Exemplo n.º 1
0
def run_varying_enrichment(isotopes, iso_names, nat_conc, PuAmCm_conc, mix_ratios, reactor_type):
    avg_ks = []
    for ratio_mox in mix_ratios:
        conc = nat_conc*(1-ratio_mox) + PuAmCm_conc*(ratio_mox)

        years = 50 / (35*1e-6*1e3) / 365.25 # MWd/kg / W/g * MW/W * g/kg / days/year
        steps = int(1e3)
        conc_over_time, fluxes, ks = main.main_function(isotopes, conc, reactor_type, years, steps)

        print('mox isotopics')
        print_isotopics_final(iso_names, conc, conc_over_time[:,-1])
        avg_ks.append(np.average(ks))
    return avg_ks
Exemplo n.º 2
0
def run():
    deviceID = request.args.get('deviceID')
    detect_final_result = main.main_function(deviceID)
    return "".join(str(x) for x in detect_final_result)
Exemplo n.º 3
0
import numpy as np
import sys
sys.path.append('..')
import pandas

from main import main_function
from plotting import concentration_plot

isotopes = ['922350', '922360', '922370', '922380', '922390']
conc = np.zeros(len(isotopes))
conc[0] = 0.05
conc[3] = 0.95
flux = 0
years = 5
steps = 10000
reactor_type = 'fast'
conc_over_time = main_function(isotopes, conc, flux, reactor_type, years,
                               steps)

data = np.vstack([np.array(isotopes), conc, conc_over_time[:, -1]])
data = data.transpose()
headers = ['Isotope', 'Conc-init', 'Conc-final']

df = pandas.DataFrame(data=data, columns=headers)
print(df)

concentration_plot(isotopes, years, steps, conc_over_time)
Exemplo n.º 4
0
conc = np.zeros(len(isotopes) + 2)
conc[2] = 0.05
conc[5] = 0.95

nat_conc = copy.deepcopy(conc)
nat_conc[2] = 0.00711  # Weight percent
nat_conc[5] = (1 - 0.00711)

years = 50 / (35 * 1e-6 *
              1e3) / 365.25  # MWd/kg / W/g * MW/W * g/kg / days/year
steps = int(1e3)

# Find thermal avg k
reactor_type = 'thermal'
conc_over_time, fluxes, ks = main_function(isotopes, conc, reactor_type, years,
                                           steps)
fresh_ks = ks
avg_k_fresh_thermal = np.average(ks)
PuAmCm_conc = extract_PuAmCm(isotopes, conc_over_time[:, -1])
print('Plutonium Vector')
print_isotopics_final(iso_names, conc, PuAmCm_conc)
csv_path = './' + reactor_type + '_fresh_concentrations.csv'
# flux_k_plot(years, steps, fluxes, ks)
print_isotopics_final(iso_names, conc, conc_over_time[:, -1], csv_path)
PuAmCm_thermals = [extract_PuAmCm(isotopes, conc_over_time[:, -1])]
print(reactor_type + 'Fresh Average k: ', avg_k_fresh_thermal)

if burnup_plot:
    title = '50 MWd/kg Burnup in ' + reactor_type + ' spectrum'
    concentration_subplot(iso_names, years, steps, conc_over_time, title)
    flux_k_plot(years, steps, fluxes, ks)
Exemplo n.º 5
0
    try:
        iso_names.append(nucname.serpent(iso))
    except:
        iso_names.append(iso)
iso_names.append('Lumped-Act.')
iso_names.append('FPs')

conc = np.zeros(len(isotopes) + 2)
conc[2] = 0.05
conc[5] = 0.95
flux = 0
years = 60 / (35 * 1e-6 *
              1e3) / 365.25  # MWd/kg / W/g * MW/W * g/kg / days/year
steps = int(1e3)
reactor_type = 'thermal'
conc_over_time, fluxes, ks = main_function(isotopes, conc, flux, reactor_type,
                                           years, steps)

data = np.vstack(
    [np.array(iso_names), conc * 100, conc_over_time[:, -1] * 100])
data = data.transpose()
headers = ['Isotope', 'Conc-init', 'Conc-final']

pandas.options.display.float_format = '{:2.4f}'.format
df = pandas.DataFrame(data=data, columns=headers)
df['Conc-init'] = pandas.to_numeric(df['Conc-init'])
df['Conc-final'] = pandas.to_numeric(df['Conc-final'])
df.loc['Total'] = pandas.Series(df['Conc-final'].sum(), index=['Conc-final'])
df.at['Total', 'Conc-init'] = df['Conc-init'].sum()
csv_path = './' + reactor_type + '_concentrations.csv'
df.to_csv(csv_path)
print(df)
Exemplo n.º 6
0
conc = np.zeros(len(isotopes) + 2)
conc[2] = 0.05
conc[5] = 0.95

nat_conc = copy.deepcopy(conc)
nat_conc[2] = 0.00711  # Weight percent
nat_conc[5] = (1 - 0.00711)

years = 50 / (35 * 1e-6 *
              1e3) / 365.25  # MWd/kg / W/g * MW/W * g/kg / days/year
steps = int(1e3)

# Make MOX
reactor_type = 'thermal'
conc_over_time, fluxes, ks = main_function(isotopes, conc, reactor_type, years,
                                           steps)
PuAmCm_conc = extract_PuAmCm(isotopes, conc_over_time[:, -1])

weight_percent = 0.30
mox_conc = weight_percent * PuAmCm_conc + (1 - weight_percent) * nat_conc

# Deplete by 15 atom percent in fast reactor
years = 100  # Large number to hit 15 percent atom depletion
steps = int(1e4)
reactor_type = 'fast'
print("Start of 15 deplete function")
conc_over_time_fast, fluxes, ks = main_function(isotopes,
                                                mox_conc,
                                                reactor_type,
                                                years,
                                                steps,