
ens.append(en)
#Finding specific ens
ens = menus.flatten(ens)
en_ID = []
#Organizing and fingind specific en parameters
for i in comp:
en_ID.append(ens[i - 1])
return en_ID
def a0(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
a0s = []
for row in readCSV:
a0 = float(row[8]) #a0 parameter
#Organize read values to respective lists
a0s.append(a0)
#Finding specific a0s
a0s = menus.flatten(a0s)
a0_ID = []
#Organizing and fingind specific a0 parameters
for i in comp:
a0_ID.append(a0s[i - 1])
return a0_ID
def C_antoine(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
Cs = []
for row in readCSV:
C = float(row[7]) #C antoine parameter
#Organize read values to respective lists
Cs.append(C)
#Finding specific Cs
Cs = menus.flatten(Cs)
C_ID = []
#Organizing and fingind specific C antoine parameters
for i in comp:
C_ID.append(Cs[i - 1])
return C_ID
def B_antoine(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
Bs = []
for row in readCSV:
B = float(row[6]) #B antoine parameter
#Organize read values to respective lists
Bs.append(B)
#Finding specific Bs
Bs = menus.flatten(Bs)
B_ID = []
#Organizing and fingind specific B antoine parameters
for i in comp:
B_ID.append(Bs[i - 1])
return B_ID
def A_antoine(ID):
comp = menus.flatten(ID)
with open('properties.csv') as csvfile:
readCSV = csv.reader(csvfile, delimiter=';')
As = []
for row in readCSV:
A = float(row[5]) #A antoine parameter
#Organize read values to respective lists
As.append(A)
#Finding specific As
As = menus.flatten(As)
A_ID = []
#Organizing and fingind specific A antoine parameters
for i in comp:
A_ID.append(As[i - 1])
return A_ID
def cubic_v_roots(coef,R,T,P):
V = []
coef = menus.flatten(coef)
coef = np.array(coef)
alfa = coef[0]
beta = coef[1]
gama = coef[2]
#Newton Raphson to find first root
#Initial guess
V1 = R*T/P
tol = 1e-10
err = tol+1
i = 1
stop = 1.0
while err>tol or i<3:
V1old = V1
F = V1**3+alfa*V1**2+beta*V1+gama
dF = 3*V1**2+2*alfa*V1+beta
V1 = V1 - stop*F/dF
err = abs((V1-V1old)/V1)
i = i+1
if i>50:
stop = stop/1.1
i = 1
#Solve quadratic equation to find other roots
delta = (alfa+V1)**2-4*1*(V1**2+alfa*V1+beta)
if delta>0:
V2 = (-(alfa+V1)+(delta)**0.5)/2
V3 = (-(alfa+V1)-(delta)**0.5)/2
else:
V2 = V1
V3 = V1
V.append(V1)
V.append(V2)
V.append(V3)
return V
def calc_entropy(T,f,P,avdw,rho,h,IDs):
f0 = np.array(menus.flatten(f[0]))
f1 = np.array(menus.flatten(f[1]))
f2 = np.array(menus.flatten(f[2]))
T0 = np.array(menus.flatten(T[0]))
T1 = np.array(menus.flatten(T[1]))
T2 = np.array(menus.flatten(T[2]))
rho0 = np.array(menus.flatten(rho[0]))
rho1 = np.array(menus.flatten(rho[1]))
rho2 = np.array(menus.flatten(rho[2]))
P0 = np.array(menus.flatten(P[0]))
P1 = np.array(menus.flatten(P[1]))
P2 = np.array(menus.flatten(P[2]))
avdw0 = np.array(menus.flatten(avdw[0]))
V0 = 1/rho0
V1 = 1/rho1
V2 = 1/rho2
A0 = f0/rho0 #MPa.m3/mol
A1 = f1/rho1
A2 = f2/rho2
F0 = A0/(R*T0)
F1 = A1/(R*T1)
F2 = A2/(R*T2)
n = len(P1[0])
#Derivatives
d2AdT2 = (A2 - 2*A1 + A0)/(h**2)
d2FdT2 = (F2 - 2*F1 + F0)/(h**2)
dAdT = (A2 - A0)/(2*h)
dFdT = (F2 - F0)/(2*h)
S_A = -dAdT*1.0e6 # converting from MPa.m3/(mol.K) = 1e-6 J/(mol.K) to J/(mol.K)
S_F = -dFdT # 1/K
S_F = -dAdT/R # converting from MPa.m3/(mol.K) to adimensional
rho = rho[0][0][0]
S_A = S_A[0]
S_F = S_F[0]
A0 = A0[0]*1.0e6 # converting from MPa.m3/mol = 1e-6 J/mol to J/mol
f0 = f0[0]*1.0e6 # converting from MPa = 1e-6 J/m3 to J/m3
avdw0 = avdw0[0]*1.0e6 # converting from MPa = 1e-6 J/m3 to J/m3
S_data = []
S_data.append(rho)
S_data.append(S_A)
S_data.append(S_F)
S_data.append(A0)
S_data.append(f0)
S_data.append(avdw0)
return S_data
def report_renorm_bin(rhov,x0v,fm,nx,nd,MR,IDs,EoS):
rep = []
x = x0v
x1 = np.array(menus.flatten(x))
x2 = 1.0-x1
rhob = rhov[0]
xb = np.empty((2))
f2d = np.empty((nx,nd))
rho = np.empty((nx,nd))
dfdrhob = np.empty((nx,nd))
dfdx1 = np.empty((nx,nd))
dfdx2 = np.empty((nx,nd))
rho1 = np.empty((nx,nd))
rho2 = np.empty((nx,nd))
u1mat = np.empty((nx,nd))
u2mat = np.empty((nx,nd))
bmix = np.empty((nx))
b = eos.b_calc(IDs,EoS)
b1 = b[0]
b2 = b[1]
for i in range(0,nx):
xb[0] = x1[i]
xb[1] = x2[i]
bmix[i] = eos.bmix_calc(MR,b,xb)
for i in range(0,nx):
f = np.array(fm[i])
for j in range(0,nd):
f2d[i][j] = f[j]
rho[i][j] = rhob[j]/bmix[i]
for i in range(0,nx):
for j in range(0,nd):
rho1[i][j] = x1[i]*rho[i][j]
rho2[i][j] = x2[i]*rho[i][j]
for i in range(0,nx):
dfdrhob[i][0] = (f2d[i][1]-f2d[i][0])/(rhob[1]-rhob[0])
for j in range(1,nd-1):
dfdrhob[i][j] = (f2d[i][j+1]-f2d[i][j-1])/(rhob[j+1]-rhob[j-1])
dfdrhob[i][nd-1] = (f2d[i][nd-1]-f2d[i][nd-2])/(rhob[nd-1]-rhob[nd-2])
for i in range(0,nx-1):
for j in range(0,nd):
if i!=0:
dfdx1[i][j] = (f2d[i+1][j]-f2d[i-1][j])/(x1[i+1]-x1[i-1])
else:
dfdx1[0][j] = (f2d[1][j]-f2d[0][j])/(x1[1]-x1[0])
dfdx1[nx-1][j] = (f2d[nx-1][j]-f2d[nx-2][j])/(x1[nx-1]-x1[nx-2])
for i in range(0,nx-1):
for j in range(0,nd):
if i!=0:
dfdx2[i][j] = (f2d[i+1][j]-f2d[i-1][j])/(x2[i+1]-x2[i-1])
else:
dfdx2[0][j] = (f2d[1][j]-f2d[0][j])/(x2[1]-x2[0])
dfdx2[nx-1][j] = (f2d[nx-1][j]-f2d[nx-2][j])/(x2[nx-1]-x2[nx-2])
for i in range(0,nx):
for j in range(0,nd):
u1mat[i][j] = dfdrhob[i][j]*b1+dfdx2[i][j]*(0-rho2[i][j])/(rho[i][j]*rho[i][j])
u2mat[i][j] = dfdrhob[i][j]*b2+dfdx1[i][j]*(0-rho1[i][j])/(rho[i][j]*rho[i][j])
u1res_mat = RectBivariateSpline(x,rhob,u1mat)
u2res_mat = RectBivariateSpline(x,rhob,u2mat)
u1mat_r = []
u2mat_r = []
for i in range(0,nx):
u1mat_r.append(u1mat[i])
u2mat_r.append(u2mat[i])
title = 'ren_f.tmp'
savedir = str('%s' %title)
with open(savedir,'w') as file:
dv = str("")
for j in range(0,nd):
d1 = str(round(rhob[j],9))
dv = dv+';'+d1
file.write(dv)
file.write('\n')
for i in range(0,nx):
x = str(round(x0v[i],9))
f = fm[i]
lin1 = x
for j in range(0,nd):
f1 = str(round(f[j],9))
lin1 = lin1+';'+f1
file.write(lin1)
file.write('\n')
title = 'u1.tmp'
savedir = str('%s' %title)
with open(savedir,'w') as file:
dv = str("")
for j in range(0,nd):
d1 = str(round(rhob[j],9))
dv = dv+';'+d1
file.write(dv)
file.write('\n')
for i in range(0,nx):
x = str(round(x0v[i],9))
u = u1mat_r[i]
lin1 = x
for j in range(0,nd):
u1 = str(round(u[j],9))
lin1 = lin1+';'+u1
file.write(lin1)
file.write('\n')
title = 'u2.tmp'
savedir = str('%s' %title)
with open(savedir,'w') as file:
dv = str("")
for j in range(0,nd):
d1 = str(round(rhob[j],9))
dv = dv+';'+d1
file.write(dv)
file.write('\n')
for i in range(0,nx):
x = str(round(x0v[i],9))
u = u2mat_r[i]
lin1 = x
for j in range(0,nd):
u2 = str(round(u[j],9))
lin1 = lin1+';'+u2
file.write(lin1)
file.write('\n')
rep.append(u1res_mat)
rep.append(u2res_mat)
return rep
def volume_renorm(phase, xint, Pint, bmix, R, T, r_data):
Pspln = r_data[5]
rho = r_data[3][0]
x = np.array(menus.flatten(r_data[1]))
nd = len(rho)
nx = x.shape[0]
Pvec = np.empty((nd))
Pfvec = np.empty((nd))
dPdrho = np.empty((nd))
flag = False
inflex = False
while flag!=True:
#Interpolate specific pressure
Pvint = Pspln(xint,0.0001)
Pvec[0] = Pvint
Pfvec[0] = Pvec[0] - Pint
for i in range(1,nd-1):
rhoint = float(i)/nd
Pvint = Pspln(xint,rhoint)
#print i,rhoint,Pvint
Pvec[i] = Pvint
Pfvec[i] = Pvec[i] - Pint
dPdrho[i] = (Pvec[i+1] - Pvec[i-1])/(float(i+1)/nd-float(i-1)/nd)
if inflex==False and dPdrho[i]<0:
inflex=True
Pvint = Pspln(xint,int(nd-1))
Pvec[nd-1] = Pvint
Pfvec[nd-1] = Pvec[nd-1] - Pint
dPdrho[0] = (Pvec[1] - Pvec[0])/(float(1)/nd-float(0)/nd)
dPdrho[nd-1] = (Pvec[nd-1] - Pvec[nd-2])/(float(nd-1)/nd-float(nd-2)/nd)
#Bracketing the real densities at given P
#print rho
#print Pvec
#print Pfvec
#NEW
P_fvec_spl = splrep(rho,Pfvec,k=3) #Cubic Spline Representation
Pfvec = splev(rho,P_fvec_spl,der=0)
#NEW
#plt.plot(rho,Pvec)
#plt.ylim(-15,15)
#plt.show()
max1 = 2
min1 = int(0.90*nd) #it was 0.90 before
max2 = max1+2
min2 = min1-2
#raw_input('before')
while Pfvec[max1]*Pfvec[max2]>0:# and max2<len(Pfvec):
#max2 = max2+int(nd/200)
max2 = max2+1
#print 'max',max2
#raw_input('max')
if max2-int(nd/100)<0:
max1 = 0
#print 'max1',max1
else:
#max1 = max2-int(nd/100)
max1 = max2-4
#print 'else',max1
while Pfvec[min1]*Pfvec[min2]>0 and min2>0:
#min2 = min2-int(nd/200)
min2 = min2-1
#print 'min',min2
#raw_input('min')
#min1 = min2+int(nd/100)
min1 = min2+4
#print 'int',Pint,xint,phase
#print 'falsi_spline',rho[max1],rho[max2],rho[min1],rho[min2]
#print 'falsi_pressures',Pfvec[max1],Pfvec[max2],Pfvec[min1],Pfvec[min2]
#Calculate coexistence densities in interpolated isotherm for given P
rho_vap = numerical.falsi_spline(rho, Pfvec, rho[max1], rho[max2], 1e-5)
#print 'rho_vap',rho_vap
rho_liq = numerical.falsi_spline(rho, Pfvec, rho[min2], rho[min1], 1e-5)
#print 'rho_liq',rho_liq
#raw_input('...')
if inflex==True and abs(rho_vap-rho_liq)<1e-5:
Pint=Pint/2
if inflex==True and abs(rho_vap-rho_liq)>1e-5:
flag=True
if xint>0.05:
flag=True
#Select desired density
if phase<0:
rho_out = rho_liq
if phase>0:
rho_out = rho_vap
V = 1/(rho_out/bmix)
V_out = []
V_out.append(V)
V_out.append(0)
return V_out