def translate_nodes_ABAQUS_c0(m0,
n0,
c0,
funcnum,
model_name,
part_name,
H_model,
semi_angle=0.,
scaling_factor=1.,
fem_meridian_bot2top=True,
ignore_bot_h=None,
ignore_top_h=None,
T=None):
r"""Translates the nodes in Abaqus based on a Fourier series
The Fourier Series can be a half-sine, half-cosine or a complete Fourier
Series as detailed in :func:`desicos.conecylDB.fit_data.calc_c0`.
Parameters
----------
m0 : int
Number of terms along the `x` coordinate.
n0 : int
Number of terms along the `\theta` coordinate.
c0 : numpy.ndarray
The coefficients that will give the imperfection pattern.
funcnum : int
The function type, as detailed in
:func:`desicos.conecylDB.fit_data.calc_c0`.
model_name : str
Must be a valid key in the dictionary ``mdb.models``, in the
interactive Python inside Abaqus.
part_name : str
Must be a valid key in the dictionary
``mdb.models[model_name].parts``, in the interactive Python inside
Abaqus.
H_model : float
Total height of the model where the imperfections will be applied to,
considering also eventual resin rings.
semi_angle : float, optional
The cone semi-vertex angle (a null value indicates that a cylinder is
beeing analyzed).
scaling_factor : float, optional
The scaling factor that will multiply ``c0`` when applying the
imperfections.
fem_meridian_bot2top : bool, optional
A boolean indicating if the finite element has the `x` axis starting
at the bottom or at the top.
ignore_bot_h : None or float, optional
Used to ignore nodes from the bottom resin ring.
ignore_top_h : None or float, optional
Used to ignore nodes from the top resin ring.
T : None or np.ndarray, optional
A transformation matrix (cf. :func:`.transf_matrix`) required when the
mesh is not in the :ref:`default coordinate system <figure_conecyl>`.
Returns
-------
nodal_translations : numpy.ndarray
A 2-D array containing the translations ``x, y, z`` for each column.
Notes
-----
Despite the nodal traslations are returned all the nodes belonging to this
model will be already translated.
"""
from abaqus import mdb, session
from desicos.conecylDB import fit_data
log('Calculating imperfection amplitudes for model {0} ...\n\t'.format(
model_name) + '(using a scaling factor of {0})'.format(scaling_factor))
c0 = c0 * scaling_factor
mod = mdb.models[model_name]
part = mod.parts[part_name]
part_nodes = np.array(part.nodes)
coords = np.array([n.coordinates for n in part_nodes])
if T is not None:
tmp = np.vstack((coords.T, np.ones((1, coords.shape[0]))))
coords = np.dot(T, tmp).T
del tmp
if ignore_bot_h is not None:
if ignore_bot_h <= 0:
ignore_bot_h = None
else:
log('Applying ignore_bot_h: ignoring nodes with z <= {0}'.format(
ignore_bot_h))
mask = coords[:, 2] > ignore_bot_h
coords = coords[mask]
part_nodes = part_nodes[mask]
if ignore_top_h is not None:
if ignore_top_h <= 0:
ignore_top_h = None
else:
log('Applying ignore_top_h: ignoring nodes with z >= {0}'.format(
H_model - ignore_top_h))
mask = coords[:, 2] < (H_model - ignore_top_h)
coords = coords[mask]
part_nodes = part_nodes[mask]
if ignore_bot_h is None:
ignore_bot_h = 0
if ignore_top_h is None:
ignore_top_h = 0
H_eff = H_model - (ignore_bot_h + ignore_top_h)
if fem_meridian_bot2top:
xs_norm = (coords[:, 2] - ignore_bot_h) / H_eff
else:
xs_norm = (H_eff - (coords[:, 2] - ignore_bot_h)) / H_eff
thetas = arctan2(coords[:, 1], coords[:, 0])
alpharad = deg2rad(semi_angle)
w0 = fit_data.fw0(m0, n0, c0, xs_norm, thetas, funcnum)
nodal_translations = np.zeros_like(coords)
nodal_translations[:, 0] = w0 * cos(alpharad) * cos(thetas)
nodal_translations[:, 1] = w0 * cos(alpharad) * sin(thetas)
nodal_translations[:, 2] = w0 * sin(alpharad)
log('Calculation of imperfection amplitudes finished!')
# applying translations
viewport = session.viewports[session.currentViewportName]
log('Applying new nodal positions in ABAQUS CAE to model {0} ...'.format(
model_name))
log(' (using a scaling factor of {0})'.format(scaling_factor))
new_coords = coords + nodal_translations
if T is not None:
Tinv = np.zeros_like(T)
Tinv[:3, :3] = T[:3, :3].T
Tinv[:, 3] = -T[:, 3]
tmp = np.vstack((new_coords.T, np.ones((1, new_coords.shape[0]))))
new_coords = np.dot(Tinv, tmp).T
del tmp
meshNodeArray = part.nodes.sequenceFromLabels(
[n.label for n in part_nodes])
new_coords = np.ascontiguousarray(new_coords)
part.editNode(nodes=meshNodeArray, coordinates=new_coords)
log('Application of new nodal positions finished!')
ra = mod.rootAssembly
viewport.setValues(displayedObject=ra)
ra.regenerate()
return nodal_translations
from desicos.conecylDB.fit_data import fw0
ntheta = 420
nz = 180
funcnum = 2
path = 'degenhardt_2010_z25_msi_theta_z_imp.txt'
theta = linspace(-pi, pi, ntheta)
z = linspace(0., 1., nz)
theta, z = meshgrid(theta, z, copy=False)
for m0, n0 in [[20, 30], [30, 45], [40, 60], [50, 75]]:
c, residues = calc_c0(path, m0=m0, n0=n0, sample_size=(10*2*m*n),
funcnum=funcnum)
w0 = fw0(m0, n0, z.ravel(), theta.ravel(), funcnum=funcnum)
plt.figure(figsize=(3.5, 2))
levels = np.linspace(w0.min(), w0.max(), 400)
plt.contourf(theta, z*H_measured, w0.reshape(theta.shape),
levels=levels)
ax = plt.gca()
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.xaxis.set_ticks([-pi, pi])
ax.xaxis.set_ticklabels([r'$-\pi$', r'$\pi$'])
def translate_nodes_ABAQUS_c0(m0, n0, c0, funcnum,
model_name,
part_name,
H_model,
semi_angle=0.,
scaling_factor=1.,
fem_meridian_bot2top=True,
ignore_bot_h=None,
ignore_top_h=None,
T=None):
r"""Translates the nodes in Abaqus based on a Fourier series
The Fourier Series can be a half-sine, half-cosine or a complete Fourier
Series as detailed in :func:`desicos.conecylDB.fit_data.calc_c0`.
Parameters
----------
m0 : int
Number of terms along the `x` coordinate.
n0 : int
Number of terms along the `\theta` coordinate.
c0 : numpy.ndarray
The coefficients that will give the imperfection pattern.
funcnum : int
The function type, as detailed in
:func:`desicos.conecylDB.fit_data.calc_c0`.
model_name : str
Must be a valid key in the dictionary ``mdb.models``, in the
interactive Python inside Abaqus.
part_name : str
Must be a valid key in the dictionary
``mdb.models[model_name].parts``, in the interactive Python inside
Abaqus.
H_model : float
Total height of the model where the imperfections will be applied to,
considering also eventual resin rings.
semi_angle : float, optional
The cone semi-vertex angle (a null value indicates that a cylinder is
beeing analyzed).
scaling_factor : float, optional
The scaling factor that will multiply ``c0`` when applying the
imperfections.
fem_meridian_bot2top : bool, optional
A boolean indicating if the finite element has the `x` axis starting
at the bottom or at the top.
ignore_bot_h : None or float, optional
Used to ignore nodes from the bottom resin ring.
ignore_top_h : None or float, optional
Used to ignore nodes from the top resin ring.
T : None or np.ndarray, optional
A transformation matrix (cf. :func:`.transf_matrix`) required when the
mesh is not in the :ref:`default coordinate system <figure_conecyl>`.
Returns
-------
nodal_translations : numpy.ndarray
A 2-D array containing the translations ``x, y, z`` for each column.
Notes
-----
Despite the nodal traslations are returned all the nodes belonging to this
model will be already translated.
"""
from abaqus import mdb, session
from desicos.conecylDB import fit_data
log('Calculating imperfection amplitudes for model {0} ...\n\t'.
format(model_name) +
'(using a scaling factor of {0})'.format(scaling_factor))
c0 = c0*scaling_factor
mod = mdb.models[model_name]
part = mod.parts[part_name]
part_nodes = np.array(part.nodes)
coords = np.array([n.coordinates for n in part_nodes])
if T is not None:
tmp = np.vstack((coords.T, np.ones((1, coords.shape[0]))))
coords = np.dot(T, tmp).T
del tmp
if ignore_bot_h is not None:
if ignore_bot_h <= 0:
ignore_bot_h = None
else:
log('Applying ignore_bot_h: ignoring nodes with z <= {0}'.format(
ignore_bot_h))
mask = coords[:, 2] > ignore_bot_h
coords = coords[mask]
part_nodes = part_nodes[mask]
if ignore_top_h is not None:
if ignore_top_h <= 0:
ignore_top_h = None
else:
log('Applying ignore_top_h: ignoring nodes with z >= {0}'.format(
H_model - ignore_top_h))
mask = coords[:, 2] < (H_model - ignore_top_h)
coords = coords[mask]
part_nodes = part_nodes[mask]
if ignore_bot_h is None:
ignore_bot_h = 0
if ignore_top_h is None:
ignore_top_h = 0
H_eff = H_model - (ignore_bot_h + ignore_top_h)
if fem_meridian_bot2top:
xs_norm = (coords[:, 2]-ignore_bot_h)/H_eff
else:
xs_norm = (H_eff-(coords[:, 2]-ignore_bot_h))/H_eff
thetas = arctan2(coords[:, 1], coords[:, 0])
alpharad = deg2rad(semi_angle)
w0 = fit_data.fw0(m0, n0, c0, xs_norm, thetas, funcnum)
nodal_translations = np.zeros_like(coords)
nodal_translations[:, 0] = w0*cos(alpharad)*cos(thetas)
nodal_translations[:, 1] = w0*cos(alpharad)*sin(thetas)
nodal_translations[:, 2] = w0*sin(alpharad)
log('Calculation of imperfection amplitudes finished!')
# applying translations
viewport = session.viewports[session.currentViewportName]
log('Applying new nodal positions in ABAQUS CAE to model {0} ...'.
format(model_name))
log(' (using a scaling factor of {0})'.format(scaling_factor))
new_coords = coords + nodal_translations
if T is not None:
Tinv = np.zeros_like(T)
Tinv[:3, :3] = T[:3, :3].T
Tinv[:, 3] = -T[:, 3]
tmp = np.vstack((new_coords.T, np.ones((1, new_coords.shape[0]))))
new_coords = np.dot(Tinv, tmp).T
del tmp
meshNodeArray = part.nodes.sequenceFromLabels(
[n.label for n in part_nodes])
new_coords = np.ascontiguousarray(new_coords)
part.editNode(nodes=meshNodeArray, coordinates=new_coords)
log('Application of new nodal positions finished!')
ra = mod.rootAssembly
viewport.setValues(displayedObject=ra)
ra.regenerate()
return nodal_translations
nz = 180
funcnum = 2
path = 'degenhardt_2010_z25_msi_theta_z_imp.txt'
theta = linspace(-pi, pi, ntheta)
z = linspace(0., 1., nz)
theta, z = meshgrid(theta, z, copy=False)
for m0, n0 in [[20, 30], [30, 45], [40, 60], [50, 75]]:
c, residues = calc_c0(path,
m0=m0,
n0=n0,
sample_size=(10 * 2 * m * n),
funcnum=funcnum)
w0 = fw0(m0, n0, z.ravel(), theta.ravel(), funcnum=funcnum)
plt.figure(figsize=(3.5, 2))
levels = np.linspace(w0.min(), w0.max(), 400)
plt.contourf(theta, z * H_measured, w0.reshape(theta.shape), levels=levels)
ax = plt.gca()
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.xaxis.set_ticks([-pi, pi])
ax.xaxis.set_ticklabels([r'$-\pi$', r'$\pi$'])
ax.set_xlabel('Circumferential Position, $rad$')
