def test_freq():
for model in ['plate_clt_donnell_bardell',
'plate_clt_donnell_bardell_w',
'cpanel_clt_donnell_bardell',
'kpanel_clt_donnell_bardell']:
for atype in [3, 4]:
print('Frequency Analysis, atype={0}, model={1}'.format(
atype, model))
p = Panel()
p.model = model
p.bc_ssss()
p.a = 1.
p.b = 0.5
p.r = 1.e8
p.alphadeg = 0.
p.stack = [0, 90, -45, +45]
p.plyt = 1e-3*0.125
p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9)
p.mu = 1.3e3
p.m = 11
p.n = 12
p.Nxx = -60.
p.Nyy = -5.
p.freq(sparse_solver=True, reduced_dof=False, silent=True,
atype=atype)
if atype == 3:
if '_w' in model:
assert np.allclose(p.eigvals[0], 19.9271684726)
else:
assert np.allclose(p.eigvals[0], 17.8587479369)
elif atype == 4:
if '_w' in model:
assert np.allclose(p.eigvals[0], 40.3728103572)
else:
assert np.allclose(p.eigvals[0], 39.3147553173)
def test_lb():
for model in ['plate_clt_donnell_bardell',
'plate_clt_donnell_bardell_w',
'cpanel_clt_donnell_bardell',
'kpanel_clt_donnell_bardell']:
print('Linear buckling for model {0}'.format(model))
# ssss
p = Panel()
p.bc_ssss()
p.m = 12
p.n = 13
p.stack = [0, 90, -45, +45]
p.plyt = 0.125e-3
p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9)
p.model = model
p.a = 1.
p.b = 0.5
p.r = 1.e8
p.alphadeg = 0.
p.Nxx = -1
p.lb(silent=True)
if '_w' in model:
assert np.allclose(p.eigvals[0], 88.4769618837)
else:
assert np.allclose(p.eigvals[0], 85.2911727144)
p.Nxx = 0
p.Nyy = -1
p.lb(silent=True)
if '_w' in model:
assert np.allclose(p.eigvals[0], 26.4588171556)
else:
assert np.allclose(p.eigvals[0], 25.1756170679)
# ssfs
p = Panel()
p.bc_ssfs()
p.m = 12
p.n = 13
p.stack = [0, 90, -45, +45]
p.plyt = 0.125e-3
p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9)
p.model = model
p.a = 1.
p.b = 0.5
p.r = 1.e8
p.alphadeg = 0.
p.Nxx = -1
p.lb(silent=True)
if '_w' in model:
assert np.allclose(p.eigvals[0], 17.1442703121)
else:
assert np.allclose(p.eigvals[0], 15.8423562314)
p.bc_sfss()
p.Nxx = 0
p.Nyy = -1
p.lb(silent=True)
if '_w' in model:
assert np.allclose(p.eigvals[0], 15.8099861083)
else:
assert np.allclose(p.eigvals[0], 13.9421987614)
