Candu Reactor compared k_eff values with Serpent

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  • Thread starter emilmammadzada
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In summary, the comparison of k_eff values for Candu reactors using the Serpent Monte Carlo code reveals insights into the reactor's criticality and performance. The analysis highlights the accuracy of Serpent in simulating neutron behavior and its effectiveness in predicting k_eff for various configurations and fuel compositions, ultimately enhancing the understanding of Candu reactor operations and safety assessments.
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emilmammadzada
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TL;DR Summary
Candu Reactor compared k_eff values with Serpent
Dear experts, I am trying to set the Serpent input file for the candu reactor in Openmc accordingly. But in the output section, Serpent k_eff values are around 0.9, while Openmc shows 0.42. How can I solve this problem or what are the errors in the files I added below that cause this difference?
[from math import pi, sin, cos
import numpy as np
import openmc
import json
import numpy as np
from pathlib import Path
import openmc.deplete
# Fuel and clad
temperature_fuel = 960 #Fuel at 960 K with a density of 10.52 g/cc
temperature_structure = 345.15 #Moderator at 345.15 K with a density of 1.086 g/cc
r_fuel = 0.6122
r_clad = 0.6540
pressure_tube_ir = 5.16890
pressure_tube_or = 5.60320
calendria_ir = 6.44780
calendria_or = 6.58750
# Fuel
fuel = openmc.Material(name='fuel', temperature=temperature_fuel)
fuel.add_nuclide('U235', 6.27118E-1 , 'wo')
fuel.add_nuclide('U238', 8.75256E+1 , 'wo')
fuel.add_nuclide('O16', 1.18473E+1 , 'wo')
fuel.volume = 37*pi*r_fuel**2
fuel.set_density('g/cm3', 10.4375010)
# Coolant Water
heavy_water_coolant = openmc.Material(name='heavy water coolant')
heavy_water_coolant.add_nuclide('H2', 1.99768E-1 , 'wo' )
heavy_water_coolant.add_nuclide('O16', 7.99449E-1 , 'wo' )
heavy_water_coolant.add_nuclide('H1', 7.83774E-4 , 'wo' )
heavy_water_coolant.set_density('g/cm3', 0.812120)
# Calandria tube
clad_calandria = openmc.Material(name='Calandria')
clad_calandria.add_nuclide('Mn55', 1.60000E-1 , 'wo' )
clad_calandria.add_element('Ni', 6.00000E-2 , 'wo' )
clad_calandria.add_element('Cr', 1.10000E-1 , 'wo' )
clad_calandria.add_element('Zr', 9.97100E+1 , 'wo' )
clad_calandria.add_nuclide('B10', 5.7409e-05 , 'wo' )
clad_calandria.add_nuclide('B11', 2.5259E-04 , 'wo' )
clad_calandria.set_density('g/cm3', 6.44)
# Clad
clad = openmc.Material(name='Clad')
clad.add_nuclide('Mn55', 1.60000E-1 , 'wo' )
clad.add_element('Ni', 6.00000E-2 , 'wo' )
clad.add_element('Cr', 1.10000E-1 , 'wo' )
clad.add_element('Zr', 9.97100E+1 , 'wo' )
clad.add_nuclide('B10', 5.7409e-05 , 'wo' )
clad.add_nuclide('B11', 2.5259E-04 , 'wo' )
clad.set_density('g/cm3', 6.44)
# Moder
heavy_water = openmc.Material(name='heavy water')
heavy_water.add_nuclide('H2', 2.01016E-1, 'wo' )
heavy_water.add_nuclide('O16', 7.98895E-1, 'wo' )
heavy_water.add_nuclide('H1', 8.96000E-5, 'wo' )
heavy_water.set_density('g/cm3', 1.082885 )
heavy_water.add_s_alpha_beta('c_D_in_D2O')
# Pressure Tube
tube = openmc.Material(name='PressTube')
tube.add_element('Zr', 9.75000E+1 , 'wo' )
tube.add_nuclide('B10', 3.8889E-05 , 'wo' )
tube.add_nuclide('B11', 1.7111E-04 , 'wo' )
tube.set_density('g/cm3', 6.57)
mats = openmc.Materials([fuel, heavy_water_coolant, clad_calandria, clad, heavy_water, tube ])
mats.export_to_xml()

# Radius to center of each ring of fuel pins
ring_radii = np.array([0.0, 1.4885, 2.8755, 4.3305])
# These are the surfaces that will divide each of the rings
radial_surf = [openmc.ZCylinder(R=r) for r in
(ring_radii[:-1] + ring_radii[1:])/2]

water_cells = []
for i in range(ring_radii.size):
# Create annular region
if i == 0:
water_region = -radial_surf
elif i == ring_radii.size - 1:
water_region = +radial_surf[i-1]
else:
water_region = +radial_surf[i-1] & -radial_surf

water_cells.append(openmc.Cell(fill=heavy_water, region=water_region))
bundle_universe = openmc.Universe(cells=water_cells)
surf_fuel = openmc.ZCylinder(R=r_fuel)
surf_clad = openmc.ZCylinder(R=r_clad)

fuel_cell = openmc.Cell(fill=fuel, region=-surf_fuel)
clad_cell = openmc.Cell(fill=clad, region=+surf_fuel & -surf_clad)
cool_cell = openmc.Cell(fill=heavy_water_coolant, region=+surf_clad & -surf_clad)

pin_universe = openmc.Universe(cells=(fuel_cell, clad_cell, cool_cell))
num_pins = [1, 6, 12, 18]
angles = [0, 0, 15, 0]

for i, (r, n, a) in enumerate(zip(ring_radii, num_pins, angles)):
for j in range(n):
# Determine location of center of pin
theta = (a + j/n*360.) * pi/180.
x = r*cos(theta)
y = r*sin(theta)

pin_boundary = openmc.ZCylinder(x0=x, y0=y, R=r_clad)
water_cells.region &= +pin_boundary


# That we can identify the pin later when looking at tallies
pin = openmc.Cell(fill=pin_universe, region=-pin_boundary)
pin.translation = (x, y, 0)
pin.id = (i + 1)*100 + j
bundle_universe.add_cell(pin)

pt_inner = openmc.ZCylinder(R=pressure_tube_ir)
pt_outer = openmc.ZCylinder(R=pressure_tube_or)
calendria_inner = openmc.ZCylinder(R=calendria_ir)
calendria_outer = openmc.ZCylinder(R=calendria_or,boundary_type='reflective')

bundle = openmc.Cell(fill=bundle_universe, region=-pt_inner)
pressure_tube = openmc.Cell(fill=tube, region=+pt_inner & -pt_outer)
v1 = openmc.Cell(region=+pt_outer & -calendria_inner)
calendria = openmc.Cell(fill=clad_calandria, region=+calendria_inner & -calendria_outer)

root_universe = openmc.Universe(cells=[bundle, pressure_tube, v1, calendria])

geom = openmc.Geometry(root_universe)
geom.export_to_xml()
settings = openmc.Settings()
settings = openmc.Settings()
settings.particles = 500
settings.batches = 50
settings.inactive = 5
settings.source = openmc.Source(space=openmc.stats.Point())
settings.temperature = {
'default': temperature_structure,
'method': 'interpolation',
}
settings.export_to_xml()
openmc.run()]
 

FAQ: Candu Reactor compared k_eff values with Serpent

What is a CANDU reactor?

A CANDU (CANada Deuterium Uranium) reactor is a type of nuclear reactor that uses heavy water (deuterium oxide) as its moderator and coolant, and natural uranium as its fuel. It was developed in Canada and is known for its ability to use various types of fuel, including natural uranium, reprocessed uranium, and thorium.

What is k_eff in the context of nuclear reactors?

The effective multiplication factor, k_eff, is a measure of the neutron multiplication in a reactor core. It indicates whether a nuclear chain reaction is self-sustaining. If k_eff is equal to 1, the reactor is critical and the chain reaction is stable. If k_eff is less than 1, the reaction is subcritical and will eventually die out. If k_eff is greater than 1, the reaction is supercritical and the neutron population will increase.

What is Serpent and how is it used in reactor analysis?

Serpent is a Monte Carlo reactor physics code used for simulating neutron transport and other reactor physics phenomena. It is widely used for reactor core analysis, fuel cycle studies, and other applications in nuclear engineering. Serpent can model complex geometries and materials, making it a powerful tool for comparing k_eff values in different reactor designs, including CANDU reactors.

How do k_eff values obtained from Serpent compare with those calculated for CANDU reactors?

k_eff values obtained from Serpent simulations are generally considered to be highly accurate due to the detailed modeling capabilities of the code. When comparing these values to those calculated for CANDU reactors using traditional methods or other simulation tools, Serpent's results often provide a more precise understanding of the reactor's behavior under various conditions. However, discrepancies can arise due to differences in modeling assumptions, nuclear data libraries, and computational methods.

Why is it important to compare k_eff values for CANDU reactors using Serpent?

Comparing k_eff values for CANDU reactors using Serpent is important for validating and verifying reactor designs and operational strategies. Accurate k_eff values are crucial for ensuring the safety and efficiency of the reactor. By using Serpent, researchers and engineers can gain insights into the reactor's performance, identify potential issues, and optimize the reactor's operation. This comparison also helps in improving the accuracy of other computational tools and methods used in reactor analysis.

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