def createIntegrator(self, tacs, options):
"""
Create the Integrator (solver) and configure it
"""
end_time = options['steps'] * options['step_size']
# Create an integrator for TACS
if options['integrator'] == 'BDF':
integrator = TACS.BDFIntegrator(tacs, options['start_time'],
end_time, options['steps'],
options['integration_order'])
# Set other parameters for integration
integrator.setRelTol(options['solver_rel_tol'])
integrator.setAbsTol(options['solver_abs_tol'])
integrator.setMaxNewtonIters(options['max_newton_iters'])
integrator.setUseFEMat(options['femat'], options['ordering'])
#integrator.setPrintLevel(options['print_level'])
integrator.setOutputFrequency(options['output_freq'])
return integrator
assembler = TACS.Assembler.create(comm, 1, 1, 1)
conn = np.array([0], dtype=np.intc)
ptr = np.array([0, 1], dtype=np.intc)
assembler.setElementConnectivity(conn, ptr)
assembler.setElements([spr])
assembler.initialize()
# Create instance of integrator
t0 = 0.0
dt = 0.01
num_steps = 1000
tf = num_steps * dt
order = 2
bdf = TACS.BDFIntegrator(assembler, t0, tf, num_steps, order)
# Integrate governing equations
#bdf.integrate()
bdf.iterate(0)
for step in range(1, num_steps + 1):
bdf.iterate(step)
_, uvec, _, _ = bdf.getStates(num_steps)
u = uvec.getArray()
print "f = ", u
print "df/dx, approx = ", u.imag / 1e-30
# Write out solution
bdf.writeRawSolution('spring.dat', 0)
conn = np.array([0], dtype=np.intc)
ptr = np.array([0, 1], dtype=np.intc)
assembler.setElementConnectivity(conn, ptr)
assembler.setElements([spr])
assembler.initialize()
# Time marching setup
tinit = 0.0
tfinal = 1000.0
# Create integrators for implicit time marching of system
sizes = [1250, 2500, 5000, 10000]
for nsteps in sizes:
# BDF solution
bdf_orders = [1, 2, 3]
for order in bdf_orders:
bdf = TACS.BDFIntegrator(assembler, tinit, tfinal, nsteps, order)
bdf.setPrintLevel(0)
bdf.integrate()
bdf.writeRawSolution(
'smd-bdf' + str(order) + '-' + str(nsteps) + '.dat', 0)
# DIRK solution
dirk_orders = [2, 3, 4]
for order in dirk_orders:
dirk = TACS.DIRKIntegrator(assembler, tinit, tfinal, nsteps, order - 1)
dirk.setPrintLevel(0)
dirk.integrate()
dirk.writeRawSolution(
'smd-dirk' + str(order) + '-' + str(nsteps) + '.dat', 0)
data = []
def print_details(method, function, index, stepsize, fvals, adj_dfdx, fd_dfdx):
#data.append([method, function, stepsize, adj_dfdx, fd_dfdx])
record = dict(method=method, function=function, index=index, dh=stepsize,
adjoint=adj_dfdx, complex_step=fd_dfdx,
error=fd_dfdx - adj_dfdx)
data.append(record)
print("%10s %20s %4d %25.16e %25.16e %25.16e %25.16e %25.16e" %
(method, function, index, stepsize, fvals, adj_dfdx, fd_dfdx, fd_dfdx - adj_dfdx))
#---------------------------------------------------------------------#
# BDF Integrator
#---------------------------------------------------------------------#
for bdf_order in [1,2,3]:
bdf = TACS.BDFIntegrator(tacs, tinit, tfinal, num_steps_per_sec, bdf_order)
bdf.setPrintLevel(0)
bdf.setJacAssemblyFreq(1)
bdf.setFunction(funcs)
bdf.getFuncGrad(num_design_vars, x, fvals, dfdx)
bdf.getFDFuncGrad(num_design_vars, x, fvals_fd, dfdx_fd, dh)
fnum = 0
for func in funcs:
print_details("BDF" + str(bdf_order), func.__class__.__name__, fnum,
dh,
fvals[fnum],
np.real(dfdx[fnum]), np.real(dfdx_fd[fnum]))
fnum += 1
v[0] = 1.0
return
def addResidual(self, time, res, X, v, dv, ddv):
res[0] += self.m * ddv[0] + self.c * dv[0] + self.k * v[0]
return
def addJacobian(self, time, J, alpha, beta, gamma, X, v, dv, ddv):
J[0] += alpha * self.k + beta * self.c + gamma * self.m
return
spr = SpringMassDamper(1, 1, 1.0, 0.5, 5.0)
comm = MPI.COMM_WORLD
assembler = TACS.Assembler.create(comm, 1, 1, 1)
conn = np.array([0], dtype=np.intc)
ptr = np.array([0, 1], dtype=np.intc)
assembler.setElementConnectivity(conn, ptr)
assembler.setElements([spr])
assembler.initialize()
bdf = TACS.BDFIntegrator(assembler, 0.0, 100.0, 1000, 2)
bdf.integrate()
bdf.writeRawSolution('spring.dat', 0)
element = elements.MITC(stiff, gravity, v0, w0)
mesh.setElement(i, element)
tacs = mesh.createTACS(8)
######################################################################
# Time integration #
######################################################################
# Configure F5 output if tecplot output is required
f5_format = "output/plate_%04d.f5"
flag = (TACS.ToFH5.NODES | TACS.ToFH5.DISPLACEMENTS | TACS.ToFH5.STRAINS
| TACS.ToFH5.STRESSES | TACS.ToFH5.EXTRAS)
f5 = TACS.ToFH5(tacs, TACS.PY_SHELL, flag)
# Create the BDF integrator solver
tfinal = 0.5
num_steps_per_second = 250.0
order = 2
# Set the file output format
solver = TACS.BDFIntegrator(tacs, 0.0, tfinal, num_steps_per_second, order)
solver.setRelTol(1e-8)
#solver.setPrintLevel(2)
#solver.setOrderingType(TACS.PY_NATURAL_ORDER)
#solver.setUseLapack(1)
solver.setMaxNewtonIters(20)
solver.configureF5Output(f5, 1, f5_format)
solver.integrate()
def createSolver(params, pc):
'''
Creating solver
'''
if pc is not None:
pc.initialize()
print("number of basis terms = ", pc.getNumBasisTerms())
if params is not None:
m1 = params[0]
m2 = params[1]
m3 = params[2]
else:
m1 = 1.0
m2 = 10.0
m3 = 100.0
# Create TACS
M = np.matrix([[m1, 0.0, 0.0], [0.0, m2, 0.0], [0.0, 0.0, m3]])
k1 = 1.0
k2 = 10.0
k3 = 100.0
k4 = 1000.0
K = np.matrix([[k1 + k2, -k2, 0.0], [-k2, k2 + k3, -k3],
[0.0, -k3, k3 + k4]])
# Spring element
num_disps = 3
num_nodes = 1
dspr = SpringMassDamper(num_disps, num_nodes, M, K)
if pc is not None:
sprcb = SMDUpdate(dspr)
sspr = STACS.PyStochasticElement(dspr, pc, sprcb)
# dforce = ForcingElement(num_disps, num_nodes, amplitude=1.0, omega=10.0)
# forcecb = ForceUpdate(dforce)
# sforce = STACS.PyStochasticElement(dforce, pc, forcecb)
if pc is not None:
ndof_per_node = num_disps * pc.getNumBasisTerms()
else:
ndof_per_node = num_disps
num_owned_nodes = 1
num_elems = 1
# Add user-defined element to TACS
comm = MPI.COMM_WORLD
assembler = TACS.Assembler.create(comm, ndof_per_node, num_owned_nodes,
num_elems)
ptr = np.array([0, 1], dtype=np.intc)
conn = np.array([0], dtype=np.intc)
assembler.setElementConnectivity(ptr, conn)
# Set elements
if pc is not None:
assembler.setElements([sspr])
else:
assembler.setElements([dspr])
# set Auxiliary elements
# aux = TACS.AuxElements()
# aux.addElement(0, sforce)
# assembler.setAuxElements(aux)
assembler.initialize()
# Create Integrator
t0 = 0.0
tf = 2.0
num_steps = 100
order = 2
integrator = TACS.BDFIntegrator(assembler, t0, tf, num_steps, order)
integrator.setPrintLevel(1)
integrator.integrate()
return integrator
def integrate(assembler, forest, tfinal=30.0, nsteps=30, output=False):
# Create the BDF integrator
tinit = 0.0
order = 2
bdf = TACS.BDFIntegrator(assembler, tinit, tfinal, nsteps, order)
bdf.setPrintLevel(0)
bdf.setAbsTol(1e-6)
bdf.setRelTol(1e-15)
if output:
# Set the output file name
flag = (TACS.OUTPUT_CONNECTIVITY | TACS.OUTPUT_NODES
| TACS.OUTPUT_DISPLACEMENTS | TACS.OUTPUT_EXTRAS)
f5 = TACS.ToFH5(assembler, TACS.PLANE_STRESS_ELEMENT, flag)
bdf.setFH5(f5)
bdf.setOutputFrequency(1)
bdf.setOutputPrefix('time_history/')
# Define the functions of interest
temp0 = functions.KSTemperature(assembler, 50.0)
temp0.setKSTemperatureType('discrete')
elems, _ = get_elems_and_surfs(['battery_0'])
temp0.setDomain(elems)
temp1 = functions.KSTemperature(assembler, 50.0)
temp1.setKSTemperatureType('discrete')
elems, _ = get_elems_and_surfs(['battery_1'])
temp1.setDomain(elems)
temp2 = functions.KSTemperature(assembler, 50.0)
temp2.setKSTemperatureType('discrete')
elems, _ = get_elems_and_surfs(['battery_2'])
temp2.setDomain(elems)
# Set the functions into the integrator class
bdf.setFunctions([temp0, temp1, temp2])
# Create a vector that will store the instantaneous traction
# load at any point in time
forces = assembler.createVec()
# Compute the tractions due to a unit input heat flux
unit_forces = update_force(forest, assembler, qdot_in=1.0)
# Iterate in time to march the equations of motion forward
# in time
t_array = np.linspace(tinit, tfinal, nsteps + 1)
for i, t in enumerate(t_array):
# Compute the magnitude of the input heat flux
q_in = qdot_in_func(t)
# Copy the unit force values and scale by the heat flux
forces.copyValues(unit_forces)
forces.scale(q_in)
# Iterate forward in time for one time step
bdf.iterate(i, forces=forces)
# Compute the nodal sensitivities
fvals = bdf.evalFunctions([temp0, temp1, temp2])
bdf.integrateAdjoint()
df0dXpt = bdf.getXptGradient(0)
df1dXpt = bdf.getXptGradient(1)
df2dXpt = bdf.getXptGradient(2)
dfdXpt = [df0dXpt, df1dXpt, df2dXpt]
# Extract the time history
qvals = np.zeros(nsteps + 1)
tvals = np.zeros(nsteps + 1)
for time_step in range(nsteps + 1):
# Extract vectors
time, q, _, _ = bdf.getStates(time_step)
# Extract Arrays
qarray = q.getArray()
qvals[time_step] = np.amax(qarray)
tvals[time_step] = time
# Evaluate the functions at every time step
temp0_vals = np.zeros(nsteps + 1)
temp1_vals = np.zeros(nsteps + 1)
temp2_vals = np.zeros(nsteps + 1)
for time_step in range(nsteps + 1):
# Extract vectors
_, q, qdot, qddot = bdf.getStates(time_step)
# Compute the function values
assembler.setVariables(q)
fvals = assembler.evalFunctions([temp0, temp1, temp2])
temp0_vals[time_step] = fvals[0]
temp1_vals[time_step] = fvals[1]
temp2_vals[time_step] = fvals[2]
fvals = [temp0_vals, temp1_vals, temp2_vals]
return tvals, qvals, fvals, dfdXpt
