def test_average_atom_Ni_Al(self):
"""Create A-atom potential for a Ni-Al eam/alloy potential and 15% Al
The input potential is from Ref. [1]_ and was downloaded from
the NIST database [2]_. The generated The generated A-atom
potential is compared to a reference A-atom potential, which
was created with an independent implementation. This is not
a very strong test, but should capture some regressions.
References
----------
[1] G.P. Purja Pun, and Y. Mishin (2009), "Development of an
interatomic potential for the Ni-Al system", Philosophical
Magazine, 89(34-36), 3245-3267. DOI: 10.1080/14786430903258184.
[2] https://www.ctcms.nist.gov/potentials/Download/2009--Purja-Pun-G-P-Mishin-Y--Ni-Al/2/Mishin-Ni-Al-2009.eam.alloy
"""
input_table = "Mishin-Ni-Al-2009.eam.alloy"
reference_table = "Mishin-Ni-Al-2009_reference_A-atom_Ni85Al15.eam.alloy"
concentrations = np.array((0.85, 0.15))
source, parameters, F, f, rep = io.read_eam(input_table)
(new_parameters, new_F, new_f,
new_rep) = average_atom.average_potential(concentrations, parameters,
F, f, rep)
ref_source, ref_parameters, ref_F, ref_f, ref_rep = io.read_eam(
reference_table)
diff_F = np.linalg.norm(ref_F - new_F)
diff_f = np.linalg.norm(ref_f - new_f)
diff_rep = np.linalg.norm(ref_rep - new_rep)
print(diff_F, diff_f, diff_rep)
self.assertTrue(diff_F < self.tol)
self.assertTrue(diff_f < self.tol)
self.assertTrue(diff_rep < self.tol)
def test_average_atom_Fe_Cu_Ni(self):
"""Create A-atom potential for a Fe-Cu-Ni eam/alloy potential at equicomposition
The input potential is from Ref. [1]_ and was downloaded from
the NIST database [2]_. The generated The generated A-atom
potential is compared to a reference A-atom potential, which
was created with an independent implementation. This is not
a very strong test, but should capture some regressions.
References
----------
[1] G. Bonny, R.C. Pasianot, N. Castin, and L. Malerba (2009),
"Ternary Fe-Cu-Ni many-body potential to model reactor
pressure vessel steels: First validation by simulated
thermal annealing", Philosophical Magazine, 89(34-36),
3531-3546. DOI: 10.1080/14786430903299824.
[2] https://www.ctcms.nist.gov/potentials/Download/2009--Bonny-G-Pasianot-R-C-Castin-N-Malerba-L--Fe-Cu-Ni/1/FeCuNi.eam.alloy
"""
input_table = "FeCuNi.eam.alloy"
reference_table = "FeCuNi_reference_A-atom_Fe33Cu33Ni33.eam.alloy"
concentrations = np.array((1.0 / 3.0, 1.0 / 3.0, 1.0 / 3.0))
source, parameters, F, f, rep = io.read_eam(input_table)
(new_parameters, new_F, new_f,
new_rep) = average_atom.average_potential(concentrations, parameters,
F, f, rep)
ref_source, ref_parameters, ref_F, ref_f, ref_rep = io.read_eam(
reference_table)
diff_F = np.linalg.norm(ref_F - new_F)
diff_f = np.linalg.norm(ref_f - new_f)
diff_rep = np.linalg.norm(ref_rep - new_rep)
print(diff_F, diff_f, diff_rep)
self.assertTrue(diff_F < self.tol)
self.assertTrue(diff_f < self.tol)
self.assertTrue(diff_rep < self.tol)
def average(input_table, output_table, concentrations):
"""Create Average-atom potential for an Embedded Atom Method potential
Read an EAM potential from INPUT_TABLE, create the Average-atom
potential for the random alloy with composition specified
by CONCENTRATIONS and write a new table with both the original
and the A-atom potential functions to OUTPUT_TABLE.
CONCENTRATIONS is a whitespace-separated list of the concentration of
the elements, in the order in which the appear in the input table.
"""
source, parameters, F, f, rep = io.read_eam(input_table)
(new_parameters, new_F, new_f, new_rep) = average_atom.average_potential(
np.array(concentrations, dtype=float), parameters, F, f, rep
)
composition = " ".join(
[str(c * 100.0) + f"% {e}," for c, e in zip(np.array(concentrations, dtype=float), parameters.symbols)]
)
composition = composition.rstrip(",")
source += f", averaged for composition {composition}"
io.write_eam(
source,
new_parameters,
new_F,
new_f,
new_rep,
output_table,
kind="eam/alloy",
)