def main(case):
if (case == 'NASTRAN_PRE'):
dvs_file = 'x_final.dat'
dvs = open(dvs_file)
x_dvs = np.loadtxt(dvs);
dvs.close()
config = spaceio.Config('../config_DSN.cfg')
konfig = copy.deepcopy(config)
computeNastran(konfig, x_dvs)
elif (case == 'NASTRAN_POST'):
postproNastran('struct_nastran.f06','struct_nastran.sol')
elif (case == 'TACS'):
dvs_file = 'x_final.dat'
dvs = open(dvs_file)
x_dvs = np.loadtxt(dvs);
dvs.close()
config = spaceio.Config('../config_DSN.cfg')
konfig = copy.deepcopy(config)
computeTacs(konfig, x_dvs)
def main():
config = spaceio.Config('config.cfg')
data = spaceutil.ordered_bunch()
data.lift_sub = spaceutil.ordered_bunch()
data.lift_sub.sps = config.DATABASE_LIFT_SUB
data.lift_sub.ranges = np.array([[0.5, 0.95], [-5.0, 20.0], [-0.5, 0.5],
[-0.5, 0.5], [-0.5, 0.5]])
data.lift_sup = spaceutil.ordered_bunch()
data.lift_sup.sps = config.DATABASE_LIFT_SUP
data.lift_sup.ranges = np.array([[1.1, 9.0], [-5.0, 20.0], [-0.5, 0.5],
[-0.5, 0.5], [-0.5, 0.5]])
lift_model = spacemodel.RangedModel(data)
data = spaceutil.ordered_bunch()
data.drag_sub = spaceutil.ordered_bunch()
data.drag_sub.sps = config.DATABASE_DRAG_SUB
data.drag_sub.ranges = np.array([[0.5, 0.95], [-5.0, 20.0], [-0.5, 0.5],
[-0.5, 0.5], [-0.5, 0.5]])
data.drag_sup = spaceutil.ordered_bunch()
data.drag_sup.sps = config.DATABASE_DRAG_SUP
data.drag_sup.ranges = np.array([[1.1, 9.0], [-5.0, 20.0], [-0.5, 0.5],
[-0.5, 0.5], [-0.5, 0.5]])
drag_model = spacemodel.RangedModel(data)
mach = 0.5
aoa = 10.0
# XB = np.array([[-0.5, 0.5],[-0.5, 0.5]])
# dvs = LHC_unif(XB,600)
x = np.arange(-0.5, 0.5, 0.01)
y = np.arange(-0.5, 0.5, 0.01)
X, Y = np.meshgrid(x, y)
Z = np.zeros(X.shape)
for i in range(X.shape[0]):
for j in range(X.shape[1]):
model_l = lift_model.find_model([mach, aoa, 0.0, X[i][j], Y[i][j]])
model_d = drag_model.find_model([mach, aoa, 0.0, X[i][j], Y[i][j]])
Z[i][j] = model_l.eval([
mach, aoa, 0.0, X[i][j], Y[i][j]
]) / model_d.eval([mach, aoa, 0.0, X[i][j], Y[i][j]])
fig = plt.figure()
plt.contour(X, Y, Z)
fig.savefig('image.png', dpi=fig.dpi)
# start new design
design = spacedesign.Design(konfig)
# update local state filenames ( ??? why not in Design() )
for key in design.files:
name = design.files[key]
name = os.path.split(name)[-1]
design.files[key] = name
return design
# -------------------------------------------------------------------
# Run Main Program
# -------------------------------------------------------------------
# this is only accessed if running from command prompt
if __name__ == '__main__':
# Command Line Options
# parser=OptionParser()
# parser.add_option("-f", "--func", dest="func_name",
# help="read function", metavar="FUNCTION_NAME")
# (options, args)=parser.parse_args()
config = spaceio.Config('config_DSN.cfg')
eval_design(sys.argv[1], config)
def process_design(regime='BOTH'):
original = False
number_ini = 0
range_number = 840
if original:
build_points_folder = 'BUILD_POINTS_ORIGINAL'
designs_folder = 'DESIGNS_BATCH_1'
else:
build_points_folder = 'BUILD_POINTS'
designs_folder = 'DESIGNS'
desvar = DesignVariables()
if regime == 'ON':
ndim_struct = desvar.ndim_struct_on
pack_structure = desvar.pack_structure_on
elif regime == 'OFF':
ndim_struct = desvar.ndim_struct_off
pack_structure = desvar.pack_structure_off
elif regime == 'BOTH':
ndim_struct = desvar.ndim_struct
pack_structure = desvar.pack_structure
threshold = 1.0001
mass_models = []
for index in range(132):
mass_model = Surfpack('MASS_%05d' % (index + 1), ndim_struct)
# if original:
# mass_model.load_data(os.path.join(build_points_folder,'build_points_mass_%05d.dat' % (index+1)))
# else:
# mass_model.load_data(os.path.join('BUILD_POINTS_ORIGINAL','enriched_points_mass_%05d.dat' % (index+1)))
mass_models.append(mass_model)
thickness_models = []
for index in range(132):
thickness_model = Surfpack('THICKNESS_%05d' % (index + 1), ndim_struct)
# if original:
# thickness_model.load_data(os.path.join(build_points_folder,'build_points_thickness_%05d.dat' % (index+1)))
# else:
# thickness_model.load_data(os.path.join('BUILD_POINTS_ORIGINAL','enriched_points_thickness_%05d.dat' % (index+1)))
thickness_models.append(thickness_model)
area_models = []
for index in range(132):
area_model = Surfpack('AREA_%05d' % (index + 1), ndim_struct)
# if original:
# area_model.load_data(os.path.join(build_points_folder,'build_points_area_%05d.dat' % (index+1)))
# else:
# area_model.load_data(os.path.join('BUILD_POINTS_ORIGINAL','enriched_points_area_%05d.dat' % (index+1)))
area_models.append(area_model)
structure_mass_model = Surfpack('STRUCTURE_MASS', ndim_struct)
structure_area_model = Surfpack('STRUCTURE_AREA', ndim_struct)
# if original:
# structure_mass_model.load_data(os.path.join(build_points_folder,'build_points_STRUCTURE_MASS.dat'))
# structure_area_model.load_data(os.path.join(build_points_folder,'build_points_STRUCTURE_AREA.dat'))
# else:
# structure_mass_model.load_data(os.path.join('BUILD_POINTS_ORIGINAL','enriched_points_STRUCTURE_MASS.dat'))
# structure_area_model.load_data(os.path.join('BUILD_POINTS_ORIGINAL','enriched_points_STRUCTURE_AREA.dat'))
for dsn_index in range(number_ini, range_number):
design_folder = os.path.join(designs_folder,
'DSN_%03d' % (dsn_index + 1))
history_file_name = os.path.join(design_folder,
'STRUCTURE/history_structure.dat')
mass_file_name = os.path.join(design_folder,
'STRUCTURE/lc0_mass_member.dat')
thickness_file_name = os.path.join(design_folder,
'STRUCTURE/lc0_x_final.dat')
postpro_file_name = os.path.join(design_folder,
'STRUCTURE/postpro_load_1.dat')
if os.path.exists(history_file_name) and os.path.exists(
mass_file_name) and os.path.exists(
postpro_file_name) and os.path.exists(thickness_file_name):
history = numpy.loadtxt(history_file_name,
delimiter=',',
skiprows=1)
structure_mass = history[-1, 1]
check = history[-1, 2:5]
if (check[0] < threshold) and (check[1] < threshold) and (
check[2] < threshold):
if structure_mass > 0.0 and structure_mass < 8000.0:
print dsn_index + 1, ': Success'
config = spaceio.Config(
os.path.join(design_folder, 'config_DSN.cfg'))
dvs = pack_structure(config)
structure_mass_model.add(dvs, structure_mass)
mass_data = numpy.loadtxt(mass_file_name)
for index, mass_model in enumerate(mass_models):
mass_model.add(dvs, mass_data[index])
thickness_data = numpy.loadtxt(thickness_file_name)
for index, thickness_model in enumerate(thickness_models):
thickness_model.add(dvs, thickness_data[index])
structure_area = 0
for index, area_model in enumerate(area_models):
area = mass_data[index] / thickness_data[
index] / float(config.MATERIAL_DENSITY)
area_model.add(dvs, area)
structure_area += area
structure_area_model.add(dvs, structure_area)
else:
print dsn_index + 1, ': Too Big or Too Small'
else:
print dsn_index + 1, ': Warning: ', check[0], check[1], check[
2]
else:
print 'Missing:', dsn_index + 1
structure_mass_model.save_data(
os.path.join(build_points_folder,
'enriched_points_STRUCTURE_MASS.dat'))
structure_area_model.save_data(
os.path.join(build_points_folder,
'enriched_points_STRUCTURE_AREA.dat'))
for index, mass_model in enumerate(mass_models):
print 'Save MASS: ', index
mass_model.save_data(
os.path.join(build_points_folder,
'enriched_points_mass_%05d.dat' % (index + 1)))
for index, thickness_model in enumerate(thickness_models):
print 'Save THICKNESS: ', index
thickness_model.save_data(
os.path.join(build_points_folder,
'enriched_points_thickness_%05d.dat' % (index + 1)))
for index, area_model in enumerate(area_models):
print 'Save AREA: ', index
area_model.save_data(
os.path.join(build_points_folder,
'enriched_points_area_%05d.dat' % (index + 1)))
def process_design():
range_number = 300
desvar = DesignVariables()
build_points_folder = 'BUILD_POINTS'
lift_model = Surfpack('LIFT', desvar.ndim - 2)
lift_model.load_data(
os.path.join(build_points_folder,
'build_points_struct_lift_model.dat'))
drag_model = Surfpack('DRAG', desvar.ndim - 2)
drag_model.load_data(
os.path.join(build_points_folder,
'build_points_struct_drag_model.dat'))
threshold = 1.0001
for dsn_index in range(range_number):
design_folder = 'DESIGNS/DSN_%03d' % (dsn_index + 1)
print design_folder
postpro_file_name = os.path.join(design_folder,
'STRUCTURE/postpro_load_1.dat')
history_file_name = os.path.join(design_folder,
'STRUCTURE/history_structure.dat')
mass_file_name = os.path.join(design_folder,
'STRUCTURE/lc0_mass_member.dat')
postpro_file_name = os.path.join(design_folder,
'STRUCTURE/postpro_load_1.dat')
if os.path.exists(history_file_name) and os.path.exists(
mass_file_name) and os.path.exists(postpro_file_name):
history = numpy.loadtxt(history_file_name,
delimiter=',',
skiprows=1)
structure_mass = history[-1, 1]
check = history[-1, 2:5]
if (check[0] < threshold) and (check[1] < threshold) and (
check[2] < threshold):
config = spaceio.Config(
os.path.join(design_folder, 'config_DSN.cfg'))
dvs = desvar.pack(config)
dvs_filtered = dvs[0:3] + dvs[5:11]
print dvs_filtered
with open(postpro_file_name) as fp:
for i, line in enumerate(fp):
if i == 13:
data = line.split(':')[-1].split(',')
lift = float(data[0])
drag = float(data[1])
print lift, drag
elif i > 13:
break
lift_model.add(dvs_filtered, lift)
drag_model.add(dvs_filtered, drag)
lift_model.save_data(
os.path.join(build_points_folder,
'enriched_points_struct_lift_model.dat'))
drag_model.save_data(
os.path.join(build_points_folder,
'enriched_points_struct_drag_model.dat'))
lift_model.build('kriging')
drag_model.build('kriging')
lift_model.save_model('struct_lift.sps')
drag_model.save_model('struct_drag.sps')