Skip to content

Commit

Permalink
Merge pull request pyne#807 from mzweig/cram
Browse files Browse the repository at this point in the history 
Added CRAM to alara.py
  • Loading branch information
Rachel Slaybaugh committed Jan 15, 2016
2 parents 4402a2a + cc1e319 commit 5463170
Show file tree
Hide file tree
Showing 2 changed files with 247 additions and 28 deletions.
202 changes: 174 additions & 28 deletions pyne/alara.py
View file
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
"""This module contains functions relevant to the ALARA activation code.
"""This module contains functions relevant to the ALARA activation code and the Chebyshev Rational Approximation Method
"""
from __future__ import print_function
import os
Expand All @@ -25,8 +25,11 @@

from pyne.mesh import Mesh, MeshError
from pyne.material import Material, from_atom_frac
from pyne import nucname
from pyne.nucname import serpent, alara, znum, anum
from pyne.data import N_A
from pyne.data import N_A, decay_const, decay_children, branch_ratio
from pyne.xs.data_source import SimpleDataSource


def mesh_to_fluxin(flux_mesh, flux_tag, fluxin="fluxin.out",
reverse=False):
Expand Down Expand Up @@ -88,7 +91,7 @@ def photon_source_to_hdf5(filename, chunkshape=(10000,)):
"""Converts a plaintext photon source file to an HDF5 version for
quick later use.
This function produces a single HDF5 file named <filename>.h5 containing the
This function produces a single HDF5 file named <filename>.h5 containing the
table headings:
idx : int
Expand Down Expand Up @@ -212,7 +215,7 @@ def photon_source_hdf5_to_mesh(mesh, filename, tags):
else:
tag_handles[tags[cond]][ve] = [0] * num_e_groups

def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,
def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,
sig_figs=6):
"""This function preforms the same task as alara.mesh_to_geom, except the
geometry is on the basis of the stuctured array output of
Expand All @@ -229,7 +232,7 @@ def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,
The output from dagmc.discretize_geom(). A sorted, one dimensional
array, each entry containing the following fields:
:idx: int
:idx: int
The volume element index.
:cell: int
The geometry cell number.
Expand All @@ -251,7 +254,7 @@ def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,
"""
# Create geometry information header. Note that the shape of the geometry
# (rectangular) is actually inconsequential to the ALARA calculation so
# unstructured meshes are not adversely affected.
# unstructured meshes are not adversely affected.
geometry = 'geometry rectangular\n\n'

# Create three strings in order to create all ALARA input blocks in a
Expand Down Expand Up @@ -284,15 +287,15 @@ def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,

mixture += 'end\n\n'

mat_loading += ' zone_{0} mix_{1}\n'.format(i,
mat_loading += ' zone_{0} mix_{1}\n'.format(i,
unique_mixtures.index(ve_mixture))

volume += 'end\n\n'
mat_loading += 'end\n\n'

with open(geom_file, 'w') as f:
f.write(geometry + volume + mat_loading + mixture)

matlib = '' # ALARA material library string

printed_mats = []
Expand All @@ -307,7 +310,7 @@ def record_to_geom(mesh, cell_fracs, cell_mats, geom_file, matlib_file,
matlib += '{0} {1: 1.6E} {2}\n'.format(name, mat.density,
len(mat.comp))
for nuc, comp in mat.comp.iteritems():
matlib += '{0} {1: 1.6E} {2}\n'.format(alara(nuc),
matlib += '{0} {1: 1.6E} {2}\n'.format(alara(nuc),
comp*100.0, znum(nuc))
matlib += '\n'

Expand All @@ -328,7 +331,7 @@ def mesh_to_geom(mesh, geom_file, matlib_file):
geometry and materials portion of an ALARA input file, as well as a
corresponding matlib file. If the mesh is structured, xyz ordering is used
(z changing fastest). If the mesh is unstructured iMesh.iterate order is
used.
used.
Parameters
----------
Expand All @@ -341,7 +344,7 @@ def mesh_to_geom(mesh, geom_file, matlib_file):
"""
# Create geometry information header. Note that the shape of the geometry
# (rectangular) is actually inconsequential to the ALARA calculation so
# unstructured meshes are not adversely affected.
# unstructured meshes are not adversely affected.
geometry = "geometry rectangular\n\n"

# Create three strings in order to create all ALARA input blocks in a
Expand All @@ -354,13 +357,13 @@ def mesh_to_geom(mesh, geom_file, matlib_file):
for i, mat, ve in mesh:
volume += " {0: 1.6E} zone_{1}\n".format(mesh.elem_volume(ve), i)
mat_loading += " zone_{0} mix_{0}\n".format(i)
matlib += "mat_{0} {1: 1.6E} {2}\n".format(i, mesh.density[i],
matlib += "mat_{0} {1: 1.6E} {2}\n".format(i, mesh.density[i],
len(mesh.comp[i]))
mixture += ("mixture mix_{0}\n"
" material mat_{0} 1 1\nend\n\n".format(i))

for nuc, comp in mesh.comp[i].iteritems():
matlib += "{0} {1: 1.6E} {2}\n".format(alara(nuc), comp*100.0,
matlib += "{0} {1: 1.6E} {2}\n".format(alara(nuc), comp*100.0,
znum(nuc))
matlib += "\n"

Expand All @@ -369,15 +372,15 @@ def mesh_to_geom(mesh, geom_file, matlib_file):

with open(geom_file, 'w') as f:
f.write(geometry + volume + mat_loading + mixture)

with open(matlib_file, 'w') as f:
f.write(matlib)

def num_density_to_mesh(lines, time, m):
"""num_density_to_mesh(lines, time, m)
This function reads ALARA output containing number density information and
creates material objects which are then added to a supplied PyNE Mesh object.
The volumes within ALARA are assummed to appear in the same order as the
This function reads ALARA output containing number density information and
creates material objects which are then added to a supplied PyNE Mesh object.
The volumes within ALARA are assummed to appear in the same order as the
idx on the Mesh object.
Parameters
Expand Down Expand Up @@ -407,7 +410,7 @@ def num_density_to_mesh(lines, time, m):
# Get decay time index from next line (the column the decay time answers
# appear in.
line_strs = lines.pop(0).replace('\t', ' ')
time_index = [s.strip() for s in line_strs.split(' ')
time_index = [s.strip() for s in line_strs.split(' ')
if s.strip()].index(time)

# Create a dict of mats for the mesh.
Expand Down Expand Up @@ -439,20 +442,20 @@ def num_density_to_mesh(lines, time, m):
m.mats = mats


def irradiation_blocks(material_lib, element_lib, data_library, cooling,
def irradiation_blocks(material_lib, element_lib, data_library, cooling,
flux_file, irr_time, output = "number_density",
truncation=1E-12, impurity = (5E-6, 1E-3),
truncation=1E-12, impurity = (5E-6, 1E-3),
dump_file = "dump_file"):
"""irradiation_blocks(material_lib, element_lib, data_library, cooling,
"""irradiation_blocks(material_lib, element_lib, data_library, cooling,
flux_file, irr_time, output = "number_density",
truncation=1E-12, impurity = (5E-6, 1E-3),
truncation=1E-12, impurity = (5E-6, 1E-3),
dump_file = "dump_file")
This function returns a string of the irradation-related input blocks. This
function is meant to be used with files created by the mesh_to_geom
This function returns a string of the irradation-related input blocks. This
function is meant to be used with files created by the mesh_to_geom
function, in order to append the remaining input blocks to form a complete
ALARA input file. Only the simplest irradiation schedule is supported: a
single pulse of time <irr_time>. The notation in this function is consistent
ALARA input file. Only the simplest irradiation schedule is supported: a
single pulse of time <irr_time>. The notation in this function is consistent
with the ALARA users' guide, found at:
http://alara.engr.wisc.edu/users.guide.html/
Expand Down Expand Up @@ -481,7 +484,7 @@ def irradiation_blocks(material_lib, element_lib, data_library, cooling,
The impurity parameters (see ALARA users' guide).
dump_file: str, optional
Path to the dump file.
Returns
-------
s : str
Expand Down Expand Up @@ -513,7 +516,7 @@ def irradiation_blocks(material_lib, element_lib, data_library, cooling,
" {0} flux_1 pulse_once 0 s\nend\n\n".format(irr_time))

s += "pulsehistory pulse_once\n 1 0.0 s\nend\n\n"

# Output block
s += "output zone\n units Ci cm3\n"
if isinstance(output, collections.Iterable) and not isinstance(output, basestring):
Expand All @@ -530,3 +533,146 @@ def irradiation_blocks(material_lib, element_lib, data_library, cooling,
s += "dump_file {0}\n".format(dump_file)

return s

def _build_matrix(N):
""" This function builds burnup matrix, A. Decay only.
"""

A = np.zeros((len(N), len(N)))

# convert N to id form
N_id = []
for i in range(len(N)):
if isinstance(N[i], str):
ID = nucname.id(N[i])
else:
ID = N[i]
N_id.append(ID)

sds = SimpleDataSource()

# Decay
for i in range(len(N)):
A[i, i] -= decay_const(N_id[i])

# Find decay parents
for k in range(len(N)):
if N_id[i] in decay_children(N_id[k]):
A[i, k] += branch_ratio(N_id[k], N_id[i])*decay_const(N_id[k])
return A

def _rat_apprx_14(A, t, n_0):
""" CRAM of order 14
Parameters
---------
A : numpy array
Burnup matrix
t : float
Time step
n_0: numpy array
Inital composition vector
"""

theta = np.array([ -8.8977731864688888199 + 16.630982619902085304j,
-3.7032750494234480603 + 13.656371871483268171j,
-.2087586382501301251 + 10.991260561901260913j,
3.9933697105785685194 + 6.0048316422350373178j,
5.0893450605806245066 + 3.5888240290270065102j,
5.6231425727459771248 + 1.1940690463439669766j,
2.2697838292311127097 + 8.4617379730402214019j])

alpha = np.array([-.000071542880635890672853 + .00014361043349541300111j,
.0094390253107361688779 - .01784791958483017511j,
-.37636003878226968717 + .33518347029450104214j,
-23.498232091082701191 - 5.8083591297142074004j,
46.933274488831293047 + 45.643649768827760791j,
-27.875161940145646468 - 102.14733999056451434j,
4.8071120988325088907 - 1.3209793837428723881j])

alpha_0 = np.array([1.8321743782540412751e-14])

s = 7
A = A*t
n = 0*n_0

for j in range(7):
n = n + np.linalg.solve(A - theta[j] * np.identity(np.shape(A)[0]), alpha[j]*n_0)

n = 2*n.real
n = n + alpha_0*n_0

return n

def _rat_apprx_16(A, t, n_0):
""" CRAM of order 16
Parameters
---------
A : numpy array
Burnup matrix
t : float
Time step
n_0: numpy array
Inital composition vector
"""
theta = np.array([ -10.843917078696988026 + 19.277446167181652284j,
-5.2649713434426468895 + 16.220221473167927305j,
5.9481522689511774808 + 3.5874573620183222829j,
3.5091036084149180974 + 8.4361989858843750826j,
6.4161776990994341923 + 1.1941223933701386874j,
1.4193758971856659786 + 10.925363484496722585j,
4.9931747377179963991 + 5.9968817136039422260j,
-1.4139284624888862114 + 13.497725698892745389j])

alpha = np.array([ -.0000005090152186522491565 - .00002422001765285228797j,
.00021151742182466030907 + .0043892969647380673918j,
113.39775178483930527 + 101.9472170421585645j,
15.059585270023467528 - 5.7514052776421819979j,
-64.500878025539646595 - 224.59440762652096056j,
-1.4793007113557999718 + 1.7686588323782937906j,
-62.518392463207918892 - 11.19039109428322848j,
.041023136835410021273 - .15743466173455468191j])

alpha_0 = np.array([2.1248537104952237488e-16])


s = 8
A = A*t
n = 0*n_0

for j in range(8):
n = n + np.linalg.solve(A - theta[j] * np.identity(np.shape(A)[0]), alpha[j]*n_0)

n = 2*n.real
n = n + alpha_0*n_0
return n

def cram(N, t, n_0, order):
""" This function returns matrix exponential solution n using CRAM14 or CRAM16
Parameters
----------
N : list or array
Array of nuclides under consideration
t : float
Time step
n_0 : list or array
Nuclide concentration vector
order : int
Order of method. Only 14 and 16 are supported.
"""

n_0 = np.array(n_0)
A = _build_matrix(N)

if order == 14:
return _rat_apprx_14(A, t, n_0)

elif order == 16:
return _rat_apprx_16(A, t, n_0)

else:
msg = 'Rational approximation of degree {0} is not supported.'.format(order)
raise ValueError(msg)

Loading

0 comments on commit 5463170

Please sign in to comment.