def _get_destruction(self, nuc, decay=True):
"""Computes the destruction rate of the nuclide.
Parameters
----------
nuc : int
Name of the nuclide in question
decay : bool
True if the decay constant should be added to the returned value.
False if only destruction from neutron reactions should be considered.
Returns
-------
d : float
Destruction rate of the nuclide.
"""
xscache = self.xscache
sig_a = sigma_a(nuc, xs_cache=xscache)
d = utils.from_barns(sig_a[0], 'cm2') * xscache['phi_g'][0]
if decay and not np.isnan(data.decay_const(nuc)):
d += data.decay_const(nuc)
return d
def _get_destruction(self, nuc, decay=True):
"""Computes the destruction rate of the nuclide.
Parameters
----------
nuc : int
Name of the nuclide in question
decay : bool
True if the decay constant should be added to the returned value.
False if only destruction from neutron reactions should be considered.
Returns
-------
d : float
Destruction rate of the nuclide.
"""
xscache = self.xscache
sig_a = sigma_a(nuc, xs_cache=xscache)
d = utils.from_barns(sig_a[0], 'cm2') * xscache['phi_g'][0]
if decay and not np.isnan(data.decay_const(nuc)):
d += data.decay_const(nuc)
return d
def _traversal(self, nuc, A, out, depth=0):
"""Nuclide transmutation traversal method.
This method will traverse the reaction tree recursively, using a DFS
algorithm. On termination, the method will return all number densities
after a given time that are a result of the starting nuclide.
Parameters
----------
nuc : int
ID of the active nuclide for the traversal.
A : NumPy 2-dimensional array
Current state of the coupled equation matrix.
out : dict
A dictionary containing the final recorded number densities for each
nuclide. Keys are nuclide names in integer id form. Values are
number densities for the coupled nuclide in float format. This is
modified in place.
depth : int
Current depth of traversal (root at 0). Should never be provided by user.
"""
t = self.t
tol = self.tol
phi = self.xscache['phi_g'][0]
temp = self.temp
xscache = self.xscache
if self.log is not None:
self._log_tree(depth, nuc, 1.0)
prod = {}
# decay info
lam = data.decay_const(nuc)
decay_branches = {} if lam == 0 else self._decay_branches(nuc)
for decay_child, branch_ratio in decay_branches.items():
prod[decay_child] = lam * branch_ratio
# reaction daughters
for rx in self.rxs:
try:
child = rxname.child(nuc, rx)
except RuntimeError:
continue
child_xs = xscache[nuc, rx, temp][0]
rr = utils.from_barns(child_xs, 'cm2') * phi # reaction rate
prod[child] = rr + prod.get(child, 0.0)
# Cycle production dictionary
for child in prod:
# Grow matrix
d = self._get_destruction(child)
B = self._grow_matrix(A, prod[child], d)
# Create initial density vector
n = B.shape[0]
N0 = np.zeros((n, 1), dtype=float)
N0[0] = 1.0
# Compute matrix exponential and dot with density vector
eB = linalg.expm(B * t)
N_final = np.dot(eB, N0) # <-- DENSE
#N_final = eB.dot(N0) # <-- SPARSE
if self.log is not None:
self._log_tree(depth + 1, child, N_final[-1])
# Check against tolerance and continue traversal
if N_final[-1] > tol:
self._traversal(child, B, out, depth=depth + 1)
# On recursion exit or truncation, write data from this nuclide
outval = N_final[-1, 0] + out.get(child, 0.0)
if 0.0 < outval:
out[child] = outval
def test_from_barns():
assert_equal(3E-3, utils.from_barns(3, 'KB'))
def test_from_barns():
assert_equal(3E-3, utils.from_barns(3, 'KB'))
def _traversal(self, nuc, A, out, depth=0):
"""Nuclide transmutation traversal method.
This method will traverse the reaction tree recursively, using a DFS
algorithm. On termination, the method will return all number densities
after a given time that are a result of the starting nuclide.
Parameters
----------
nuc : int
ID of the active nuclide for the traversal.
A : NumPy 2-dimensional array
Current state of the coupled equation matrix.
out : dict
A dictionary containing the final recorded number densities for each
nuclide. Keys are nuclide names in integer id form. Values are
number densities for the coupled nuclide in float format. This is
modified in place.
depth : int
Current depth of traversal (root at 0). Should never be provided by user.
"""
t = self.t
tol = self.tol
phi = self.xscache['phi_g'][0]
temp = self.temp
xscache = self.xscache
if self.log is not None:
self._log_tree(depth, nuc, 1.0)
prod = {}
# decay info
lam = data.decay_const(nuc)
decay_branches = {} if lam == 0 else self._decay_branches(nuc)
for decay_child, branch_ratio in decay_branches.items():
prod[decay_child] = lam * branch_ratio
# reaction daughters
for rx in self.rxs:
try:
child = rxname.child(nuc, rx)
except RuntimeError:
continue
child_xs = xscache[nuc, rx, temp][0]
rr = utils.from_barns(child_xs, 'cm2') * phi # reaction rate
prod[child] = rr + prod.get(child, 0.0)
# Cycle production dictionary
for child in prod:
# Grow matrix
d = self._get_destruction(child)
B = self._grow_matrix(A, prod[child], d)
# Create initial density vector
n = B.shape[0]
N0 = np.zeros((n, 1), dtype=float)
N0[0] = 1.0
# Compute matrix exponential and dot with density vector
eB = linalg.expm(B * t)
N_final = np.dot(eB, N0) # <-- DENSE
#N_final = eB.dot(N0) # <-- SPARSE
if self.log is not None:
self._log_tree(depth+1, child, N_final[-1])
# Check against tolerance and continue traversal
if N_final[-1] > tol:
self._traversal(child, B, out, depth=depth+1)
# On recursion exit or truncation, write data from this nuclide
outval = N_final[-1,0] + out.get(child, 0.0)
if 0.0 < outval:
out[child] = outval
def test_from_barns():
assert_equal(3e-3, utils.from_barns(3, "KB"))
