def main():
from sfepy import data_dir
parser = OptionParser(usage=usage, version='%prog')
parser.add_option('--diffusivity',
metavar='float',
type=float,
action='store',
dest='diffusivity',
default=1e-5,
help=helps['diffusivity'])
parser.add_option('--ic-max',
metavar='float',
type=float,
action='store',
dest='ic_max',
default=2.0,
help=helps['ic_max'])
parser.add_option('--order',
metavar='int',
type=int,
action='store',
dest='order',
default=2,
help=helps['order'])
parser.add_option('-r',
'--refine',
metavar='int',
type=int,
action='store',
dest='refine',
default=0,
help=helps['refine'])
parser.add_option('-p',
'--probe',
action="store_true",
dest='probe',
default=False,
help=helps['probe'])
parser.add_option('-s',
'--show',
action="store_true",
dest='show',
default=False,
help=helps['show'])
options, args = parser.parse_args()
assert_((0 < options.order),
'temperature approximation order must be at least 1!')
output('using values:')
output(' diffusivity:', options.diffusivity)
output(' max. IC value:', options.ic_max)
output('uniform mesh refinement level:', options.refine)
mesh = Mesh.from_file(data_dir + '/meshes/3d/cylinder.mesh')
domain = FEDomain('domain', mesh)
if options.refine > 0:
for ii in xrange(options.refine):
output('refine %d...' % ii)
domain = domain.refine()
output('... %d nodes %d elements' %
(domain.shape.n_nod, domain.shape.n_el))
omega = domain.create_region('Omega', 'all')
left = domain.create_region('Left', 'vertices in x < 0.00001', 'facet')
right = domain.create_region('Right', 'vertices in x > 0.099999', 'facet')
field = Field.from_args('fu',
nm.float64,
'scalar',
omega,
approx_order=options.order)
T = FieldVariable('T', 'unknown', field, history=1)
s = FieldVariable('s', 'test', field, primary_var_name='T')
m = Material('m', diffusivity=options.diffusivity * nm.eye(3))
integral = Integral('i', order=2 * options.order)
t1 = Term.new('dw_diffusion(m.diffusivity, s, T)',
integral,
omega,
m=m,
s=s,
T=T)
t2 = Term.new('dw_volume_dot(s, dT/dt)', integral, omega, s=s, T=T)
eq = Equation('balance', t1 + t2)
eqs = Equations([eq])
# Boundary conditions.
ebc1 = EssentialBC('T1', left, {'T.0': 2.0})
ebc2 = EssentialBC('T2', right, {'T.0': -2.0})
# Initial conditions.
def get_ic(coors, ic):
x, y, z = coors.T
return 2 - 40.0 * x + options.ic_max * nm.sin(4 * nm.pi * x / 0.1)
ic_fun = Function('ic_fun', get_ic)
ic = InitialCondition('ic', omega, {'T.0': ic_fun})
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton({'is_linear': True}, lin_solver=ls, status=nls_status)
pb = Problem('heat', equations=eqs, nls=nls, ls=ls)
pb.set_bcs(ebcs=Conditions([ebc1, ebc2]))
pb.set_ics(Conditions([ic]))
tss = SimpleTimeSteppingSolver({
't0': 0.0,
't1': 100.0,
'n_step': 11
},
problem=pb)
tss.init_time()
if options.probe:
# Prepare probe data.
probes, labels = gen_lines(pb)
ev = pb.evaluate
order = 2 * (options.order - 1)
gfield = Field.from_args('gu',
nm.float64,
'vector',
omega,
approx_order=options.order - 1)
dvel = FieldVariable('dvel',
'parameter',
gfield,
primary_var_name='(set-to-None)')
cfield = Field.from_args('gu',
nm.float64,
'scalar',
omega,
approx_order=options.order - 1)
component = FieldVariable('component',
'parameter',
cfield,
primary_var_name='(set-to-None)')
nls_options = {'eps_a': 1e-16, 'i_max': 1}
if options.show:
plt.ion()
# Solve the problem using the time stepping solver.
suffix = tss.ts.suffix
for step, time, state in tss():
if options.probe:
# Probe the solution.
dvel_qp = ev('ev_diffusion_velocity.%d.Omega(m.diffusivity, T)' %
order,
copy_materials=False,
mode='qp')
project_by_component(dvel,
dvel_qp,
component,
order,
nls_options=nls_options)
all_results = []
for ii, probe in enumerate(probes):
fig, results = probe_results(ii, T, dvel, probe, labels[ii])
all_results.append(results)
plt.tight_layout()
fig.savefig('time_poisson_interactive_probe_%s.png' %
(suffix % step),
bbox_inches='tight')
if options.show:
plt.draw()
for ii, results in enumerate(all_results):
output('probe %d (%s):' % (ii, probes[ii].name))
output.level += 2
for key, res in ordered_iteritems(results):
output(key + ':')
val = res[1]
output(' min: %+.2e, mean: %+.2e, max: %+.2e' %
(val.min(), val.mean(), val.max()))
output.level -= 2
def main():
from sfepy import data_dir
parser = OptionParser(usage=usage, version='%prog')
parser.add_option('--diffusivity', metavar='float', type=float,
action='store', dest='diffusivity',
default=1e-5, help=helps['diffusivity'])
parser.add_option('--ic-max', metavar='float', type=float,
action='store', dest='ic_max',
default=2.0, help=helps['ic_max'])
parser.add_option('--order', metavar='int', type=int,
action='store', dest='order',
default=2, help=helps['order'])
parser.add_option('-r', '--refine', metavar='int', type=int,
action='store', dest='refine',
default=0, help=helps['refine'])
parser.add_option('-p', '--probe',
action="store_true", dest='probe',
default=False, help=helps['probe'])
parser.add_option('-s', '--show',
action="store_true", dest='show',
default=False, help=helps['show'])
options, args = parser.parse_args()
assert_((0 < options.order),
'temperature approximation order must be at least 1!')
output('using values:')
output(' diffusivity:', options.diffusivity)
output(' max. IC value:', options.ic_max)
output('uniform mesh refinement level:', options.refine)
mesh = Mesh.from_file(data_dir + '/meshes/3d/cylinder.mesh')
domain = FEDomain('domain', mesh)
if options.refine > 0:
for ii in range(options.refine):
output('refine %d...' % ii)
domain = domain.refine()
output('... %d nodes %d elements'
% (domain.shape.n_nod, domain.shape.n_el))
omega = domain.create_region('Omega', 'all')
left = domain.create_region('Left',
'vertices in x < 0.00001', 'facet')
right = domain.create_region('Right',
'vertices in x > 0.099999', 'facet')
field = Field.from_args('fu', nm.float64, 'scalar', omega,
approx_order=options.order)
T = FieldVariable('T', 'unknown', field, history=1)
s = FieldVariable('s', 'test', field, primary_var_name='T')
m = Material('m', diffusivity=options.diffusivity * nm.eye(3))
integral = Integral('i', order=2*options.order)
t1 = Term.new('dw_diffusion(m.diffusivity, s, T)',
integral, omega, m=m, s=s, T=T)
t2 = Term.new('dw_volume_dot(s, dT/dt)',
integral, omega, s=s, T=T)
eq = Equation('balance', t1 + t2)
eqs = Equations([eq])
# Boundary conditions.
ebc1 = EssentialBC('T1', left, {'T.0' : 2.0})
ebc2 = EssentialBC('T2', right, {'T.0' : -2.0})
# Initial conditions.
def get_ic(coors, ic):
x, y, z = coors.T
return 2 - 40.0 * x + options.ic_max * nm.sin(4 * nm.pi * x / 0.1)
ic_fun = Function('ic_fun', get_ic)
ic = InitialCondition('ic', omega, {'T.0' : ic_fun})
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton({'is_linear' : True}, lin_solver=ls, status=nls_status)
pb = Problem('heat', equations=eqs, nls=nls, ls=ls)
pb.set_bcs(ebcs=Conditions([ebc1, ebc2]))
pb.set_ics(Conditions([ic]))
tss = SimpleTimeSteppingSolver({'t0' : 0.0, 't1' : 100.0, 'n_step' : 11},
problem=pb)
tss.init_time()
if options.probe:
# Prepare probe data.
probes, labels = gen_lines(pb)
ev = pb.evaluate
order = 2 * (options.order - 1)
gfield = Field.from_args('gu', nm.float64, 'vector', omega,
approx_order=options.order - 1)
dvel = FieldVariable('dvel', 'parameter', gfield,
primary_var_name='(set-to-None)')
cfield = Field.from_args('gu', nm.float64, 'scalar', omega,
approx_order=options.order - 1)
component = FieldVariable('component', 'parameter', cfield,
primary_var_name='(set-to-None)')
nls_options = {'eps_a' : 1e-16, 'i_max' : 1}
if options.show:
plt.ion()
# Solve the problem using the time stepping solver.
suffix = tss.ts.suffix
for step, time, state in tss():
if options.probe:
# Probe the solution.
dvel_qp = ev('ev_diffusion_velocity.%d.Omega(m.diffusivity, T)'
% order, copy_materials=False, mode='qp')
project_by_component(dvel, dvel_qp, component, order,
nls_options=nls_options)
all_results = []
for ii, probe in enumerate(probes):
fig, results = probe_results(ii, T, dvel, probe, labels[ii])
all_results.append(results)
plt.tight_layout()
fig.savefig('time_poisson_interactive_probe_%s.png'
% (suffix % step), bbox_inches='tight')
if options.show:
plt.draw()
for ii, results in enumerate(all_results):
output('probe %d (%s):' % (ii, probes[ii].name))
output.level += 2
for key, res in ordered_iteritems(results):
output(key + ':')
val = res[1]
output(' min: %+.2e, mean: %+.2e, max: %+.2e'
% (val.min(), val.mean(), val.max()))
output.level -= 2
def main(cli_args):
dims = parse_argument_list(cli_args.dims, float)
shape = parse_argument_list(cli_args.shape, int)
centre = parse_argument_list(cli_args.centre, float)
material_parameters = parse_argument_list(cli_args.material_parameters,
float)
order = cli_args.order
ts_vals = cli_args.ts.split(',')
ts = {
't0' : float(ts_vals[0]), 't1' : float(ts_vals[1]),
'n_step' : int(ts_vals[2])}
do_plot = cli_args.plot
### Mesh and regions ###
mesh = gen_block_mesh(
dims, shape, centre, name='block', verbose=False)
domain = FEDomain('domain', mesh)
omega = domain.create_region('Omega', 'all')
lbn, rtf = domain.get_mesh_bounding_box()
box_regions = define_box_regions(3, lbn, rtf)
regions = dict([
[r, domain.create_region(r, box_regions[r][0], box_regions[r][1])]
for r in box_regions])
### Fields ###
scalar_field = Field.from_args(
'fu', np.float64, 'scalar', omega, approx_order=order-1)
vector_field = Field.from_args(
'fv', np.float64, 'vector', omega, approx_order=order)
u = FieldVariable('u', 'unknown', vector_field, history=1)
v = FieldVariable('v', 'test', vector_field, primary_var_name='u')
p = FieldVariable('p', 'unknown', scalar_field, history=1)
q = FieldVariable('q', 'test', scalar_field, primary_var_name='p')
### Material ###
c10, c01 = material_parameters
m = Material(
'm', mu=2*c10, kappa=2*c01,
)
### Boundary conditions ###
x_sym = EssentialBC('x_sym', regions['Left'], {'u.0' : 0.0})
y_sym = EssentialBC('y_sym', regions['Near'], {'u.1' : 0.0})
z_sym = EssentialBC('z_sym', regions['Bottom'], {'u.2' : 0.0})
disp_fun = Function('disp_fun', get_displacement)
displacement = EssentialBC(
'displacement', regions['Right'], {'u.0' : disp_fun})
ebcs = Conditions([x_sym, y_sym, z_sym, displacement])
### Terms and equations ###
integral = Integral('i', order=2*order)
term_neohook = Term.new(
'dw_tl_he_neohook(m.mu, v, u)',
integral, omega, m=m, v=v, u=u)
term_mooney = Term.new(
'dw_tl_he_mooney_rivlin(m.kappa, v, u)',
integral, omega, m=m, v=v, u=u)
term_pressure = Term.new(
'dw_tl_bulk_pressure(v, u, p)',
integral, omega, v=v, u=u, p=p)
term_volume_change = Term.new(
'dw_tl_volume(q, u)',
integral, omega, q=q, u=u, term_mode='volume')
term_volume = Term.new(
'dw_volume_integrate(q)',
integral, omega, q=q)
eq_balance = Equation('balance', term_neohook+term_mooney+term_pressure)
eq_volume = Equation('volume', term_volume_change-term_volume)
equations = Equations([eq_balance, eq_volume])
### Solvers ###
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton(
{'i_max' : 5},
lin_solver=ls, status=nls_status
)
### Problem ###
pb = Problem('hyper', equations=equations)
pb.set_bcs(ebcs=ebcs)
pb.set_ics(ics=Conditions([]))
tss = SimpleTimeSteppingSolver(ts, nls=nls, context=pb)
pb.set_solver(tss)
### Solution ###
axial_stress = []
axial_displacement = []
def stress_strain_fun(*args, **kwargs):
return stress_strain(
*args, order=order, global_stress=axial_stress,
global_displacement=axial_displacement, **kwargs)
pb.solve(save_results=True, post_process_hook=stress_strain_fun)
if do_plot:
plot_graphs(
material_parameters, axial_stress, axial_displacement,
undeformed_length=dims[0])
def main(cli_args):
dims = parse_argument_list(cli_args.dims, float)
shape = parse_argument_list(cli_args.shape, int)
centre = parse_argument_list(cli_args.centre, float)
material_parameters = parse_argument_list(cli_args.material_parameters,
float)
order = cli_args.order
ts_vals = cli_args.ts.split(',')
ts = {
't0': float(ts_vals[0]),
't1': float(ts_vals[1]),
'n_step': int(ts_vals[2])
}
do_plot = cli_args.plot
### Mesh and regions ###
mesh = gen_block_mesh(dims, shape, centre, name='block', verbose=False)
domain = FEDomain('domain', mesh)
omega = domain.create_region('Omega', 'all')
lbn, rtf = domain.get_mesh_bounding_box()
box_regions = define_box_regions(3, lbn, rtf)
regions = dict(
[[r, domain.create_region(r, box_regions[r][0], box_regions[r][1])]
for r in box_regions])
### Fields ###
scalar_field = Field.from_args('fu',
np.float64,
'scalar',
omega,
approx_order=order - 1)
vector_field = Field.from_args('fv',
np.float64,
'vector',
omega,
approx_order=order)
u = FieldVariable('u', 'unknown', vector_field, history=1)
v = FieldVariable('v', 'test', vector_field, primary_var_name='u')
p = FieldVariable('p', 'unknown', scalar_field, history=1)
q = FieldVariable('q', 'test', scalar_field, primary_var_name='p')
### Material ###
c10, c01 = material_parameters
m = Material(
'm',
mu=2 * c10,
kappa=2 * c01,
)
### Boundary conditions ###
x_sym = EssentialBC('x_sym', regions['Left'], {'u.0': 0.0})
y_sym = EssentialBC('y_sym', regions['Near'], {'u.1': 0.0})
z_sym = EssentialBC('z_sym', regions['Bottom'], {'u.2': 0.0})
disp_fun = Function('disp_fun', get_displacement)
displacement = EssentialBC('displacement', regions['Right'],
{'u.0': disp_fun})
ebcs = Conditions([x_sym, y_sym, z_sym, displacement])
### Terms and equations ###
integral = Integral('i', order=2 * order)
term_neohook = Term.new('dw_tl_he_neohook(m.mu, v, u)',
integral,
omega,
m=m,
v=v,
u=u)
term_mooney = Term.new('dw_tl_he_mooney_rivlin(m.kappa, v, u)',
integral,
omega,
m=m,
v=v,
u=u)
term_pressure = Term.new('dw_tl_bulk_pressure(v, u, p)',
integral,
omega,
v=v,
u=u,
p=p)
term_volume_change = Term.new('dw_tl_volume(q, u)',
integral,
omega,
q=q,
u=u,
term_mode='volume')
term_volume = Term.new('dw_volume_integrate(q)', integral, omega, q=q)
eq_balance = Equation('balance',
term_neohook + term_mooney + term_pressure)
eq_volume = Equation('volume', term_volume_change - term_volume)
equations = Equations([eq_balance, eq_volume])
### Solvers ###
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton({'i_max': 5}, lin_solver=ls, status=nls_status)
### Problem ###
pb = Problem('hyper', equations=equations)
pb.set_bcs(ebcs=ebcs)
pb.set_ics(ics=Conditions([]))
tss = SimpleTimeSteppingSolver(ts, nls=nls, context=pb)
pb.set_solver(tss)
### Solution ###
axial_stress = []
axial_displacement = []
def stress_strain_fun(*args, **kwargs):
return stress_strain(*args,
order=order,
global_stress=axial_stress,
global_displacement=axial_displacement,
**kwargs)
pb.solve(save_results=True, post_process_hook=stress_strain_fun)
if do_plot:
plot_graphs(material_parameters,
axial_stress,
axial_displacement,
undeformed_length=dims[0])
def main(argv=None):
options = parse_args(argv=argv)
# vvvvvvvvvvvvvvvv #
approx_order = 2
# ^^^^^^^^^^^^^^^^ #
# Setup output names
outputs_folder = options.output_dir
domain_name = "domain_1D"
problem_name = "iburgers_1D"
output_folder = pjoin(outputs_folder, problem_name, str(approx_order))
output_format = "vtk"
save_timestn = 100
clear_folder(pjoin(output_folder, "*." + output_format))
configure_output({
'output_screen':
True,
'output_log_name':
pjoin(output_folder, f"last_run_{problem_name}_{approx_order}.txt")
})
# ------------
# | Get mesh |
# ------------
X1 = 0.
XN = 1.
n_nod = 100
n_el = n_nod - 1
mesh = get_gen_1D_mesh_hook(X1, XN, n_nod).read(None)
# -----------------------------
# | Create problem components |
# -----------------------------
integral = Integral('i', order=approx_order * 2)
domain = FEDomain(domain_name, mesh)
omega = domain.create_region('Omega', 'all')
left = domain.create_region('Gamma1', 'vertices in x == %.10f' % X1,
'vertex')
right = domain.create_region('Gamma2', 'vertices in x == %.10f' % XN,
'vertex')
field = DGField('dgfu',
nm.float64,
'scalar',
omega,
approx_order=approx_order)
u = FieldVariable('u', 'unknown', field, history=1)
v = FieldVariable('v', 'test', field, primary_var_name='u')
MassT = Term.new('dw_dot(v, u)', integral, omega, u=u, v=v)
velo = nm.array(1.0)
def adv_fun(u):
vu = velo.T * u[..., None]
return vu
def adv_fun_d(u):
v1 = velo.T * nm.ones(u.shape + (1, ))
return v1
burg_velo = velo.T / nm.linalg.norm(velo)
def burg_fun(u):
vu = burg_velo * u[..., None]**2
return vu
def burg_fun_d(u):
v1 = 2 * burg_velo * u[..., None]
return v1
StiffT = Term.new('dw_ns_dot_grad_s(fun, fun_d, u[-1], v)',
integral,
omega,
u=u,
v=v,
fun=burg_fun,
fun_d=burg_fun_d)
# alpha = Material('alpha', val=[.0])
# FluxT = AdvectDGFluxTerm("adv_lf_flux(a.val, v, u)", "a.val, v, u[-1]",
# integral, omega, u=u, v=v, a=a, alpha=alpha)
FluxT = Term.new('dw_dg_nonlinear_laxfrie_flux(fun, fun_d, v, u[-1])',
integral,
omega,
u=u,
v=v,
fun=burg_fun,
fun_d=burg_fun_d)
eq = Equation('balance', MassT - StiffT + FluxT)
eqs = Equations([eq])
# ------------------------------
# | Create boundary conditions |
# ------------------------------
left_fix_u = EssentialBC('left_fix_u', left, {'u.all': 1.0})
right_fix_u = EssentialBC('right_fix_u', right, {'u.all': 0.0})
# ----------------------------
# | Create initial condition |
# ----------------------------
def ghump(x):
"""
Nice gaussian.
"""
return nm.exp(-200 * x**2)
def ic_wrap(x, ic=None):
return ghump(x - .3)
ic_fun = Function('ic_fun', ic_wrap)
ics = InitialCondition('ic', omega, {'u.0': ic_fun})
# ------------------
# | Create problem |
# ------------------
pb = Problem(problem_name,
equations=eqs,
conf=Struct(options={"save_times": save_timestn},
ics={},
ebcs={},
epbcs={},
lcbcs={},
materials={}),
active_only=False)
pb.setup_output(output_dir=output_folder, output_format=output_format)
pb.set_ics(Conditions([ics]))
# ------------------
# | Create limiter |
# ------------------
limiter = MomentLimiter1D
# ---------------------------
# | Set time discretization |
# ---------------------------
CFL = .2
max_velo = nm.max(nm.abs(velo))
t0 = 0
t1 = .2
dx = nm.min(mesh.cmesh.get_volumes(1))
dt = dx / max_velo * CFL / (2 * approx_order + 1)
tn = int(nm.ceil((t1 - t0) / dt))
dtdx = dt / dx
# ------------------
# | Create solver |
# ------------------
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton({'is_linear': True}, lin_solver=ls, status=nls_status)
tss_conf = {
't0': t0,
't1': t1,
'n_step': tn,
'limiters': {
"dgfu": limiter
}
}
tss = TVDRK3StepSolver(tss_conf, nls=nls, context=pb, verbose=True)
# ---------
# | Solve |
# ---------
pb.set_solver(tss)
state_end = pb.solve()
output("Solved equation \n\n\t\t u_t - div(f(u))) = 0\n")
output(f"With IC: {ic_fun.name}")
# output("and EBCs: {}".format(pb.ebcs.names))
# output("and EPBCS: {}".format(pb.epbcs.names))
output("-------------------------------------")
output(f"Approximation order is {approx_order}")
output(f"Space divided into {mesh.n_el} cells, " +
f"{len(mesh.coors)} steps, step size is {dx}")
output(f"Time divided into {tn - 1} nodes, {tn} steps, step size is {dt}")
output(f"CFL coefficient was {CFL} and " +
f"order correction {1 / (2 * approx_order + 1)}")
output(f"Courant number c = max(abs(u)) * dt/dx = {max_velo * dtdx}")
output("------------------------------------------")
output(f"Time stepping solver is {tss.name}")
output(f"Limiter used: {limiter.name}")
output("======================================")
# ----------
# | Plot 1D|
# ----------
if options.plot:
load_and_plot_fun(output_folder, domain_name, t0, t1,
min(tn, save_timestn), ic_fun)
ics = InitialCondition('ic', omega, {'u.0': ic_fun})
# ------------------
# | Create problem |
# ------------------
pb = Problem(problem_name,
equations=eqs,
conf=Struct(options={"save_times": save_timestn},
ics={},
ebcs={},
epbcs={},
lcbcs={},
materials={}),
active_only=False)
pb.setup_output(output_dir=output_folder, output_format=output_format)
pb.set_ics(Conditions([ics]))
# ------------------
# | Create limiter |
# ------------------
limiter = MomentLimiter1D
# ---------------------------
# | Set time discretization |
# ---------------------------
CFL = .2
max_velo = nm.max(nm.abs(velo))
t0 = 0
t1 = .2
dx = nm.min(mesh.cmesh.get_volumes(1))
dt = dx / max_velo * CFL / (2 * approx_order + 1)
# vol = np.loadtxt('tmp_vol.dat')
#
# vm_stresses[i, 0] = np.sum(vms * vol) / np.sum(vol)
# vm_stresses[i, 1] = np.max(vms)
#
# pb.save_state('voronoi_foam_%f.vtk' % z_displacement, state)
#
### Solvers ###
ls = ScipyDirect({})
nls_status = IndexedStruct()
nls = Newton({'i_max': 20}, lin_solver=ls, status=nls_status)
### Problem ###
pb = Problem('hyper', equations=equations)
pb.set_bcs(ebcs=ebcs)
pb.set_ics(ics=Conditions([]))
tss = SimpleTimeSteppingSolver(ts, nls=nls, context=pb)
pb.set_solver(tss)
### Solution ###
axial_stress = []
axial_displacement = []
def stress_strain_fun(*args, **kwargs):
return stress_strain(*args,
order=order,
global_stress=axial_stress,
global_displacement=axial_displacement,
**kwargs)
pb.solve(save_results=True, post_process_hook=stress_strain_fun)
