BDF Overview
Introduction
This is meant as a tutorial on how to use the pyNastran pyNastran.bdf.bdf.BDF class
The head/tail/file_slice methods can be found at:
These examples can be found at:
Example 1: Read/Write
this example will demonstate:
reading the BDF
getting some basic information
writing the BDF
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'solid_bending')
>>> bdf_filename = os.path.join(test_path, 'solid_bending.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename)
For unicode:
The standard encoding is utf-8, but most English decks should use latin1 and will fail with utf-8.
If you just have ascii, then you don’t need to worry about the encoding.
>>> model.read_bdf(bdf_filename, encoding='latin1')
print information about the model
>>> print(model.get_bdf_stats())
---BDF Statistics---
SOL 101
bdf.loads[1]
FORCE: 23
bdf.loads[2]
LOAD: 1
bdf.params
PARAM : 2
bdf.nodes
GRID : 72
bdf.elements
CTETRA : 186
bdf.properties
PSOLID : 1
bdf.materials
MAT1 : 1
bdf.coords
CORD2R : ???
write the file
>>> bdf_filename_out = os.path.join(test_path, 'solid_bending_out.bdf')
>>> model.write_bdf(bdf_filename_out)
looking at the output
>>> print(file_slice(bdf_filename_out, 94, 100))
GRID 71 .500008 1.61116 3.
GRID 72 .500015 1.00001 3.
$ELEMENTS_WITH_PROPERTIES
PSOLID 1 1
CTETRA 1 1 8 13 67 33
CTETRA 2 1 8 7 62 59
write the file with large field format; double precision
>>> bdf_filename_out2 = os.path.join(test_path, 'solid_bending_out2.bdf')
>>> model.write_bdf(bdf_filename_out2, size=16, is_double=False)
>>> print(file_slice(bdf_filename_out2, 166, 175))
GRID* 71 .500008 1.61116
* 3.
GRID* 72 .500015 1.00001
* 3.
$ELEMENTS_WITH_PROPERTIES
PSOLID 1 1
CTETRA 1 1 8 13 67 33
CTETRA 2 1 8 7 62 59
CTETRA 3 1 8 45 58 66
write the file with large field format; double precision
>>> bdf_filename_out3 = os.path.join(test_path, 'solid_bending_out3.bdf')
>>> model.write_bdf(bdf_filename_out3, size=16, is_double=True)
>>> print(file_slice(bdf_filename_out3, 166, 175))
GRID* 71 5.0000800000D-011.6111600000D+00
* 3.0000000000D+00
GRID* 72 5.0001500000D-011.0000100000D+00
* 3.0000000000D+00
$ELEMENTS_WITH_PROPERTIES
PSOLID 1 1
CTETRA 1 1 8 13 67 33
CTETRA 2 1 8 7 62 59
CTETRA 3 1 8 45 58 66
Example 2: Printing Nodes
this example will demonstate:
writing cards
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'solid_bending')
>>> bdf_filename = os.path.join(test_path, 'solid_bending.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
Method 1 - using objects
GRIDs
>>> for nid,node in sorted(model.nodes.items()):
>>> f.write(node.write_card(size=8, is_double=False))
GRIDSET
>>> if model.gridSet:
>>> f.write(model.gridSet.write_card(size=8, is_double=False))
SPOINTs
>>> if model.spoints:
>>> f.write(model.spoints.write_card(size=8, is_double=False))
Coord
>>> for cid,coord in sorted(model.coords.items()):
>>> if cid != 0: # if CID=0 is the global frame, skip it
>>> f.write(coord)
Method 2 - using built-in methods
>>> model._write_nodes(f)
>>> model._write_coords(f)
Example 3: Printing Elements/Properties
Print the Element ID and associated Node and Property to an Output File
note this skips rigidElements
this example will demonstate:
using the BDF class to write cards/properties
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'solid_bending')
>>> bdf_filename = os.path.join(test_path, 'solid_bending.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
Method 1 - using objects
>>> for eid, element in sorted(model.elements.items()):
>>> f.write(element.write_card(size=8, is_double=False))
>>> for pid, prop in sorted(model.properties.items()):
>>> f.write(prop.write_card(size=8, is_double=False))
Method 2 - using built-in method
>>> model._write_elements_properties(f)
Method 3 - using built-in methods
>>> model._write_elements(f)
>>> model._write_properties(f)
Example 4: Get Element ID & Type
Print the Element ID and its type(e.g. CQUAD4, CTRIA3, etc.) to a file
note this skips rigidElements
this example will demonstate:
accessing element type information
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'solid_bending')
>>> bdf_filename = os.path.join(test_path, 'solid_bending.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
Method 1 - using objects
>>> for eid,element in sorted(model.elements.items()):
>>> msg = 'eid=%s type=%s\n' %(eid, element.type)
>>> f.write(msg)
Example 5: Get Elements by Node ID
this example will demonstate:
getting the list of elements that share a certain node
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'solid_bending')
>>> bdf_filename = os.path.join(test_path, 'solid_bending.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
given a Node, get the Elements Attached to that Node
assume node 55
doesnt support 0d/1d elements yet
>>> nid_to_eids_map = model.get_node_id_to_element_ids_map()
>>> eids = nid_to_eids_map[55]
convert to elements instead of element IDs
>>> elements = []
>>> for eid in eids:
>>> elements.append(model.Element(eid))
>>> print("eids = %s" % eids)
>>> print("elements =\n %s" % elements)
Example 6: Get Elements by Property ID
this example will demonstate:
getting a list of elements that have a certain property
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'sol_101_elements')
>>> bdf_filename = os.path.join(test_path, 'static_solid_shell_bar.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
Creating a List of Elements based on a Property ID
assume pid=1
>>> pid_to_eids_map = model.get_property_id_to_element_ids_map()
>>> eids4 = pid_to_eids_map[4] # PSHELL
>>> print("eids4 = %s" % eids4)
eids4 = [6, 7, 8, 9, 10, 11]
convert to elements instead of element IDs
>>> elements4 = []
>>> for eid in eids4:
>>> elements4.append(model.Element(eid))
just to verify
>>> elem = model.elements[eids4[0]]
>>> print(elem.pid)
PSHELL 4 1 .25 1 1
Example 7: Get Elements by Material ID
this example will demonstate:
getting a list of elements that have a certain material
our model
>>> import pyNastran
>>> pkg_path = pyNastran.__path__[0]
>>> test_path = os.path.join(pkg_path, '..', 'models', 'sol_101_elements')
>>> bdf_filename = os.path.join(test_path, 'static_solid_shell_bar.bdf')
instantiate the model
>>> from pyNastran.bdf.bdf import BDF
>>> model = BDF()
>>> model.read_bdf(bdf_filename, xref=True)
>>> f = open('junk.out', 'w')
assume you want the eids for material 10
>>> pid_to_eids_map = model.get_property_id_to_element_ids_map()
>>> mid_to_pids_map = model.get_material_id_to_property_ids_map()
>>> pids1 = mid_to_pids_map[1]
>>> print('pids1 = %s' % pids1)
pids1 = [1, 2, 3, 4, 5]
>>> eids = []
>>> for pid in pids1:
>>> eids += pid_to_eids_map[pid]
convert to elements instead of element IDs
>>> elements = []
>>> for eid in eids:
>>> element = model.Element(eid)
>>> elements.append(element)
>>> print(str(element).rstrip())
CBAR 13 1 15 19 0. 1. 0.
$ Direct Text Input for Bulk Data
$ Pset: "shell" will be imported as: "pshell.1"
CHEXA 1 2 2 3 4 1 8 5
6 7
CPENTA 2 2 6 8 5 10 11 9
CPENTA 3 2 6 7 8 10 12 11
CTETRA 4 2 10 11 9 13
CTETRA 5 2 10 12 11 13
CROD 14 3 16 20
CROD 15 3 17 21
CQUAD4 6 4 4 1 14 15
CQUAD4 7 4 3 2 17 16
CTRIA3 8 4 4 3 16
CTRIA3 9 4 16 15 4
CTRIA3 10 4 1 2 17
CTRIA3 11 4 17 14 1
$
CBEAM 12 5 14 18 0. 1. 0. GGG