def _get_load_task(self):
self.fold_task.x_1
cp = self.factory_task
n_l_h = cp.N_h[0, (0, -1)].flatten()
n_r_h = cp.N_h[-1, (0, -1)].flatten()
dof_constraints = fix(n_l_h, [0, 1, 2]) + fix(n_r_h, [0, 1, 2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
use_f_du=True,
acc=1e-4, MAX_ITER=1000,
debug_level=0)
F_ext_list = [(n, 2, 100.0) for n in cp.N_h[1, :]]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=1)
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
fu_tot_poteng.forming_task = st
return st
def _get_load_task(self):
self.fold_task.x_1
cp = self.factory_task
n_l_h = cp.N_h[0, (0, -1)].flatten()
n_r_h = cp.N_h[-1, (0, -1)].flatten()
dof_constraints = fix(n_l_h, [0, 1, 2]) + fix(n_r_h, [0, 1, 2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints
},
use_f_du=True,
acc=1e-4,
MAX_ITER=1000,
debug_level=0)
F_ext_list = [(n, 2, 100.0) for n in cp.N_h[1, :]]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config,
n_steps=1)
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
fu_tot_poteng.forming_task = st
return st
def _get_turn_task2(self):
self.fold_task.x_1
u_z = 0.1
fixed_nodes_xzy = fix([7, 19], (0, 1, 2))
lift_nodes_z = fix([3, 15], (2), lambda t: t * u_z)
dof_constraints = fixed_nodes_xzy + lift_nodes_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-5, MAX_ITER=1000,
debug_level=0)
load_nodes = []
FN = lambda F: lambda t: t * F
F_ext_list = [(n, 2, FN(-10)) for n in load_nodes]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([1000]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=1)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.u[(3, 15), 2] = u_z
return st
def _get_load_task(self):
self.turn_task.x_1
fixed_nodes_yz = fix([0, 2, 20, 22], (1, 2)) # + \
fixed_nodes_x = fix([0, 2, 20, 22], (0)) # + \
# fix([1, 21], [0, 2])
link_bnd = link([48, 49, 50, 56, 57, 58, 64, 65, 66, 72, 73, 74],
[0, 1, 2], 1.0,
[51, 52, 53, 59, 60, 61, 67, 68, 69, 75, 76, 77],
[0, 1, 2], -1.0)
dof_constraints = fixed_nodes_x + fixed_nodes_yz + link_bnd
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-5, MAX_ITER=1000,
debug_level=0)
load_nodes = [10, 11, 12]
FN = lambda F: lambda t: t * F
F_ext_list = [(n, 2, FN(-10)) for n in load_nodes]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
F_ext_list=F_ext_list) # (2 * n, 2, -1)])
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.turn_task,
config=sim_config, n_steps=1)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.turn_task.x_1
cp.u[:, :] = 0.0
return st
def _get_load_task(self):
self.fold_task.x_1
dof_constraints = fix(
[0, 2, 6], [2]) + fix([0, 2], [1]) + fix([6], [0])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
use_f_du=True,
acc=1e-8, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
F_ext_list = [(n, 2, FN(-1)) for n in [1, 3]]
print 'F_ext_list', F_ext_list
fu_tot_poteng = FuPotEngTotal(kappa=10, fu_factor=1,
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=1)
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
#cp.u[(4, 5), 2] = -0.001
#cp.u[(1, 3), 2] = -0.001
fu_tot_poteng.forming_task = st
return st
def _get_load_task(self):
self.fold_task.x_1
cp = self.factory_task
n_l_h = cp.N_h[0, (0, -1)].flatten()
n_r_h = cp.N_h[-1, (0, -1)].flatten()
dof_constraints = fix(
[0, 2, 4], [0, 1, 2]) + fix([20, 22, 24], [0, 1, 2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-6, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
F_max = 20
F_ext_list = [(cp.N_h[2, :], 2, FN(F_max))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=10)
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
cp.u[[10, 11, 12, 13, 14], 2] = 0.001
fu_tot_poteng.forming_task = st
return st
def _get_load_task(self):
self.fold_task.x_1
dof_constraints = fix(
[0, 2, 6], [2]) + fix([0, 2], [1]) + fix([6], [0])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
use_f_du=True,
acc=1e-8, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
F_ext_list = [(n, 2, FN(-1)) for n in [1, 3]]
print('F_ext_list', F_ext_list)
fu_tot_poteng = FuPotEngTotal(kappa=10, fu_factor=1,
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=1)
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
#cp.u[(4, 5), 2] = -0.001
#cp.u[(1, 3), 2] = -0.001
fu_tot_poteng.forming_task = st
return st
def _get_turn_task2(self):
self.fold_task.x_1
u_z = 0.1
fixed_nodes_xzy = fix([7, 19], (0, 1, 2))
lift_nodes_z = fix([3, 15], (2), lambda t: t * u_z)
dof_constraints = fixed_nodes_xzy + lift_nodes_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints
},
acc=1e-5,
MAX_ITER=1000,
debug_level=0)
load_nodes = []
FN = lambda F: lambda t: t * F
F_ext_list = [(n, 2, FN(-10)) for n in load_nodes]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([1000]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config,
n_steps=1)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.u[(3, 15), 2] = u_z
return st
def _get_fold_deform_task(self):
ft = self.factory_task
self.init_displ_task.x_1
fixed_z = fix(self.fixed_z, (2))
fixed_y = fix(self.fixed_y, (1))
fixed_x = fix(self.fixed_x, (0))
link_z = link(self.link_z[0], [2], 1, self.link_z[1], [2], -1)
dof_constraints = fixed_x + fixed_z + fixed_y + \
link_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
def FN(psi):
return lambda t: psi * t
psi_constr = [([(i, 1.0)], FN(self.psi_max)) for i in self.psi_lines]
gu_constant_length = GuConstantLength()
gu_psi_constraints = \
GuPsiConstraints(forming_task=ft,
psi_constraints=psi_constr)
sim_config = SimulationConfig(
goal_function_type='gravity potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5,
MAX_ITER=self.MAXITER,
debug_level=0)
fu_tot_poteng = FuPotEngTotal(kappa=np.array([self.kappa]),
F_ext_list=[],
rho=self.rho,
exclude_lines=self.psi_lines)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.init_displ_task,
config=sim_config,
n_steps=self.n_steps)
#
# st = SimulationTask(previous_task=ft,
# config=sim_config, n_steps=self.n_steps)
fu_tot_poteng.forming_task = st
# gu_psi_constraints.forming_task = st
#
# cp = st.formed_object
# cp.u = it.u_1
return st
def _get_load_task(self):
self.turn_task.x_1
fixed_nodes_yz = fix([0, 2, 20, 22], (1, 2)) # + \
fixed_nodes_x = fix([0, 2, 20, 22], (0)) # + \
# fix([1, 21], [0, 2])
link_bnd = []
if self.stiffening_boundary:
link_bnd = link([48, 49, 50, 56, 57, 58, 64, 65, 66, 72, 73, 74],
[0, 1, 2], 1.0,
[51, 52, 53, 59, 60, 61, 67, 68, 69, 75, 76, 77],
[0, 1, 2], -1.0)
dof_constraints = fixed_nodes_x + fixed_nodes_yz + link_bnd
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints
},
acc=1e-5,
MAX_ITER=1000,
debug_level=0)
def FN(F):
return lambda t: t * F
H = 0
P = 3.5 * self.load_factor
F_ext_list = [(33, 2, FN(-P)), (34, 2, FN(-P)), (11, 2, FN(-P)),
(39, 2, FN(-P)), (40, 2, FN(-P)), (4, 0, FN(0.1609 * H)),
(4, 2, FN(-0.2385 * H)), (10, 2, FN(-0.3975 * H)),
(16, 0, FN(-0.1609 * H)), (16, 2, FN(-0.2385 * H)),
(6, 0, FN(0.1609 * H)), (6, 2, FN(-0.2385 * H)),
(12, 2, FN(-0.3975 * H)), (18, 0, FN(-0.1609 * H)),
(18, 2, FN(-0.2385 * H))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([5.28]),
F_ext_list=F_ext_list)
# load_nodes = [10, 11, 12]
# FN = lambda F: lambda t: t * F
# F_ext_list = [(n, 2, FN(-10)) for n in load_nodes]
# fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
# F_ext_list=F_ext_list) # (2 * n, 2, -1)])
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.turn_task,
config=sim_config,
n_steps=self.n_load_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.turn_task.x_1
cp.u[:, :] = 0.0
return st
def _get_load_task(self):
self.turn_task.x_1
fixed_nodes_yz = fix([0, 2, 20, 22], (1, 2)) # + \
fixed_nodes_x = fix([0, 2, 20, 22], (0)) # + \
fixed_nodes_middle = fix([1, 21], [0, 1, 2])
# 'Gesamter Randbereich'
# link_bnd = link([48, 49, 50, 56, 57, 58, 64, 65, 66, 72, 73, 74, 71, 55],
# [0, 1, 2], 1.0,
# [51, 52, 53, 59, 60, 61, 67,
# 68, 69, 75, 76, 77, 63, 47],
# [0, 1, 2], -1.0)
# 'Ohne mittlere Randknoten'
# link_bnd = link([48, 49, 50, 56, 57, 58, 64, 65, 66, 72, 73, 74],
# [0, 1, 2], 1.0,
# [51, 52, 53, 59, 60, 61, 67,
# 68, 69, 75, 76, 77],
# [0, 1, 2], -1.0)
# 'Ohne aeussere Randknoten'
# link_bnd = link([48, 49, 56, 57, 64, 65, 72, 73, 71, 55],
# [0, 1, 2], 1.0,
# [51, 52, 59, 60, 67,
# 68, 75, 76, 63, 47],
# [0, 1, 2], -1.0)
# + link_bnd + # fixed_nodes_middle
dof_constraints = fixed_nodes_x + fixed_nodes_yz
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-8, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
H = 0
P = 3.5
F_ext_list = [(33, 2, FN(-P)), (34, 2, FN(-P)), (11, 2, FN(-P)), (39, 2, FN(-P)), (40, 2, FN(-P)), (4, 0, FN(0.1609 * H)), (4, 2, FN(-0.2385 * H)), (10, 2, FN(-0.3975 * H)), (16, 0, FN(-0.1609 * H)), (16, 2, FN(-0.2385 * H)),
(6, 0, FN(0.1609 * H)), (6, 2, FN(-0.2385 * H)), (12, 2, FN(-0.3975 * H)), (18, 0, FN(-0.1609 * H)), (18, 2, FN(-0.2385 * H))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([5.28]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.turn_task,
config=sim_config, n_steps=1)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.turn_task.x_1
cp.u[:, :] = 0.0
return st
def _get_load_task(self):
self.fold_task.x_1
fat = self.factory_task
fixed_corner_n = fat.N_grid[(0, 0, -1, -1), (1, -2, 1, -2)].flatten()
fixed_n = fat.N_grid[(0, 0), (1, -2)].flatten()
slide_z = fix(fat.N_grid[-1, -2], [2], lambda t: -0.8 * self.L_x * t)
slide_x = fix(fat.N_grid[-1, -2], [0], lambda t: 0.1 * self.L_y * t)
loaded_n = fat.N_grid[self.n_x / 2, self.n_y / 2]
fixed_nodes_xyz = fix(fixed_n, (0, 2)) + slide_z
#fixed_nodes_xyz = fix(fixed_corner_n, (0, 1, 2))
dof_constraints = fixed_nodes_xyz
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
diag_psi_mask = np.ones_like(fat.L_d_grid, dtype=np.bool_)
diag_psi_mask[1:-1, 1:-1] = False
diag_lines = fat.L_d_grid[diag_psi_mask].flatten()
diag_psi_constraints = [([(i, 1.0)], 0) for i in diag_lines]
gu_psi_constraints = \
GuPsiConstraints(forming_task=fat,
psi_constraints=diag_psi_constraints)
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5,
MAX_ITER=1000,
debug_level=0)
def FN(F):
return lambda t: t * F
P = 0.0 * 30.5 * self.load_factor
F_ext_list = [(loaded_n, 2, FN(-P))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([1.0]),
F_ext_list=F_ext_list,
thickness=1,
exclude_lines=diag_lines)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config,
n_steps=self.n_load_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
return st
def _get_load_task(self):
self.fold_task.x_1
fat = self.factory_task
fixed_corner_n = fat.N_grid[(0, 0, -1, -1), (1, -2, 1, -2)].flatten()
fixed_n = fat.N_grid[(0, 0), (1, -2)].flatten()
slide_z = fix(fat.N_grid[-1, -2], [2], lambda t: -0.8 * self.L_x * t)
slide_x = fix(fat.N_grid[-1, -2], [0], lambda t: 0.1 * self.L_y * t)
loaded_n = fat.N_grid[self.n_x / 2, self.n_y / 2]
fixed_nodes_xyz = fix(fixed_n, (0, 2)) + slide_z
#fixed_nodes_xyz = fix(fixed_corner_n, (0, 1, 2))
dof_constraints = fixed_nodes_xyz
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
diag_psi_mask = np.ones_like(fat.L_d_grid, dtype=np.bool_)
diag_psi_mask[1:-1, 1:-1] = False
diag_lines = fat.L_d_grid[diag_psi_mask].flatten()
diag_psi_constraints = [([(i, 1.0)], 0)
for i in diag_lines]
gu_psi_constraints = \
GuPsiConstraints(forming_task=fat,
psi_constraints=diag_psi_constraints)
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5, MAX_ITER=1000,
debug_level=0
)
def FN(F): return lambda t: t * F
P = 0.0 * 30.5 * self.load_factor
F_ext_list = [(loaded_n, 2, FN(-P))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([1.0]),
F_ext_list=F_ext_list,
thickness=1,
exclude_lines=diag_lines
)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=self.n_load_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
return st
def _get_fold_deform_task(self):
ft = self.factory_task
self.init_displ_task.x_1
fixed_z = fix(self.fixed_z, (2))
fixed_y = fix(self.fixed_y, (1))
fixed_x = fix(self.fixed_x, (0))
link_z = link(self.link_z[0], [2], 1, self.link_z[1], [2], -1)
dof_constraints = fixed_x + fixed_z + fixed_y + \
link_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
def FN(psi): return lambda t: psi * t
psi_constr = [([(i, 1.0)], FN(self.psi_max))
for i in self.psi_lines]
gu_constant_length = GuConstantLength()
gu_psi_constraints = \
GuPsiConstraints(forming_task=ft,
psi_constraints=psi_constr)
sim_config = SimulationConfig(goal_function_type='gravity potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5, MAX_ITER=self.MAXITER,
debug_level=0)
fu_tot_poteng = FuPotEngTotal(kappa=np.array([self.kappa]),
F_ext_list=[],
rho=self.rho,
exclude_lines=self.psi_lines)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.init_displ_task,
config=sim_config, n_steps=self.n_steps)
#
# st = SimulationTask(previous_task=ft,
# config=sim_config, n_steps=self.n_steps)
fu_tot_poteng.forming_task = st
# gu_psi_constraints.forming_task = st
#
# cp = st.formed_object
# cp.u = it.u_1
return st
def _get_load_task(self):
self.turn_task.x_1
fixed_nodes_yz = fix([0, 2, 20, 22], (1, 2)) # + \
fixed_nodes_x = fix([0, 2, 20, 22], (0)) # + \
# fix([1, 21], [0, 2])
link_bnd = []
if self.stiffening_boundary:
link_bnd = link([48, 49, 50, 56, 57, 58, 64, 65, 66, 72, 73, 74],
[0, 1, 2], 1.0,
[51, 52, 53, 59, 60, 61, 67, 68, 69, 75, 76, 77],
[0, 1, 2], -1.0)
dof_constraints = fixed_nodes_x + fixed_nodes_yz + link_bnd
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-5, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
H = 0
P = 3.5 * self.load_factor
F_ext_list = [(33, 2, FN(-P)), (34, 2, FN(-P)), (11, 2, FN(-P)), (39, 2, FN(-P)), (40, 2, FN(-P)), (4, 0, FN(0.1609 * H)), (4, 2, FN(-0.2385 * H)), (10, 2, FN(-0.3975 * H)), (16, 0, FN(-0.1609 * H)), (16, 2, FN(-0.2385 * H)),
(6, 0, FN(0.1609 * H)), (6, 2, FN(-0.2385 * H)), (12, 2, FN(-0.3975 * H)), (18, 0, FN(-0.1609 * H)), (18, 2, FN(-0.2385 * H))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([5.28]),
F_ext_list=F_ext_list)
# load_nodes = [10, 11, 12]
# FN = lambda F: lambda t: t * F
# F_ext_list = [(n, 2, FN(-10)) for n in load_nodes]
# fu_tot_poteng = FuPotEngTotal(kappa=np.array([10]),
# F_ext_list=F_ext_list) # (2 * n, 2, -1)])
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.turn_task,
config=sim_config, n_steps=self.n_load_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.turn_task.x_1
cp.u[:, :] = 0.0
return st
def _get_load_task(self):
self.fold_task.x_1
cp = self.factory_task
n_l_h = cp.N_h[0, (0, -1)].flatten()
n_r_h = cp.N_h[-1, (0, -1)].flatten()
n_fixed_y = cp.N_h[(0, -1), 1].flatten()
n_scheitel = cp.N_h[2, :]
n_aussen = cp.N_v
dof_constraints = fix(
n_l_h, [0, 2]) + fix(n_r_h, [0, 2]) + fix(n_fixed_y, [0, 1])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints},
acc=1e-10, MAX_ITER=1000,
debug_level=0)
FN = lambda F: lambda t: t * F
F_max = 2
F_min = 1
F_ext_list = [(7, 2, FN(F_max)), (6, 2, FN(F_min)), (8, 2, FN(F_min))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([4.97]),
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config, n_steps=10)
cp = st.formed_object
cp.L = np.vstack([cp.L, np.array([[6, 7], [7, 8]], dtype='int_')])
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
cp.u[[6, 7, 8], 2] = 0.0001
fu_tot_poteng.forming_task = st
return st
def _get_load_self_weight(self):
self.fold_kinem_cntl.x_1
f = self.factory_task
exclude_lines = np.arange(9, 17)
cp = f.formed_object
N_h = f.N_h
N_i = f.N_i
N_v = f.N_v
fixed_nodes = np.hstack([N_h[[-1, -1], [0, -1]]])
fixed_nodes = [25, 27]
fixed_nodes_xyz = fix(
list(N_h[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()), (2)
#fixed_nodes, (0, 2)
)
slided_nodes = np.hstack([N_h[[0, -1], [0, 0]]]) # , [22, 25]])
#slide_y = fix(slided_nodes, [1], lambda t: 1.8 * self.L_y * t)
slide_x = fix([22, 24], [2],
lambda t: 0.95 * (self.L_x) * t)
slide_z = fix(N_h[[1, -2], [1, 1]], [2], lambda t: -0.3 * t)
dof_constraints = fixed_nodes_xyz + slide_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
fix_psi_constr = [([(i, 1.0)], 0.0)
for i in exclude_lines]
gu_psi_constraints = \
GuPsiConstraints(forming_task=self.fold_kinem_cntl,
psi_constraints=fix_psi_constr)
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-7, MAX_ITER=1000,
debug_level=0
)
loaded_n = N_h[:, 1].flatten()
def FN(F): return lambda t: t * F
P = 0.0 * 30.5
F_ext_list = [] # (loaded_n, 2, FN(-P))]
thickness = 0.01
E_mod = 21.0e+4
I = 1.0 * thickness**3 / 12.0
kappa = E_mod * I
print('kappa', kappa)
sig_tu = 3000.0
m_u = sig_tu * 1.0 * thickness**2 / 6.0
print('m_u', m_u)
fu_tot_poteng = FuPotEngTotal(
exclude_lines=exclude_lines,
kappa=np.array([kappa]),
thickness=thickness,
rho=23.6,
m_u=m_u,
F_ext_list=F_ext_list
)
sim_config._fu = fu_tot_poteng
st = SimulationTask(
previous_task=self.fold_kinem_cntl,
config=sim_config, n_steps=self.n_load_steps
)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.fold_kinem_cntl.x_1
cp.u[:, :] = 0.0
return st
def _get_fold_self_weight_cntl(self):
self.init_displ_task.x_1
f = self.factory_task
cp = f.formed_object
N_h = f.N_h
N_i = f.N_i
N_v = f.N_v
fixed_nodes_x = fix(
N_i[1, (0, 1)], (0))
fixed_nodes_y = fix(
[N_h[1, 1].flatten()], (1))
fixed_nodes_z = fix(
list(N_v[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()) +
list(N_i[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()), (2)
)
cntl_z = fix(N_h[(1, 2), 1], 2, lambda t: 0.1 * t)
link_nodes_y = link(
list(N_v[[0, -1], [0, -1]].flatten()), 1, 1.0,
list(N_i[[0, -1], [0, -1]].flatten()), 1, -1.0,
)
link_nodes_z = link(
list(N_h[[1, 1, 1], [0, 1, -1]].flatten()), 2, 1.0,
list(N_h[[2, 2, 2], [0, 1, -1]].flatten()), 2, -1.0,
)
# link_nodes_z = link(
# N_h[1, 1], 2, 1.0,
# N_h[2, 1], 2, -1.0,
# )
dof_constraints = fixed_nodes_x + fixed_nodes_z + fixed_nodes_y + \
link_nodes_z + \
link_nodes_y
# link_nodes_yz + link_nodes_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
},
acc=1e-5, MAX_ITER=1000,
debug_level=0)
def FN(F): return lambda t: t * F
H = 0
P = 0.1
F_ext_list = [(N_i[1, 1], 2, FN(-P)), (N_i[1, -1], 2, FN(-P)),
(N_h[(0, -1), 0], 2, FN(-P)),
(N_h[(0, -1), -1], 2, FN(-P))
]
fu_tot_poteng = FuPotEngTotal(kappa=0.0, thickness=0.01,
rho=23.6,
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.init_displ_task,
config=sim_config, n_steps=self.n_fold_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
N_down = np.hstack([N_h[::3, :].flatten(),
N_i[1::3, :].flatten()
])
print('N_down', N_down)
N_up = np.hstack([N_i[::3, :].flatten(),
N_i[2::3, :].flatten(),
N_v[:, :].flatten()])
print('N_up', N_up)
cp.u[N_down, 2] -= self.d_down
cp.u[N_up, 2] += self.d_up
cp.u[:, 2] += self.d_down
return st
def _get_load_self_weight(self):
self.fold_kinem_cntl.x_1
f = self.factory_task
exclude_lines = np.arange(9, 17)
cp = f.formed_object
N_h = f.N_h
N_i = f.N_i
N_v = f.N_v
fixed_nodes = np.hstack([N_h[[-1, -1], [0, -1]]])
fixed_nodes = [25, 27]
fixed_nodes_xyz = fix(
list(N_h[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()), (2)
#fixed_nodes, (0, 2)
)
slided_nodes = np.hstack([N_h[[0, -1], [0, 0]]]) # , [22, 25]])
#slide_y = fix(slided_nodes, [1], lambda t: 1.8 * self.L_y * t)
slide_x = fix([22, 24], [2],
lambda t: 0.95 * (self.L_x) * t)
slide_z = fix(N_h[[1, -2], [1, 1]], [2], lambda t: -0.3 * t)
dof_constraints = fixed_nodes_xyz + slide_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
fix_psi_constr = [([(i, 1.0)], 0.0)
for i in exclude_lines]
gu_psi_constraints = \
GuPsiConstraints(forming_task=self.fold_kinem_cntl,
psi_constraints=fix_psi_constr)
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-7, MAX_ITER=1000,
debug_level=0
)
loaded_n = N_h[:, 1].flatten()
def FN(F): return lambda t: t * F
P = 0.0 * 30.5
F_ext_list = [] # (loaded_n, 2, FN(-P))]
thickness = 0.01
E_mod = 21.0e+4
I = 1.0 * thickness**3 / 12.0
kappa = E_mod * I
print 'kappa', kappa
sig_tu = 3000.0
m_u = sig_tu * 1.0 * thickness**2 / 6.0
print 'm_u', m_u
fu_tot_poteng = FuPotEngTotal(
exclude_lines=exclude_lines,
kappa=np.array([kappa]),
thickness=thickness,
rho=23.6,
m_u=m_u,
F_ext_list=F_ext_list
)
sim_config._fu = fu_tot_poteng
st = SimulationTask(
previous_task=self.fold_kinem_cntl,
config=sim_config, n_steps=self.n_load_steps
)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.fold_kinem_cntl.x_1
cp.u[:, :] = 0.0
return st
F_nodes = np.linspace(0, -10, n)
FN = lambda F: lambda t: t * F
F_ext_list = [(i + 1, 2, FN(F_n)) for i, F_n in enumerate(F_nodes)]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([5000.0]), fu_factor=1,
F_ext_list=F_ext_list) # (2 * n, 2, -1)])
sim_config._fu = fu_tot_poteng
sim_task = SimulationTask(previous_task=cp_factory_task,
config=sim_config,
n_steps=10)
cp = sim_task.formed_object
cp.x_0 = np.copy(sim_task.previous_task.formed_object.X)
cp.u[:, :] = 0.0
fu_tot_poteng.forming_task = sim_task
cp.u[1:n + 1, 2] = np.linspace(0, -0.001, n)
cp.u[n + 1:(2 * n) + 1, 2] = np.linspace(0, -0.0005, n)
print 'kinematic simulation: u', sim_task.u_1
cp = sim_task.formed_object
iL_phi = cp.iL_psi - cp.iL_psi_0
print 'phi', iL_phi
iL_length = np.linalg.norm(cp.iL_vectors, axis=1)
iL_m = sim_config._fu.kappa * iL_phi * iL_length
print 'moments', iL_m
ftv = FTV()
ftv.add(sim_task.sim_history.viz3d['displ'])
F_nodes = np.linspace(0, -10, n)
FN = lambda F: lambda t: t * F
F_ext_list = [(i + 1, 2, FN(F_n)) for i, F_n in enumerate(F_nodes)]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([5000.0]), fu_factor=1,
F_ext_list=F_ext_list) # (2 * n, 2, -1)])
sim_config._fu = fu_tot_poteng
sim_task = SimulationTask(previous_task=cp_factory_task,
config=sim_config,
n_steps=10)
cp = sim_task.formed_object
cp.x_0 = np.copy(sim_task.previous_task.formed_object.X)
cp.u[:, :] = 0.0
fu_tot_poteng.forming_task = sim_task
cp.u[1:n + 1, 2] = np.linspace(0, -0.001, n)
cp.u[n + 1:(2 * n) + 1, 2] = np.linspace(0, -0.0005, n)
print('kinematic simulation: u', sim_task.u_1)
cp = sim_task.formed_object
iL_phi = cp.iL_psi - cp.iL_psi_0
print('phi', iL_phi)
iL_length = np.linalg.norm(cp.iL_vectors, axis=1)
iL_m = sim_config._fu.kappa * iL_phi * iL_length
print('moments', iL_m)
ftv = FTV()
ftv.add(sim_task.sim_history.viz3d['displ'])
def _get_fold_self_weight_cntl(self):
self.init_displ_task.x_1
f = self.factory_task
cp = f.formed_object
N_h = f.N_h
N_i = f.N_i
N_v = f.N_v
fixed_nodes_x = fix(
N_i[1, (0, 1)], (0))
fixed_nodes_y = fix(
[N_h[1, 1].flatten()], (1))
fixed_nodes_z = fix(
list(N_v[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()) +
list(N_i[[0, 0, -1, -1], [0, -1, 0, -1]].flatten()), (2)
)
cntl_z = fix(N_h[(1, 2), 1], 2, lambda t: 0.1 * t)
link_nodes_y = link(
list(N_v[[0, -1], [0, -1]].flatten()), 1, 1.0,
list(N_i[[0, -1], [0, -1]].flatten()), 1, -1.0,
)
link_nodes_z = link(
list(N_h[[1, 1, 1], [0, 1, -1]].flatten()), 2, 1.0,
list(N_h[[2, 2, 2], [0, 1, -1]].flatten()), 2, -1.0,
)
# link_nodes_z = link(
# N_h[1, 1], 2, 1.0,
# N_h[2, 1], 2, -1.0,
# )
dof_constraints = fixed_nodes_x + fixed_nodes_z + fixed_nodes_y + \
link_nodes_z + \
link_nodes_y
# link_nodes_yz + link_nodes_z
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'dofs': gu_dof_constraints,
},
acc=1e-5, MAX_ITER=1000,
debug_level=0)
def FN(F): return lambda t: t * F
H = 0
P = 0.1
F_ext_list = [(N_i[1, 1], 2, FN(-P)), (N_i[1, -1], 2, FN(-P)),
(N_h[(0, -1), 0], 2, FN(-P)),
(N_h[(0, -1), -1], 2, FN(-P))
]
fu_tot_poteng = FuPotEngTotal(kappa=0.0, thickness=0.01,
rho=23.6,
F_ext_list=F_ext_list)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.init_displ_task,
config=sim_config, n_steps=self.n_fold_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
N_down = np.hstack([N_h[::3, :].flatten(),
N_i[1::3, :].flatten()
])
print 'N_down', N_down
N_up = np.hstack([N_i[::3, :].flatten(),
N_i[2::3, :].flatten(),
N_v[:, :].flatten()])
print 'N_up', N_up
cp.u[N_down, 2] -= self.d_down
cp.u[N_up, 2] += self.d_up
cp.u[:, 2] += self.d_down
return st