def HB_write(self):
assert self.mol, 'Mol needed for HB plot x axis'
nIndep = self.gen_data[self.feed][self.run]['numIndep']
my_run = [i for i in self.HB[self.feed].keys() if i[:-1] in self.run][0]
HB = self.HB[self.feed][my_run]
file_description = 'Q N_HB dQ dN_HB'
if self.box == 'box3':
self.box = 'box2'
X = self.getX()
self.box = 'box3'
else:
X = self.getX()
for pair in HB.keys():
if type(HB[pair]) == type(int(1)):
continue
elif HB[pair][self.box]['mean'] > 0.:
file_name = 'HB_%s_v_%s_%s.dat'%(pair.replace('->','-').replace(' ',''), self.mol, self.xlabel[0])
if '95conf' in X.keys():
err = X['95conf']
print(X)
else:
err = calc95conf(X['stdev'],nIndep)
writeAGR([X['mean']], [HB[pair][self.box]['mean']],
[err], [calc95conf(HB[pair][self.box]['stdev'], nIndep)],
[self.feed], file_name, file_description)
def dHigvX(self):
U = self.U[self.feed][self.run]
dH_store = self.dHmixt[self.feed][self.run]
gen_data = self.gen_data[self.feed][self.run]
file_name = 'dHig_vapor_to_%s.dat' % self.box
X = self.getX()
N = self.N[self.feed][self.run]
P = self.P[self.feed][self.run]
N1_tot = sum(N[i][self.box]['mean'] for i in N.keys())
_rho_ = self.rho[self.feed][self.run]
rho_total = getRhoTotal(_rho_)
N1 = {
'mean':
N1_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
vapor_box = 'box3'
N2 = {'mean': sum(N[i]['box3']['mean'] for i in N.keys())}
N2['stdev'] = math.pow(sum(N[i]['box3']['stdev']**2 for i in N.keys()),
0.5)
nIndep = gen_data['numIndep']
# dH = ((U[self.box]['mean']/N1['mean'] - U[vapor_box]['mean']/N2['mean'])*8.314/1000 - 8.314/1000*self.T -
# dH_store['box3-->box2']['mean'])
H_box1 = U[self.box]['mean'] / N1['mean']
H_box2 = P['box2']['mean'] * 1000. / rho_total['box2'] * N_av / R[
'\AA**3*kPa/(mol*K)']
H_box3 = U[vapor_box]['mean'] / N2['mean'] - P['box3'][
'mean'] * 1000. / rho_total['box3'] * N_av / R['\AA**3*kPa/(mol*K)']
dH = (H_box1 - H_box2 - H_box3) * R['kJ/(mol*K)']
ddH = math.pow(
(1 / N1['mean'])**2 * U['box1']['stdev']**2 +
(-1 * U['box1']['mean'] / N1['mean']**2)**2 * N1['stdev']**2 +
(1 / N2['mean'])**2 * U[vapor_box]['stdev']**2 +
(-1 * U[vapor_box]['mean'] / N2['mean']**2)**2 * N2['stdev']**2 +
dH_store['box3-->box2']['stdev']**2, 0.5) * 8.314 / 1000
dH_mean, dH_stdev = dH, ddH
file_description = 'dHig %s ddHig %s' % (self.xlabel[0],
self.xlabel[1])
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeAGR([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
def dHvX(self):
P = self.P[self.feed][self.run]
U = self.U[self.feed][self.run]
_rho_ = self.rho[self.feed][self.run]
rho_total = getRhoTotal(_rho_)
dH = self.dHmixt[self.feed][self.run]
N = self.N[self.feed][self.run]
N1_tot = sum(N[i][self.box]['mean'] for i in N.keys())
N1 = {
'mean':
N1_tot,
'stdev':
math.pow(sum(N[i][self.box]['stdev']**2 for i in N.keys()), 0.5)
} # mol
gen_data = self.gen_data[self.feed][self.run]
file_description = 'Q(%s) %s dQ %s' % (
self.units, self.xlabel[0], self.xlabel[1])
if self.boxes:
boxFrom, boxTo = self.boxes
# else:
# boxFrom = self.box
# boxTo = 'box1'
file_name = 'dH_%s_mixture.dat' % boxTo
assert 'box' in boxFrom, 'Wrong notation for box'
transfer = boxFrom + '-->' + boxTo
transfer2 = 'box2-->box1'
X = self.getX()
nIndep = gen_data['numIndep']
H_zeo = (U['box1']['mean'] / N1_tot + 0.1 * 1000. / rho_total['box1'] *
N_av / R['\AA**3*kPa/(mol*K)']) * R['kJ/(mol*K)']
dH_mean, dH_stdev = (dH[transfer]['mean'] + dH[transfer2]['mean'] -
H_zeo,
math.pow(
dH[transfer]['stdev']**2 +
4 * dH[transfer2]['stdev']**2, 0.5))
if '95conf' not in X.keys():
X['95conf'] = calc95conf(X['stdev'], nIndep)
writeAGR([X['mean']], [dH_mean], [X['95conf']],
[calc95conf(dH_stdev, nIndep)], [self.feed], file_name,
file_description)
# (molec/nm**3)*(mol/molec)*(nm**3*kPa/(mol*K))*K = kPa
p_mean = rho_mean / N_av * R['nm**3*kPa/(mol*K)'] * args['Temp']
p_stdev = rho_stdev / N_av * R['nm**3*kPa/(mol*K)'] * args['Temp']
henry_constant['mean'].append(conc['mean'] / p_mean)
kH_stdev = conc['mean'] / p_mean * math.pow(
math.pow(conc['stdev'] / conc['mean'], 2) +
math.pow(p_stdev / p_mean, 2), 0.5)
henry_constant['95conf'].append(calc95conf(kH_stdev, numIndep))
pressure['mean'].append(p_mean)
pressure['95conf'].append(calc95conf(p_stdev, numIndep))
if args['verbosity'] > 0:
print('liquid analysis for feed %s is with mol %s, box %s' %
(feed, c_mol, box))
henry_constant['feed'].append(feed)
# write out results
for mol in mol_data.keys():
file_name = 'kH-mol%s.dat' % (mol)
file_name = file_name.replace('/', '_')
x_data = mol_data[mol]['kH']
y_data = mol_data[mol]['P']
message = 'kH (g/(mL*kPa) P (kPa) d(kH) d(P)'
writeAGR(x_data['mean'],
y_data['mean'],
x_data['95conf'],
y_data['95conf'],
x_data['feed'],
file_name,
description=message)