def run() :
# parameter dictionary
p = {}
p['number_batches'] = 3
p['leakage_penalty'] = 0.04
p['assembly_width'] = 21.5036
p['assembly_power'] = 3.4/193
p['active_height'] = 366.0
p['fuel_radius'] = 0.4096
p['cladding_inner_radius'] = 0.4180
p['cladding_outer_radius'] = 0.4750
p['number_pins'] = 264
p['power_share'] = 'reactivity'
T_F = 900*np.ones(p['number_batches']) # batch fuel temperatures (K)
T_C = 580*np.ones(p['number_batches']) # batch moderator temperatures (K)
num_thick = 20
thick = np.linspace(0.0, 500, num_thick)
B_c_FeCrAl = np.zeros((2, num_thick))
B_c_SiC = np.zeros((2, num_thick))
solver = NRM(p, rho=rho, m2=m2, k_cladding=k_cladding)
te = time.time()
for i in range(num_thick):
print 'thickness = %f micron' % thick[i]
# FeCrAl
p['power_share'] = 'equal'
p['t_fecral'] = thick[i]
p['t_sic'] = 0.0
p['power_share'] = 'equal'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_FeCrAl[0, i] = B[-1]/len(T_F)
p['power_share'] = 'reactivity'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_FeCrAl[1, i] = B[-1]/len(T_F)
p['t_sic'] = thick[i]
p['t_fecral'] = 0.0
p['power_share'] = 'equal'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_SiC[0, i] = B[-1]/len(T_F)
p['power_share'] = 'reactivity'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_SiC[1, i] = B[-1]/len(T_F)
te = time.time() - te
print "elapsed time: %f seconds" % te
pickle.dump({'thick':thick, 'B_c_FeCrAl': B_c_FeCrAl, 'B_c_SiC': B_c_SiC},\
open('example_2.p', 'w'))
def run():
# parameter dictionary
p = {}
p['number_batches'] = 3
p['leakage_penalty'] = 0.04
p['assembly_width'] = 21.5036
p['assembly_power'] = 3.4 / 193
p['active_height'] = 366.0
p['fuel_radius'] = 0.4096
p['cladding_inner_radius'] = 0.4180
p['cladding_outer_radius'] = 0.4750
p['number_pins'] = 264
p['power_share'] = 'reactivity'
T_F = 900 * sp.ones(p['number_batches']) # batch fuel temperatures (K)
T_C = 580 * sp.ones(
p['number_batches']) # batch moderator temperatures (K)
num_thick = 20
#thick = sp.linspace(0.0, 500, num_thick)
thick = sp.logspace(-1, sp.log10(5 * 10**2), num_thick)
T_F_FeCrAl = sp.zeros((3, num_thick))
T_C_FeCrAl = sp.zeros((3, num_thick))
T_F_SiC = sp.zeros((3, num_thick))
T_C_SiC = sp.zeros((3, num_thick))
PPF_FeCrAl = sp.zeros((3, num_thick))
PPF_SiC = sp.zeros((3, num_thick))
solver = NRM(p, rho=rho, m2=m2, k_cladding=k_cladding)
for i in range(num_thick):
p['t_fecral'] = thick[i]
p['t_sic'] = 0.0
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
T_F_FeCrAl[:, i] = T_F[:]
T_C_FeCrAl[:, i] = T_C[:]
PPF_FeCrAl[:, i] = ppf[:]
p['t_fecral'] = 0.0
p['t_sic'] = thick[i]
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
T_F_SiC[:, i] = T_F[:]
T_C_SiC[:, i] = T_C[:]
PPF_SiC[:, i] = ppf[:]
pickle.dump(
{
'thick': thick,
'T_F_FeCrAl': T_F_FeCrAl,
'T_C_FeCrAl': T_C_FeCrAl,
'PPF_FeCrAl': PPF_FeCrAl,
'T_F_SiC': T_F_SiC,
'T_C_SiC': T_C_SiC,
'PPF_SiC': PPF_SiC
}, open('example_3.p', 'wb'))
def run() :
# parameter dictionary
p = {}
p['number_batches'] = 3
p['leakage_penalty'] = 0.04
p['assembly_width'] = 21.5036
p['assembly_power'] = 3.4/193
p['active_height'] = 366.0
p['fuel_radius'] = 0.4096
p['cladding_inner_radius'] = 0.4180
p['cladding_outer_radius'] = 0.4750
p['number_pins'] = 264
p['power_share'] = 'reactivity'
T_F = 900*sp.ones(p['number_batches']) # batch fuel temperatures (K)
T_C = 580*sp.ones(p['number_batches']) # batch moderator temperatures (K)
num_thick = 20
#thick = sp.linspace(0.0, 500, num_thick)
thick = sp.logspace(-1, sp.log10(5*10**2), num_thick)
T_F_FeCrAl = sp.zeros((3, num_thick))
T_C_FeCrAl = sp.zeros((3, num_thick))
T_F_SiC = sp.zeros((3, num_thick))
T_C_SiC = sp.zeros((3, num_thick))
PPF_FeCrAl = sp.zeros((3, num_thick))
PPF_SiC = sp.zeros((3, num_thick))
solver = NRM(p, rho=rho, m2=m2, k_cladding=k_cladding)
for i in range(num_thick) :
p['t_fecral'] = thick[i]
p['t_sic'] = 0.0
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
T_F_FeCrAl[:, i] = T_F[:]
T_C_FeCrAl[:, i] = T_C[:]
PPF_FeCrAl[:, i] = ppf[:]
p['t_fecral'] = 0.0
p['t_sic'] = thick[i]
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
T_F_SiC[:, i] = T_F[:]
T_C_SiC[:, i] = T_C[:]
PPF_SiC[:, i] = ppf[:]
pickle.dump({'thick': thick,
'T_F_FeCrAl': T_F_FeCrAl,
'T_C_FeCrAl': T_C_FeCrAl,
'PPF_FeCrAl': PPF_FeCrAl,
'T_F_SiC': T_F_SiC,
'T_C_SiC': T_C_SiC,
'PPF_SiC': PPF_SiC}, open('example_3.p', 'w'))
def run() :
# parameter dictionary
p = {}
p['number_batches'] = 3
p['leakage_penalty'] = 0.04
p['assembly_width'] = 21.5036
p['assembly_power'] = 3.4/193
p['active_height'] = 366.0
p['fuel_radius'] = 0.4096
p['cladding_inner_radius'] = 0.4180
p['cladding_outer_radius'] = 0.4750
p['number_pins'] = 264
p['power_share'] = 'reactivity'
T_F = 900*np.ones(p['number_batches']) # batch fuel temperatures (K)
T_C = 580*np.ones(p['number_batches']) # batch moderator temperatures (K)
num_thick = 20
thick = np.linspace(0.0, 500, num_thick)
B_c_FeCrAl = np.zeros((2, num_thick))
B_c_SiC = np.zeros((2, num_thick))
solver = NRM(p, rho=rho, m2=m2, k_cladding=k_cladding)
te = time.time()
for i in range(num_thick):
print('thickness = {:.3f} micron'.format(thick[i]))
# FeCrAl
p['power_share'] = 'equal'
p['t_fecral'] = thick[i]
p['t_sic'] = 0.0
p['power_share'] = 'equal'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_FeCrAl[0, i] = B[-1]/len(T_F)
p['power_share'] = 'reactivity'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_FeCrAl[1, i] = B[-1]/len(T_F)
p['t_sic'] = thick[i]
p['t_fecral'] = 0.0
p['power_share'] = 'equal'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_SiC[0, i] = B[-1]/len(T_F)
p['power_share'] = 'reactivity'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_SiC[1, i] = B[-1]/len(T_F)
te = time.time() - te
print("elapsed time: {:.3f} seconds".format(te))
pickle.dump({'thick':thick, 'B_c_FeCrAl': B_c_FeCrAl, 'B_c_SiC': B_c_SiC},\
open('example_2.p', 'wb'))
num_enrich = 5
enrich = np.linspace(3.0, 5, num_enrich)
B_c_equal = np.zeros(num_enrich)
B_c_reactivity = np.zeros(num_enrich)
for i in range(num_enrich):
# Set enrichment
p['enrichment'] = enrich[i]
# Make model
c = CASMO4(p, degree=1, run=True)
# Make solver
solver = NRM(p, rho=c.rho, m2=c.m2, tolerance=0.000001)
te = time.time()
print('enrichment = {:.2f}%'.format(enrich[i]))
p['power_share'] = 'equal'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_equal[i] = B[-1]/p['number_batches']
p['power_share'] = 'reactivity'
B, ppf, T_F, T_C = solver.solve(T_F, T_C)
B_c_reactivity[i] = B[-1]/p['number_batches']
te = time.time() - te
