def main():
nastran_path = r'C:\Program Files\Siemens\SimcenterNastran_2019.2\bin\nastran.exe'
print(sys.argv)
export_dir = sys.argv[1]
print('export_dir = %r' % export_dir)
#folders_file = os.path.abspath('.')
#files2 = get_all_files(folders_file, '.bdf')
#files2 += get_all_files(folders_file, '.nas')
#files2 += get_all_files(folders_file, '.dat')
#files2 = list(set(files2))
#files2.sort()
max_size = 4.2 # MB
dirname = '.'
files2 = get_files_of_type(dirname, '.bdf', max_size=max_size)
files2 += get_files_of_type(dirname, '.nas', max_size=max_size)
files2 += get_files_of_type(dirname, '.dat', max_size=max_size)
files2 += get_files_of_type(dirname, '.ecd', max_size=max_size)
files2 = list(set(files2))
files2.sort()
skip_files = []
files = [
fname for fname in files2
if not os.path.basename(fname).startswith('out_')
and '.test_op2.' not in fname # removing test output files
and '.test_bdf.' not in fname and '.test_bdfv.' not in fname and
'tecplot' not in fname and os.path.basename(fname) not in skip_files
]
for fname in files:
#print(fname)
fname2 = update_with_post(fname, export_dir)
if fname2 is None:
continue
if not RUN_NASTRAN:
continue
keywords = 'scr=yes old=no news=no'
run_nastran(fname2,
nastran_cmd=nastran_path,
keywords=keywords,
run=True,
run_in_bdf_dir=True)
def main():
print(sys.argv)
#export_dir = sys.argv[1]
export_dir = r'C:\MSC.Software\msc_nastran_runs'
print('export_dir = %r' % export_dir)
#folders_file = os.path.abspath('.')
#files2 = get_all_files(folders_file, '.bdf')
#files2 += get_all_files(folders_file, '.nas')
#files2 += get_all_files(folders_file, '.dat')
#files2 = list(set(files2))
#files2.sort()
max_size = 4.2 # MB
dirname = r'C:\MSC.Software\msc_nastran_docs_2020\tpl'
files2 = get_files_of_type(dirname, '.bdf', max_size=max_size)
files2 += get_files_of_type(dirname, '.nas', max_size=max_size)
files2 += get_files_of_type(dirname, '.dat', max_size=max_size)
files2 += get_files_of_type(dirname, '.ecd', max_size=max_size)
files2 = list(set(files2))
files2.sort()
skip_files = []
files = [
fname for fname in files2
if not os.path.basename(fname).startswith('out_')
and '.test_op2.' not in fname # removing test output files
and '.test_bdf.' not in fname and '.test_bdfv.' not in fname and
'tecplot' not in fname and os.path.basename(fname) not in skip_files
]
for fname in files:
#print(fname)
fname2 = update_with_post(fname, export_dir)
if fname2 is None:
continue
if not RUN_NASTRAN:
continue
keywords = 'scr=yes old=no news=no notify=no'
run_nastran(fname2,
nastran_cmd=NASTRAN_EXE,
keywords=keywords,
run=True,
run_in_bdf_dir=True)
def test_panel_buckling_bwb(self):
"""panel buckling doesn't work in Python 3"""
input_dir = os.path.join(model_path, 'bwb')
bdf_filename = os.path.join(input_dir, 'BWB_saero.bdf')
workpath = os.path.join(os.getcwd(), 'aero_buckling')
op2_filename = os.path.join(workpath, 'BWB_saero.op2')
#op2_filename = 'BWB_saero.op2'
if workpath is not None:
if not os.path.exists(workpath):
os.makedirs(workpath)
os.chdir(workpath)
keywords = {
'old': 'no',
'scr': 'yes',
'bat': 'no',
'news': 'no',
}
if not os.path.exists(op2_filename) and 0:
run_nastran(bdf_filename, keywords=keywords)
if not os.path.exists(op2_filename):
op2_filename = None
run_panel_buckling(bdf_filename=bdf_filename,
op2_filename=op2_filename,
isubcase=1,
workpath=workpath,
build_model=False,
rebuild_patches=True,
rebulid_buckling_bdfs=False,
mode='displacement',
parse_eigenvalues=False,
run_nastran=False,
nastran_keywords=keywords,
overwrite_op2_if_exists=True,
op2_filenames=None)
analysis.import_from_bdf(input_file) # import bdf model
#%%
spanel_p = SuperAeroPanel5(1) # init panel
spanel_p.init_from_femap(
femap
) # popup femap interface to insert the location and config of the panel
analysis.add_superpanel(spanel_p)
analysis.write_cards() # write the panels on the pyNastran bdf interface
analysis.export_to_bdf(output_file) # exports to bdf file
#%% run nastran
run_nastran(output_file, nastran_cmd=nastran_exe, keywords=['old=no'])
#%% output results
panel_flutter_analysis(analysis, output_file)
#%% now with the ZONA51 theory
analysis = PanelFlutterAnalysisModel()
analysis.load_analysis_from_yaml(os.path.join(base_path, r'analysis.yml'))
analysis.import_from_bdf(input_file) # reset the bdf file
# analysis.import_from_bdf(input_file, reset_bdf=True) # reset the bdf file
analysis.subcases[1].method = 'PK'
# you may supply a value of minimum Mach number in your analysis, by default this value is sqrt(2) (i.e. 45° -> square)
spanel = SuperAeroPanel1(1, np.min(analysis.subcases[1].machs))
def fully_stressed_design(bdf_filename,
keywords=None,
niterations_max=2,
alpha=0.9):
"""
Optimizes shell thickness for minimum weight (ONLY shells)
Parameters
----------
bdf_filename : str; BDF()
the BDF filename or model
Returns
-------
desvars : dict[id]=values
the "optimization history of the design variables
"""
force = True
iteration = 0
niterations_max = 10
if isinstance(bdf_filename, str):
model = read_bdf(bdf_filename)
elif isinstance(bdf_filename, BDF):
model = bdf_filename
bdf_filename = model.bdf_filename
else:
raise TypeError(bdf_filename)
doptparm = model.doptprm
if doptparm is not None:
if 'FSDALP' in doptparm.params:
alpha = doptparm.params['FSDALP']
else:
alpha = doptparm.defaults['FSDALP']
if not isinstance(alpha, float):
msg = 'FSDALP on DOPTPARM must be an integer; FSDALP=%r' % (alpha)
raise TypeError(msg)
if not (0. < niterations_max <= 1.):
msg = 'FSDALP on DOPTPARM must be between (0. < n <= 1.0); FSDALP=%s' % (
alpha)
raise ValueError(msg)
if 'FSDMAX' in doptparm.params:
niterations_max = doptparm.params['FSDMAX']
else:
niterations_max = doptparm.defaults['FSDMAX']
if not isinstance(niterations_max, int):
msg = 'FSDMAX on DOPTPARM must be an integer; FSDMAX=%r' % (
niterations_max)
raise TypeError(msg)
if niterations_max <= 0:
msg = 'FSDMAX on DOPTPARM must be > 0; FSDMAX=%s' % (
niterations_max)
raise ValueError(msg)
else:
niterations_max = 2
alpha = 0.9
dresps_to_consider, desvars_to_consider, dvprels_to_consider = get_inputs(
model)
pid_to_eid = model.get_property_id_to_element_ids_map()
bdf_filename2 = 'fem_baseline.bdf'
op2_filename2 = 'fem_baseline.op2'
try:
shutil.copyfile(bdf_filename, bdf_filename2)
except TypeError:
msg = 'cannot copy %r to %r' % (bdf_filename, bdf_filename2)
raise TypeError(msg)
while iteration < niterations_max:
if not os.path.exists(op2_filename2) or force:
run_nastran(bdf_filename2, keywords=keywords)
results = read_op2(op2_filename2,
combine=True,
log=None,
debug=False,
debug_file=None,
build_dataframe=False,
skip_undefined_matrices=True,
mode='msc')
isubcase = 1
itime = 0
stress_per_region = {}
nopt = 0
for pid, region in iteritems(regions):
print('pid=%s region=%s' % (pid, region))
(tmin, tmax, ovm_min, ovm_max) = region
prop = model.properties[pid]
told = prop.t
eids_requested = pid_to_eid[pid]
print('eids_requested[pid=%s] = %s' % (pid, eids_requested))
#def compute_critical_stress(results, subcases)
#def compute_critical_stress(results, subcases):
stress = []
eid_node = []
for res in [results.cquad4_stress, results.ctria3_stress]:
resi = res[isubcase]
eid_nodei = resi.element_node
#print('eid_nodei = %s' % (eid_nodei))
eid = eid_nodei[:, 0]
stress_data = resi.data
eid_node.append(eid_nodei)
# A
#i = np.where(eid == eids_requested)
# B
#j = np.searchsorted(eid, eids_requested)
#i = np.where(eid[j] == eids_requested)
#j = np.in1d(eids_requested, eid) # A in B
j = np.in1d(eid, eids_requested) # A in B
i = np.where(j)
#print('i = %s' % i) #[0]
#print('j = %s' % j) #[0]
#print('eid = %s' % eid) #[0]
#print('eids_requested = %s' % eids_requested) #[0]
if len(i) == 0:
continue
#print('i=%s; ni=%s' % (i, len(i)))
stress_datai = stress_data[itime, i, 7]
#print('eids = %s' % eid[i])
#print('stress_datai = %s' % stress_datai)
stress.append(stress_datai)
#print('stressA = %s' % stress)
stress = np.hstack(stress)
#print('stressB = %s' % stress)
# PROD area
# PSHELL/PCOMP thickness
# PSHEAR thickness
eid_node = np.vstack(eid_node)
stress_max = stress.max()
stress_min = stress.min()
print('stress_min=%s' % stress_min)
print('stress_max=%s' % stress_max)
istress_max = np.where(stress == stress_max)[0]
istress_min = np.where(stress == stress_min)[0]
eid_max = eid_node[istress_max, 0]
eid_min = eid_node[istress_min, 0]
peak_stress = max(abs(stress_max), abs(stress_min))
tnew = told * stress_max / ovm_max
tnew = min(tmax, tnew)
tnew = max(tmin, tnew)
#tnew = (oi/omax)**alpha * ti_old
tratio = tnew / told
if np.allclose(tratio, 1.):
continue
nopt += 1
stress_per_region = [stress_min, stress_max, eid_min, eid_max]
print('pid=%s' % pid)
print(
' stress_per_region (ovm_min, ovm_max, eid_min, eid_max) => %s'
% stress_per_region)
print(' told=%s tnew=%s tratio=%s\n' % (told, tnew, tratio))
prop.t *= tratio
prop.z1 *= tratio
prop.z2 *= tratio
regions2[pid] = [
tnew, peak_stress, stress_max, eid_max, stress_min, eid_min
] # t_new, ovm_new
if nopt == 0:
break
#eid_node = np.hstack(eid_node)
#s = np.hstack(eid_node)
iteration += 1
bdf_filename2 = 'fem_%i.bdf' % iteration
op2_filename2 = 'fem_%i.op2' % iteration
model.write_bdf(bdf_filename2)
print('regions2 = %s' % regions2)
return regions2
def fully_stressed_design(bdf_filename, keywords=None,
niterations_max=2, alpha=0.9):
"""
Optimizes shell thickness for minimum weight (ONLY shells)
Parameters
----------
bdf_filename : str; BDF()
the BDF filename or model
Returns
-------
desvars : dict[id]=values
the "optimization history of the design variables
"""
force = True
iteration = 0
niterations_max = 10
if isinstance(bdf_filename, str):
model = read_bdf(bdf_filename)
elif isinstance(bdf_filename, BDF):
model = bdf_filename
bdf_filename = model.bdf_filename
else:
raise TypeError(bdf_filename)
doptparm = model.doptprm
if doptparm is not None:
if 'FSDALP' in doptparm.params:
alpha = doptparm.params['FSDALP']
else:
alpha = doptparm.defaults['FSDALP']
if not isinstance(alpha, float):
msg = 'FSDALP on DOPTPARM must be an integer; FSDALP=%r' % (alpha)
raise TypeError(msg)
if not(0. < niterations_max <= 1.):
msg = 'FSDALP on DOPTPARM must be between (0. < n <= 1.0); FSDALP=%s' % (alpha)
raise ValueError(msg)
if 'FSDMAX' in doptparm.params:
niterations_max = doptparm.params['FSDMAX']
else:
niterations_max = doptparm.defaults['FSDMAX']
if not isinstance(niterations_max, int):
msg = 'FSDMAX on DOPTPARM must be an integer; FSDMAX=%r' % (niterations_max)
raise TypeError(msg)
if niterations_max <= 0:
msg = 'FSDMAX on DOPTPARM must be > 0; FSDMAX=%s' % (niterations_max)
raise ValueError(msg)
else:
niterations_max = 2
alpha = 0.9
dresps_to_consider, desvars_to_consider, dvprels_to_consider = get_inputs(model)
pid_to_eid = model.get_property_id_to_element_ids_map()
bdf_filename2 = 'fem_baseline.bdf'
op2_filename2 = 'fem_baseline.op2'
try:
shutil.copyfile(bdf_filename, bdf_filename2)
except TypeError:
msg = 'cannot copy %r to %r' % (bdf_filename, bdf_filename2)
raise TypeError(msg)
while iteration < niterations_max:
if not os.path.exists(op2_filename2) or force:
run_nastran(bdf_filename2, keywords=keywords)
results = read_op2(op2_filename2, combine=True, log=None,
debug=False,
debug_file=None,
build_dataframe=False,
skip_undefined_matrices=True,
mode='msc')
isubcase = 1
itime = 0
stress_per_region = {}
nopt = 0
for pid, region in iteritems(regions):
print('pid=%s region=%s' % (pid, region))
(tmin, tmax, ovm_min, ovm_max) = region
prop = model.properties[pid]
told = prop.t
eids_requested = pid_to_eid[pid]
print('eids_requested[pid=%s] = %s' % (pid, eids_requested))
#def compute_critical_stress(results, subcases)
#def compute_critical_stress(results, subcases):
stress = []
eid_node = []
for res in [results.cquad4_stress, results.ctria3_stress]:
resi = res[isubcase]
eid_nodei = resi.element_node
#print('eid_nodei = %s' % (eid_nodei))
eid = eid_nodei[:, 0]
stress_data = resi.data
eid_node.append(eid_nodei)
# A
#i = np.where(eid == eids_requested)
# B
#j = np.searchsorted(eid, eids_requested)
#i = np.where(eid[j] == eids_requested)
#j = np.in1d(eids_requested, eid) # A in B
j = np.in1d(eid, eids_requested) # A in B
i = np.where(j)
#print('i = %s' % i) #[0]
#print('j = %s' % j) #[0]
#print('eid = %s' % eid) #[0]
#print('eids_requested = %s' % eids_requested) #[0]
if len(i) == 0:
continue
#print('i=%s; ni=%s' % (i, len(i)))
stress_datai = stress_data[itime, i, 7]
#print('eids = %s' % eid[i])
#print('stress_datai = %s' % stress_datai)
stress.append(stress_datai)
#print('stressA = %s' % stress)
stress = np.hstack(stress)
#print('stressB = %s' % stress)
# PROD area
# PSHELL/PCOMP thickness
# PSHEAR thickness
eid_node = np.vstack(eid_node)
stress_max = stress.max()
stress_min = stress.min()
print('stress_min=%s' % stress_min)
print('stress_max=%s' % stress_max)
istress_max = np.where(stress == stress_max)[0]
istress_min = np.where(stress == stress_min)[0]
eid_max = eid_node[istress_max, 0]
eid_min = eid_node[istress_min, 0]
peak_stress = max(abs(stress_max), abs(stress_min))
tnew = told * stress_max / ovm_max
tnew = min(tmax, tnew)
tnew = max(tmin, tnew)
#tnew = (oi/omax)**alpha * ti_old
tratio = tnew / told
if np.allclose(tratio, 1.):
continue
nopt += 1
stress_per_region = [stress_min, stress_max,
eid_min, eid_max]
print('pid=%s' % pid)
print(' stress_per_region (ovm_min, ovm_max, eid_min, eid_max) => %s' % stress_per_region)
print(' told=%s tnew=%s tratio=%s\n' %(told, tnew, tratio))
prop.t *= tratio
prop.z1 *= tratio
prop.z2 *= tratio
regions2[pid] = [tnew, peak_stress, stress_max, eid_max, stress_min, eid_min] # t_new, ovm_new
if nopt == 0:
break
#eid_node = np.hstack(eid_node)
#s = np.hstack(eid_node)
iteration += 1
bdf_filename2 = 'fem_%i.bdf' % iteration
op2_filename2 = 'fem_%i.op2' % iteration
model.write_bdf(bdf_filename2)
print('regions2 = %s' % regions2)
return regions2