def get_homog_mat(ts, coors, mode, term=None, problem=None, **kwargs):
if problem.update_materials_flag == 2 and mode == 'qp':
out = hyperelastic_data['homog_mat']
return {k: nm.array(v) for k, v in six.iteritems(out)}
elif problem.update_materials_flag == 0 or not mode == 'qp':
return
output('get_homog_mat')
dim = problem.domain.mesh.dim
update_var = problem.conf.options.mesh_update_variables[0]
state_u = problem.equations.variables[update_var]
state_u.field.clear_mappings()
family_data = problem.family_data(state_u, term.region,
term.integral, term.integration)
mtx_f = family_data.mtx_f.reshape((coors.shape[0],)
+ family_data.mtx_f.shape[-2:])
out = get_homog_coefs_nonlinear(ts, coors, mode, mtx_f,
term=term, problem=problem,
iteration=problem.iiter, **kwargs)
out['E'] = 0.5 * (la.dot_sequences(mtx_f, mtx_f, 'ATB') - nm.eye(dim))
hyperelastic_data['time'] = ts.step
hyperelastic_data['homog_mat_shape'] = family_data.det_f.shape[:2]
hyperelastic_data['homog_mat'] = \
{k: nm.array(v) for k, v in six.iteritems(out)}
return out
def get_homog_mat(ts, coors, mode, term=None, problem=None, **kwargs):
hyperela = hyperelastic_data
ts = hyperela['ts']
output('get_homog_mat: mode=%s, update=%s'\
% (mode, hyperela['update_materials']))
if not mode == 'qp':
return
if not hyperela['update_materials']:
out = hyperela['homog_mat']
return {k: nm.array(v) for k, v in six.iteritems(out)}
dim = problem.domain.mesh.dim
nqp = coors.shape[0]
state_u = problem.equations.variables['u']
if len(state_u.field.mappings0) == 0:
state_u.field.get_mapping(term.region, term.integral, term.integration)
state_u.field.save_mappings()
state_u.field.clear_mappings()
state_u.set_data(
hyperela['state']['u'].ravel()) # + state_u.data[-1][state_u.indx]
mtx_f = problem.evaluate('ev_def_grad.i.Omega(u)',
mode='qp').reshape(-1, dim, dim)
# relative deformation gradient
if hasattr(problem, 'mtx_f_prev'):
rel_mtx_f = la.dot_sequences(mtx_f, nm.linalg.inv(problem.mtx_f_prev),
'AB')
else:
rel_mtx_f = mtx_f
problem.mtx_f_prev = mtx_f.copy()
macro_data = {
'mtx_e_rel': rel_mtx_f - nm.eye(dim), # relative macro strain
}
for ch in problem.conf.chs:
plab = 'p%d' % ch
state_p = problem.equations.variables[plab]
state_p.set_data(hyperela['state'][plab])
macro_data['p%d_0' % ch] = \
problem.evaluate('ev_volume_integrate.i.Omega(p%d)' % ch,
mode='qp').reshape(-1, 1, 1)
macro_data['gp%d_0' % ch] = \
problem.evaluate('ev_grad.i.Omega(p%d)' % ch,
mode='qp').reshape(-1, dim, 1)
state_p.set_data(hyperela['state']['d' + plab])
macro_data['dp%d_0' % ch] = \
problem.evaluate('ev_volume_integrate.i.Omega(p%d)' % ch,
mode='qp').reshape(-1, 1, 1)
macro_data['gdp%d_0' % ch] = \
problem.evaluate('ev_grad.i.Omega(p%d)' % ch,
mode='qp').reshape(-1, dim, 1)
nel = term.region.entities[-1].shape[0]
ccoors0, macro_data0 = homog_macro_map(coors, macro_data, nel)
macro_data0['macro_ccoor'] = ccoors0
out0 = get_homog_coefs_nonlinear(ts,
ccoors0,
mode,
macro_data0,
term=term,
problem=problem,
iteration=ts.step,
**kwargs)
out0['C1'] += nm.eye(2) * 1e-12 # ! auxiliary permeability
out0['C2'] += nm.eye(2) * 1e-12 # ! auxiliary permeability
out = homog_macro_remap(out0, nqp)
# Green strain
out['E'] = 0.5 * (la.dot_sequences(mtx_f, mtx_f, 'ATB') - nm.eye(dim))
for ch in problem.conf.chs:
out['B%d' % ch] = out['B%d' % ch].reshape((nqp, dim, dim))
out['Q'] = out['Q'].reshape((nqp, dim, dim))
hyperela['time'] = ts.step
hyperela['homog_mat'] = \
{k: nm.array(v) for k, v in six.iteritems(out)}
hyperela['update_materials'] = False
hyperela['macro_data'] = macro_data
return out