def compute_residual(self, y, PD_deck, t_n):
residual = np.zeros((int(PD_deck.Num_Nodes)))
#from elastic import elastic_material
from viscoelastic import viscoelastic_material
# Middle node doesn't move
Mid_Node = int(PD_deck.Num_Nodes / 2)
y[Mid_Node] = self.x[Mid_Node]
#variables = elastic_material( PD_deck, self, y )
variables = viscoelastic_material(PD_deck, self, y, t_n)
self.update_force_data(variables, t_n)
self.update_ext_state_data(variables, t_n)
self.update_ext_state_visco_data(variables, t_n)
residual = np.zeros( ( int(PD_deck.Num_Nodes) ) )
# Middle node doesn't move
Mid_Node = int(PD_deck.Num_Nodes/2)
y[Mid_Node] = self.x[Mid_Node]
# Choice of the material class
if PD_deck.Material_Flag == "ELASTIC":
from elastic import elastic_material
variables = elastic_material( PD_deck, self, y )
self.update_force_data(variables, t_n)
self.update_ext_state_data(variables, t_n)
elif PD_deck.Material_Flag == "VISCOELASTIC":
from viscoelastic import viscoelastic_material
variables = viscoelastic_material( PD_deck, self, y, t_n)
self.update_force_data(variables, t_n)
self.update_ext_state_data(variables, t_n)
self.update_ext_state_visco_data(variables, t_n)
else:
logger.error("There is a problem with the Type of Material in your XML deck.")
# Computation of the residual
for x_i in range(0, Mid_Node):
residual[x_i] = variables.Ts[x_i] + self.b[x_i, t_n]
for x_i in range(Mid_Node + 1, len(self.x)):
residual[x_i] = variables.Ts[x_i] + self.b[x_i, t_n]
# print residual
return residual
def compute_residual(self, y, PD_deck, t_n):
residual = np.zeros((int(PD_deck.Num_Nodes)))
from elastic import elastic_material
variables = elastic_material(PD_deck, self, y)
self.update_force_data(variables, t_n)
self.update_ext_state_data(variables, t_n)
for x_i in range(PD_deck.Horizon_Factor, len(self.x)):
if PD_deck.Loading_Flag == "RAMP":
residual[x_i] = variables.Ts[x_i] + self.b[x_i, t_n]
else:
residual[x_i] = variables.Ts[x_i]
# From johntfoster/1DPDpy, the residual should be set to 0 on
# Boundary conditions
for x_i in range(0, PD_deck.Horizon_Factor):
#Clamped node
residual[x_i] = 0
#Pulling nodes
residual[len(self.x) - 1 - x_i] = 0
return residual
def quasi_static_solver(self, y, PD_deck):
for t_n in range(1, PD_deck.Num_TimeStep):
if PD_deck.Loading_Flag == "LINEAR_DISPLACEMENT":
if t_n == 1:
for x_i in range(0, PD_deck.Horizon_Factor):
self.y[:, t_n] = self.x
y = self.y[:, t_n]
# Update the boundary conditions
# Clamped Nodes
for x_i in range(0, PD_deck.Horizon_Factor):
y[x_i] = self.x[x_i]
# Nodes being pulled
for x_i in range(0, PD_deck.Horizon_Factor):
y[len(self.x) - 1 - x_i] = self.x[len(self.x) -
1 - x_i] + self.displ_load[x_i, t_n]
# Compute the forces and energy before solving the equilibrium
# Else the force is null since equilibrium has been reached
from elastic import elastic_material
variables = elastic_material(PD_deck, self, y)
self.update_energy_data(variables, t_n)
print "t_n", t_n
print "BEFORE:", y
solver = scipy.optimize.root(
self.compute_residual,
y,
args=(
PD_deck,
t_n),
method='krylov',
jac=None,
tol=1.0e-12,
callback=None,
options={
'maxiter': 1000,
'xtol': 1.0e-12,
'xatol': 1.0e-12,
'ftol': 1.0e-12})
print "AFTER:", solver.x
# pdb.set_trace()
if t_n + 1 > PD_deck.Num_TimeStep - 1:
pass
else:
self.y[:, t_n + 1] = solver.x
#y = solver.x + 0.1*random.uniform(-1,1)*PD_deck.Delta_x
y = self.random_initial_guess(solver.x, PD_deck)
# Notification if the solver failed
if solver.success == "False":
logger.warning("Convergence could not be reached.")
else:
logger.info(t_n, solver.success)
self.update_displacements(t_n)
return solver
