The properties are associated something like this:
sectionAssignment
connects section
to set
set
is the container for element
section
connects sectionAssignment
to material
instance
is connected to part
(could be from a part from another model)
part
is connected to model
model
is connected to section
Use the .inp
or .cae
file if you can. The following gets it from an opened cae
file. To thoroughly get elements
from materials
, you would do something like the following, assuming you're starting your search in rootAssembly.instances
:
- Find the
parts
which the instances
were created from.
- Find the
models
which contain these parts
.
- Look for all
sections
with material_name
in these parts
, and store all the sectionNames
associated with this section
- Look for all
sectionAssignments
which references these sectionNames
- Under each of these
sectionAssignments
, there is an associated region
object which has the name (as a string) of an elementSet
and the name of a part
. Get all the elements
from this elementSet
in this part
.
Cleanup:
- Use the Python
set
object to remove any multiple references to the same element.
- Multiply the number of elements in this set by the number of identical part instances that refer to this material in
rootAssembly
.
E.g., for some cae
model variable called model
:
model_part_repeats = {}
model_part_elemLabels = {}
for instance in model.rootAssembly.instances.values():
p = instance.part.name
m = instance.part.modelName
try:
model_part_repeats[(m, p)] += 1
continue
except KeyError:
model_part_repeats[(m, p)] = 1
# Get all sections in model
sectionNames = []
for s in mdb.models[m].sections.values():
if s.material == material_name: # material_name is already known
# This is a valid section - search for section assignments
# in part for this section, and then the associated set
sectionNames.append(s.name)
if sectionNames:
labels = []
for sa in mdb.models[m].parts[p].sectionAssignments:
if sa.sectionName in sectionNames:
eset = sa.region[0]
labels = labels + [e.label for e in mdb.models[m].parts[p].sets[eset].elements]
labels = list(set(labels))
model_part_elemLabels[(m,p)] = labels
else:
model_part_elemLabels[(m,p)] = []
num_elements_with_material = sum([model_part_repeats[k]*len(model_part_elemLabels[k]) for k in model_part_repeats])
Finally, grab the material density associated with material_name
then multiply it by num_elements_with_material
.
Of course, this method will be extremely slow for larger models, and it is more advisable to use string techniques on the .inp
file for faster performance.