def test_panel_aero():
for model in ['plate_clt_donnell_bardell',
'plate_clt_donnell_bardell_w',
'cpanel_clt_donnell_bardell']:
for atype in [1, 2]:
print('Flutter Analysis Piston Theory, atype={0}, model={1}'.
format(atype, model))
p = Panel()
p.model = model
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
E2 = 8.7e9
p.laminaprop = (142.5e9, E2, 0.28, 5.1e9, 5.1e9, 5.1e9)
p.mu = 1.5e3
p.m = 8
p.n = 9
# pre-stress applied when atype == 1
p.Nxx = -60.
p.Nyy = -5.
# testing commong methodology based on betastar
if atype == 1:
betasstar = np.linspace(150, 350, 40)
elif atype == 2:
betasstar = np.linspace(670, 690, 40)
betas = betasstar/(p.a**3/E2/(len(p.stack)*p.plyt)**3)
p.beta = betas[0]
p.freq(atype=1, reduced_dof=False, sparse_solver=False,
silent=True)
out = np.zeros((len(betasstar), p.eigvals.shape[0]),
dtype=p.eigvals.dtype)
for i, beta in enumerate(betas):
p.beta = beta
p.freq(atype=2, reduced_dof=False, sparse_solver=False,
silent=True)
eigvals = p.eigvals*p.a**2/(np.pi**2*sum(p.plyts))*np.sqrt(p.mu/E2)
out[i, :] = eigvals
ind = np.where(np.any(out.imag != 0, axis=1))[0][0]
if atype == 1:
if not model.endswith('_w'):
assert np.isclose(betas[ind], 347.16346, atol=0.1, rtol=0)
else:
assert np.isclose(betas[ind], 174.27885, atol=0.1, rtol=0)
elif atype == 2:
if not model.endswith('_w'):
assert np.isclose(betas[ind], 728.625, atol=0.1, rtol=0)
else:
assert np.isclose(betas[ind], 728.625, atol=0.1, rtol=0)
def test_panel_aero():
for model in [
'plate_clt_donnell_bardell', 'plate_clt_donnell_bardell_w',
'cpanel_clt_donnell_bardell'
]:
for atype in [1, 2]:
print(
'Flutter Analysis Piston Theory, atype={0}, model={1}'.format(
atype, model))
p = Panel()
p.model = model
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
E2 = 8.7e9
p.laminaprop = (142.5e9, E2, 0.28, 5.1e9, 5.1e9, 5.1e9)
p.mu = 1.5e3
p.m = 8
p.n = 9
# pre-stress applied when atype == 1
p.Nxx = -60.
p.Nyy = -5.
# testing commong methodology based on betastar
if atype == 1:
betasstar = np.linspace(150, 350, 40)
elif atype == 2:
betasstar = np.linspace(670, 690, 40)
betas = betasstar / (p.a**3 / E2 / (len(p.stack) * p.plyt)**3)
p.beta = betas[0]
p.freq(atype=1,
reduced_dof=False,
sparse_solver=False,
silent=True)
out = np.zeros((len(betasstar), p.eigvals.shape[0]),
dtype=p.eigvals.dtype)
for i, beta in enumerate(betas):
p.beta = beta
p.freq(atype=2,
reduced_dof=False,
sparse_solver=False,
silent=True)
eigvals = p.eigvals * p.a**2 / (
np.pi**2 * sum(p.plyts)) * np.sqrt(p.mu / E2)
out[i, :] = eigvals
ind = np.where(np.any(out.imag != 0, axis=1))[0][0]
if atype == 1:
if not model.endswith('_w'):
assert np.isclose(betas[ind], 347.16346, atol=0.1, rtol=0)
else:
assert np.isclose(betas[ind], 174.27885, atol=0.1, rtol=0)
elif atype == 2:
if not model.endswith('_w'):
assert np.isclose(betas[ind], 728.625, atol=0.1, rtol=0)
else:
assert np.isclose(betas[ind], 728.625, atol=0.1, rtol=0)
