def __init__(self, input_dir, working_dir, chemkin):
''' dir: working directory with chem.inp part files '''
input_dir = fix_dir(input_dir)
with open(input_dir + "chem_part_1.inp", "r") as f:
self.chem_part_1 = f.read()
with open(input_dir + "chem_part_3.inp", "r") as f:
self.chem_part_3 = f.read()
self.working_dir = fix_dir(working_dir)
self.chemkin = chemkin
def init_conditions(working_dir='./',
T=1300,
P=4,
MF={
'POSF10325': .004,
'AR': .996
},
mode='UV',
TIME=2e-3,
DELT=2e-5):
''' write initial conditions to file '''
working_dir = fix_dir(working_dir)
inputs = ''
if mode == 'UV':
# constant UV
inputs += 'CONV\n'
elif mode == 'HP':
# constant HP
inputs += 'CONP\n'
inputs += 'RTOL 1.0E-6\n'
inputs += 'ATOL 1.0E-12\n'
inputs += 'PRES ' + str(P) + '\n' # pressure
inputs += 'TEMP ' + str(T) + '\n' # temperature
inputs += 'TIME ' + str(TIME) + '\n' # total time of simulation
inputs += 'DELT ' + str(DELT) + '\n' # time step
# initial mole fractions
for s in MF:
inputs += 'REAC ' + s.upper() + ' ' + str(MF[s]) + '\n'
inputs += 'END\n'
with open(working_dir + 'senkin.inp', 'w') as f:
f.write(inputs)
def extract_from_outputs(working_dir='./'):
''' extract mole fraction time history from file '''
working_dir = fix_dir(working_dir)
with open(working_dir + 'senkin.ign', 'r') as f:
lines = f.read()
lines = lines.split('Time Integration:')[-1]
d = pd.read_csv(StringIO(lines), sep='\s+')
# d['t'] = d['t']/1e3 # time unit
return d
def idt_cost(dir, x, idt, cond):
dir = fix_dir(dir)
write_cheminp(dir, x)
sim = chemkin_wrapper(dir,
**cond,
TIME=3 * idt,
DELT=max(1E-6, idt / 1e3 / 100),
mode="UV")
t = sim['t']
OH = sim['OH']
idt_sim = t[OH.idxmax()]
# cost = np.abs((idt-idt_sim)/idt)
cost = np.abs(np.log(idt_sim / idt))
return cost, idt_sim
def hychem_cost(dir, x, d, cond):
dir = fix_dir(dir)
# print("hychem_cost", dir)
write_cheminp(dir, x)
sim = chemkin_wrapper(working_dir=dir, **cond) # HyChem simulated
t = d['t']
tp = sim['t']
common_s = list(set(d).intersection(set(sim)).difference(set(["t"])))
fp = sim[common_s]
interp_f = interp1d(tp, fp, axis=0, fill_value="extrapolate")
f = interp_f(t)
# meas squared error
cost = np.linalg.norm(f - d[common_s],
ord='fro')**2. / (f.shape[0] * f.shape[1])
# cost = np.sum(np.abs(f-d[common_s]))
return cost
def write_cheminp(dir, x, bounds=A2_C1_BOUNDS):
''' input
params: (d,1)
bounds (l,u): (d,2)
'''
dir = fix_dir(dir)
assert (x.shape[0] == bounds.shape[0])
assert (2 == bounds.shape[1])
outputs = ''
with open(dir + "chem_part_1.inp", "r") as f:
outputs += f.read()
params = x_to_params(x, bounds)
# print(params)
outputs += build_hychem_rxn(params)
# with open(dir+"chem_part_3_no_oxygen.inp", "r") as f:
with open(dir + "chem_part_3.inp", "r") as f:
outputs += f.read()
# print("write_cheminp: "+dir+"chem.inp")
with open(dir + "chem.inp", "w") as f:
f.write(outputs)
return
def chemkin_wrapper(working_dir='./',
T=1225,
P=1.7,
MF={
'POSF10325': .004,
'AR': .996
},
mode='HP',
TIME=2e-3,
DELT=1e-6):
''' wrapper for running chemkin '''
working_dir = fix_dir(working_dir)
# write initial condition to file
init_conditions(working_dir, T, P, MF, mode, TIME, DELT)
# change current directory
cwd = os.getcwd()
# run ./chem
os.system('cd ' + working_dir + '; ./chem; cd ' + cwd)
# run ./igsenp
os.system('cd ' + working_dir + '; ./igsenp; cd ' + cwd)
# extract mole fraction time history
d = extract_from_outputs(working_dir)
return d
def grad_hychem_gmm(
dir,
params,
cond,
perturb=1e-3,
target_species=['C2H4', 'C3H6', 'C4H81', 'CH4', 'POSF10325', 'H2'],
target_times=np.arange(1, 11) / 10 * 2e3):
dir = fix_dir(dir)
x = params_to_x(params, A2_C1_BOUNDS)
N_grad = 15
write_cheminp(dir, x)
sim = chemkin_wrapper(dir, **cond)
tp = sim['t']
fp = sim[target_species]
interp_f = interp1d(tp, fp, axis=0, fill_value="extrapolate")
f = interp_f(target_times)
grad = np.zeros((N_grad, target_times.shape[0] * len(target_species)))
for i in range(N_grad):
x1 = np.array(x, copy=True)
x1[i] = x[i] + perturb
write_cheminp(dir, x1)
sim1 = chemkin_wrapper(dir, **cond)
tp = sim1['t']
fp = sim1[target_species]
interp_f = interp1d(tp, fp, axis=0, fill_value="extrapolate")
f1 = interp_f(target_times)
# print(f1.shape, f.shape)
grad_i = (f1 - f) / perturb
# grad_i = (sim1[target_species]-sim[target_species])/perturb
grad_i = np.reshape(grad_i, (1, -1), order="F")
# print(grad_i.shape)
grad[i, :] = grad_i
return grad
def __init__(self, working_dir):
self.working_dir = fix_dir(working_dir)