def get_Sbar_matrix(self, mid_ref, theta=0.):
"""theta must be in radians"""
# this is the inverse of Sbar
S2, unused_S3 = get_mat_props_S(mid_ref)
T = get_2d_plate_transform(theta)
#Tinv = np.linalg.inv(T)
Sbar = np.linalg.multi_dot([T.T, S2, T])
return Sbar
def get_Qbar_matrix(self, mid_ref, theta=0.):
"""theta must be in radians"""
S2, unused_S3 = get_mat_props_S(mid_ref)
T = get_2d_plate_transform(theta)
#Tinv = np.linalg.inv(T)
#Qbar = np.linalg.multi_dot([Tinv, Q, Tinv.T])
Sbar = np.linalg.multi_dot([T.T, S2, T])
Qbar = np.linalg.inv(Sbar)
return Qbar
def test_abd_1(self):
"""tests some ABD matrix functionality for a PCOMP"""
log = get_logger(level='warning')
model = BDF(log=log)
model.add_grid(1, [0., 0., 0.])
model.add_grid(2, [1., 0., 0.])
model.add_grid(3, [1., 1., 0.])
model.add_grid(4, [0., 1., 0.])
nids = [1, 2, 3, 4]
eid = 1
pid = 10
mid = 20
model.add_cquad4(eid, pid, nids, theta_mcid=0.0, zoffset=0.,
tflag=0, T1=None, T2=None, T3=None, T4=None, comment='')
thetas = [0., 45., 90.]
thicknesses = [0.1] * 3
mids = len(thicknesses) * [mid]
pcomp = model.add_pcomp(pid, mids, thicknesses, thetas=None,
souts=None, nsm=0., sb=0., ft=None, tref=0., ge=0.,
lam=None, z0=0., comment='')
E = 3.0e7
G = None
nu = 0.3
model.add_mat1(mid, E, G, nu)
#--------------------------
#e1_e2 = 40.
#g12_e2 = 0.5
#nu12 = 0.25
#e22 = 30e6
e1_e2 = 3.
g12_e2 = 0.5
nu12 = 0.25
e22 = 1.
e11 = e1_e2 * e22
g12 = g12_e2 * e22
mid8 = 8
mat8 = model.add_mat8(
mid8, e11, e22, nu12, g12=g12, g1z=1e8, g2z=1e8, rho=0.,
a1=0., a2=0., tref=0.,
Xt=0., Xc=None, Yt=0., Yc=None, S=0., ge=0.,
F12=0., strn=0., comment='')
S = get_mat_props_S(mat8)
pid8 = 8
pcomp8 = model.add_pcomp(pid8, [mid8], [1.], thetas=[0.],
souts=None, nsm=0., sb=0., ft=None, tref=0., ge=0.,
lam=None, z0=0., comment='')
model.pop_parse_errors()
model.cross_reference()
model.pop_xref_errors()
ABD = pcomp.get_ABD_matrices()
thetad = np.linspace(0., 90., num=91)
if IS_MATPLOTLIB:
plot_equivalent_lamina_vs_theta(
pcomp8, mat8, thetad, plot=True, show=False, close=True,
png_filename='lamina.png')
os.remove('lamina_stiffness.png')
os.remove('lamina_nu.png')