def main(ctx_factory=cl.create_some_context, use_logmgr=True,
use_leap=False, use_profiling=False, casename=None,
rst_filename=None, actx_class=PyOpenCLArrayContext,
log_dependent=True):
"""Drive example."""
cl_ctx = ctx_factory()
if casename is None:
casename = "mirgecom"
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nparts = comm.Get_size()
from mirgecom.simutil import global_reduce as _global_reduce
global_reduce = partial(_global_reduce, comm=comm)
logmgr = initialize_logmgr(use_logmgr,
filename=f"{casename}.sqlite", mode="wu", mpi_comm=comm)
if use_profiling:
queue = cl.CommandQueue(
cl_ctx, properties=cl.command_queue_properties.PROFILING_ENABLE)
else:
queue = cl.CommandQueue(cl_ctx)
actx = actx_class(
queue,
allocator=cl_tools.MemoryPool(cl_tools.ImmediateAllocator(queue)))
# timestepping control
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
t_final = 1e-8
current_cfl = 1.0
current_dt = 1e-9
current_t = 0
current_step = 0
constant_cfl = False
# some i/o frequencies
nstatus = 1
nhealth = 1
nrestart = 5
nviz = 1
dim = 2
rst_path = "restart_data/"
rst_pattern = (
rst_path + "{cname}-{step:04d}-{rank:04d}.pkl"
)
if rst_filename: # read the grid from restart data
rst_filename = f"{rst_filename}-{rank:04d}.pkl"
from mirgecom.restart import read_restart_data
restart_data = read_restart_data(actx, rst_filename)
local_mesh = restart_data["local_mesh"]
local_nelements = local_mesh.nelements
global_nelements = restart_data["global_nelements"]
assert restart_data["num_parts"] == nparts
else: # generate the grid from scratch
nel_1d = 16
box_ll = -5.0
box_ur = 5.0
from meshmode.mesh.generation import generate_regular_rect_mesh
generate_mesh = partial(generate_regular_rect_mesh, a=(box_ll,)*dim,
b=(box_ur,) * dim, nelements_per_axis=(nel_1d,)*dim)
local_mesh, global_nelements = generate_and_distribute_mesh(comm,
generate_mesh)
local_nelements = local_mesh.nelements
order = 3
discr = EagerDGDiscretization(
actx, local_mesh, order=order, mpi_communicator=comm
)
nodes = thaw(discr.nodes(), actx)
vis_timer = None
if logmgr:
logmgr_add_device_name(logmgr, queue)
logmgr_add_device_memory_usage(logmgr, queue)
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
logmgr.add_watches([
("step.max", "step = {value}, "),
("t_sim.max", "sim time: {value:1.6e} s\n"),
("t_step.max", "------- step walltime: {value:6g} s, "),
("t_log.max", "log walltime: {value:6g} s")
])
if log_dependent:
logmgr_add_many_discretization_quantities(logmgr, discr, dim,
extract_vars_for_logging,
units_for_logging)
logmgr.add_watches([
("min_pressure", "\n------- P (min, max) (Pa) = ({value:1.9e}, "),
("max_pressure", "{value:1.9e})\n"),
("min_temperature", "------- T (min, max) (K) = ({value:7g}, "),
("max_temperature", "{value:7g})\n")])
# Pyrometheus initialization
from mirgecom.mechanisms import get_mechanism_cti
mech_cti = get_mechanism_cti("uiuc")
sol = cantera.Solution(phase_id="gas", source=mech_cti)
from mirgecom.thermochemistry import make_pyrometheus_mechanism_class
pyrometheus_mechanism = make_pyrometheus_mechanism_class(sol)(actx.np)
nspecies = pyrometheus_mechanism.num_species
eos = PyrometheusMixture(pyrometheus_mechanism)
from mirgecom.gas_model import GasModel, make_fluid_state
gas_model = GasModel(eos=eos)
from pytools.obj_array import make_obj_array
y0s = np.zeros(shape=(nspecies,))
for i in range(nspecies-1):
y0s[i] = 1.0 / (10.0 ** (i + 1))
spec_sum = sum([y0s[i] for i in range(nspecies-1)])
y0s[nspecies-1] = 1.0 - spec_sum
# Mixture defaults to STP (p, T) = (1atm, 300K)
velocity = np.zeros(shape=(dim,)) + 1.0
initializer = MixtureInitializer(dim=dim, nspecies=nspecies,
massfractions=y0s, velocity=velocity)
def boundary_solution(discr, btag, gas_model, state_minus, **kwargs):
actx = state_minus.array_context
bnd_discr = discr.discr_from_dd(btag)
nodes = thaw(bnd_discr.nodes(), actx)
return make_fluid_state(initializer(x_vec=nodes, eos=gas_model.eos,
**kwargs), gas_model,
temperature_seed=state_minus.temperature)
boundaries = {
BTAG_ALL: PrescribedFluidBoundary(boundary_state_func=boundary_solution)
}
if rst_filename:
current_t = restart_data["t"]
current_step = restart_data["step"]
current_cv = restart_data["cv"]
tseed = restart_data["temperature_seed"]
if logmgr:
from mirgecom.logging_quantities import logmgr_set_time
logmgr_set_time(logmgr, current_step, current_t)
else:
# Set the current state from time 0
current_cv = initializer(x_vec=nodes, eos=eos)
tseed = 300.0
current_state = make_fluid_state(current_cv, gas_model, temperature_seed=tseed)
visualizer = make_visualizer(discr)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim, order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt, t_final=t_final, nstatus=nstatus,
nviz=nviz, cfl=current_cfl,
constant_cfl=constant_cfl, initname=initname,
eosname=eosname, casename=casename)
if rank == 0:
logger.info(init_message)
def my_write_status(component_errors, dv=None):
from mirgecom.simutil import allsync
status_msg = (
"------- errors="
+ ", ".join("%.3g" % en for en in component_errors))
if ((dv is not None) and (not log_dependent)):
temp = dv.temperature
press = dv.pressure
from grudge.op import nodal_min_loc, nodal_max_loc
tmin = allsync(actx.to_numpy(nodal_min_loc(discr, "vol", temp)),
comm=comm, op=MPI.MIN)
tmax = allsync(actx.to_numpy(nodal_max_loc(discr, "vol", temp)),
comm=comm, op=MPI.MAX)
pmin = allsync(actx.to_numpy(nodal_min_loc(discr, "vol", press)),
comm=comm, op=MPI.MIN)
pmax = allsync(actx.to_numpy(nodal_max_loc(discr, "vol", press)),
comm=comm, op=MPI.MAX)
dv_status_msg = f"\nP({pmin}, {pmax}), T({tmin}, {tmax})"
status_msg = status_msg + dv_status_msg
if rank == 0:
logger.info(status_msg)
if rank == 0:
logger.info(status_msg)
def my_write_viz(step, t, state, dv, exact=None, resid=None):
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
if resid is None:
resid = state - exact
viz_fields = [("cv", state), ("dv", dv)]
from mirgecom.simutil import write_visfile
write_visfile(discr, viz_fields, visualizer, vizname=casename,
step=step, t=t, overwrite=True, vis_timer=vis_timer)
def my_write_restart(step, t, state, tseed):
rst_fname = rst_pattern.format(cname=casename, step=step, rank=rank)
if rst_fname != rst_filename:
rst_data = {
"local_mesh": local_mesh,
"cv": state,
"temperature_seed": tseed,
"t": t,
"step": step,
"order": order,
"global_nelements": global_nelements,
"num_parts": nparts
}
from mirgecom.restart import write_restart_file
write_restart_file(actx, rst_data, rst_fname, comm)
def my_health_check(dv, component_errors):
health_error = False
from mirgecom.simutil import check_naninf_local, check_range_local
if check_naninf_local(discr, "vol", dv.pressure) \
or check_range_local(discr, "vol", dv.pressure, 1e5, 1.1e5):
health_error = True
logger.info(f"{rank=}: Invalid pressure data found.")
exittol = .09
if max(component_errors) > exittol:
health_error = True
if rank == 0:
logger.info("Solution diverged from exact soln.")
return health_error
def my_pre_step(step, t, dt, state):
cv, tseed = state
fluid_state = make_fluid_state(cv, gas_model, temperature_seed=tseed)
dv = fluid_state.dv
try:
exact = None
component_errors = None
if logmgr:
logmgr.tick_before()
from mirgecom.simutil import check_step
do_viz = check_step(step=step, interval=nviz)
do_restart = check_step(step=step, interval=nrestart)
do_health = check_step(step=step, interval=nhealth)
do_status = check_step(step=step, interval=nstatus)
if do_health:
exact = initializer(x_vec=nodes, eos=eos, time=t)
from mirgecom.simutil import compare_fluid_solutions
component_errors = compare_fluid_solutions(discr, cv, exact)
health_errors = global_reduce(
my_health_check(dv, component_errors), op="lor")
if health_errors:
if rank == 0:
logger.info("Fluid solution failed health check.")
raise MyRuntimeError("Failed simulation health check.")
if do_restart:
my_write_restart(step=step, t=t, state=cv, tseed=tseed)
if do_viz:
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
resid = state - exact
my_write_viz(step=step, t=t, state=cv, dv=dv, exact=exact,
resid=resid)
if do_status:
if component_errors is None:
if exact is None:
exact = initializer(x_vec=nodes, eos=eos, time=t)
from mirgecom.simutil import compare_fluid_solutions
component_errors = compare_fluid_solutions(discr, cv, exact)
my_write_status(component_errors, dv=dv)
except MyRuntimeError:
if rank == 0:
logger.info("Errors detected; attempting graceful exit.")
my_write_viz(step=step, t=t, state=cv, dv=dv)
my_write_restart(step=step, t=t, state=cv, tseed=tseed)
raise
dt = get_sim_timestep(discr, fluid_state, t, dt, current_cfl, t_final,
constant_cfl)
return state, dt
def my_post_step(step, t, dt, state):
cv, tseed = state
fluid_state = make_fluid_state(cv, gas_model, temperature_seed=tseed)
tseed = fluid_state.temperature
# Logmgr needs to know about EOS, dt, dim?
# imo this is a design/scope flaw
if logmgr:
set_dt(logmgr, dt)
set_sim_state(logmgr, dim, cv, eos)
logmgr.tick_after()
return make_obj_array([fluid_state.cv, tseed]), dt
def my_rhs(t, state):
cv, tseed = state
fluid_state = make_fluid_state(cv, gas_model, temperature_seed=tseed)
return make_obj_array(
[euler_operator(discr, state=fluid_state, time=t,
boundaries=boundaries, gas_model=gas_model),
0*tseed])
current_dt = get_sim_timestep(discr, current_state, current_t, current_dt,
current_cfl, t_final, constant_cfl)
current_step, current_t, advanced_state = \
advance_state(rhs=my_rhs, timestepper=timestepper,
pre_step_callback=my_pre_step,
post_step_callback=my_post_step, dt=current_dt,
state=make_obj_array([current_state.cv,
current_state.temperature]),
t=current_t, t_final=t_final, eos=eos, dim=dim)
# Dump the final data
if rank == 0:
logger.info("Checkpointing final state ...")
current_cv, tseed = advanced_state
current_state = make_fluid_state(current_cv, gas_model, temperature_seed=tseed)
final_dv = current_state.dv
final_exact = initializer(x_vec=nodes, eos=eos, time=current_t)
final_resid = current_state.cv - final_exact
my_write_viz(step=current_step, t=current_t, state=current_cv, dv=final_dv,
exact=final_exact, resid=final_resid)
my_write_restart(step=current_step, t=current_t, state=current_state.cv,
tseed=tseed)
if logmgr:
logmgr.close()
elif use_profiling:
print(actx.tabulate_profiling_data())
finish_tol = 1e-16
assert np.abs(current_t - t_final) < finish_tol
SSPRK22MethodBuilder,
SSPRK33MethodBuilder,
)
from leap.rk.imex import KennedyCarpenterIMEXARK4MethodBuilder
from mirgecom.steppers import advance_state
@pytest.mark.parametrize(("method", "method_order"), [
(ODE23MethodBuilder("y", use_high_order=False), 2),
(ODE23MethodBuilder("y", use_high_order=True), 3),
(ODE45MethodBuilder("y", use_high_order=False), 4),
(ODE45MethodBuilder("y", use_high_order=True), 5),
(ForwardEulerMethodBuilder("y"), 1),
(MidpointMethodBuilder("y"), 2),
(HeunsMethodBuilder("y"), 2),
(RK3MethodBuilder("y"), 3),
(RK4MethodBuilder("y"), 4),
(RK5MethodBuilder("y"), 5),
(LSRK4MethodBuilder("y"), 4),
(KennedyCarpenterIMEXARK4MethodBuilder(
"y", use_implicit=False, explicit_rhs_name="y"), 4),
(SSPRK22MethodBuilder("y"), 2),
(SSPRK33MethodBuilder("y"), 3),
])
def test_leapgen_integration_order(method, method_order):
"""Test that time integrators have correct order."""
def exact_soln(t):
return np.exp(-t)
def rhs(t, y):
return -np.exp(-t)
def main(ctx_factory=cl.create_some_context,
use_logmgr=True,
use_leap=False,
use_profiling=False,
casename=None,
rst_filename=None,
actx_class=PyOpenCLArrayContext):
"""Drive example."""
cl_ctx = ctx_factory()
if casename is None:
casename = "mirgecom"
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nproc = comm.Get_size()
logmgr = initialize_logmgr(use_logmgr,
filename=f"{casename}.sqlite",
mode="wu",
mpi_comm=comm)
if use_profiling:
queue = cl.CommandQueue(
cl_ctx, properties=cl.command_queue_properties.PROFILING_ENABLE)
else:
queue = cl.CommandQueue(cl_ctx)
actx = actx_class(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
# Some discretization parameters
dim = 2
nel_1d = 8
order = 1
# {{{ Time stepping control
# This example runs only 3 steps by default (to keep CI ~short)
# With the mixture defined below, equilibrium is achieved at ~40ms
# To run to equlibrium, set t_final >= 40ms.
# Time stepper selection
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
# Time loop control parameters
current_step = 0
t_final = 1e-8
current_cfl = 1.0
current_dt = 1e-9
current_t = 0
constant_cfl = False
# i.o frequencies
nstatus = 1
nviz = 5
nhealth = 1
nrestart = 5
# }}} Time stepping control
debug = False
rst_path = "restart_data/"
rst_pattern = (rst_path + "{cname}-{step:04d}-{rank:04d}.pkl")
if rst_filename: # read the grid from restart data
rst_filename = f"{rst_filename}-{rank:04d}.pkl"
from mirgecom.restart import read_restart_data
restart_data = read_restart_data(actx, rst_filename)
local_mesh = restart_data["local_mesh"]
local_nelements = local_mesh.nelements
global_nelements = restart_data["global_nelements"]
assert restart_data["num_parts"] == nproc
rst_time = restart_data["t"]
rst_step = restart_data["step"]
rst_order = restart_data["order"]
else: # generate the grid from scratch
from meshmode.mesh.generation import generate_regular_rect_mesh
box_ll = -0.005
box_ur = 0.005
generate_mesh = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
local_mesh, global_nelements = generate_and_distribute_mesh(
comm, generate_mesh)
local_nelements = local_mesh.nelements
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(actx, discr.nodes())
vis_timer = None
if logmgr:
logmgr_add_device_name(logmgr, queue)
logmgr_add_device_memory_usage(logmgr, queue)
logmgr_add_many_discretization_quantities(logmgr, discr, dim,
extract_vars_for_logging,
units_for_logging)
vis_timer = IntervalTimer("t_vis", "Time spent visualizing")
logmgr.add_quantity(vis_timer)
logmgr.add_watches([
("step.max", "step = {value}, "),
("t_sim.max", "sim time: {value:1.6e} s\n"),
("min_pressure", "------- P (min, max) (Pa) = ({value:1.9e}, "),
("max_pressure", "{value:1.9e})\n"),
("min_temperature", "------- T (min, max) (K) = ({value:7g}, "),
("max_temperature", "{value:7g})\n"),
("t_step.max", "------- step walltime: {value:6g} s, "),
("t_log.max", "log walltime: {value:6g} s")
])
# {{{ Set up initial state using Cantera
# Use Cantera for initialization
# -- Pick up a CTI for the thermochemistry config
# --- Note: Users may add their own CTI file by dropping it into
# --- mirgecom/mechanisms alongside the other CTI files.
from mirgecom.mechanisms import get_mechanism_cti
mech_cti = get_mechanism_cti("uiuc")
cantera_soln = cantera.Solution(phase_id="gas", source=mech_cti)
nspecies = cantera_soln.n_species
# Initial temperature, pressure, and mixutre mole fractions are needed to
# set up the initial state in Cantera.
init_temperature = 1500.0 # Initial temperature hot enough to burn
# Parameters for calculating the amounts of fuel, oxidizer, and inert species
equiv_ratio = 1.0
ox_di_ratio = 0.21
stoich_ratio = 3.0
# Grab the array indices for the specific species, ethylene, oxygen, and nitrogen
i_fu = cantera_soln.species_index("C2H4")
i_ox = cantera_soln.species_index("O2")
i_di = cantera_soln.species_index("N2")
x = np.zeros(nspecies)
# Set the species mole fractions according to our desired fuel/air mixture
x[i_fu] = (ox_di_ratio * equiv_ratio) / (stoich_ratio +
ox_di_ratio * equiv_ratio)
x[i_ox] = stoich_ratio * x[i_fu] / equiv_ratio
x[i_di] = (1.0 - ox_di_ratio) * x[i_ox] / ox_di_ratio
# Uncomment next line to make pylint fail when it can't find cantera.one_atm
one_atm = cantera.one_atm # pylint: disable=no-member
# one_atm = 101325.0
# Let the user know about how Cantera is being initilized
print(f"Input state (T,P,X) = ({init_temperature}, {one_atm}, {x}")
# Set Cantera internal gas temperature, pressure, and mole fractios
cantera_soln.TPX = init_temperature, one_atm, x
# Pull temperature, total density, mass fractions, and pressure from Cantera
# We need total density, and mass fractions to initialize the fluid/gas state.
can_t, can_rho, can_y = cantera_soln.TDY
can_p = cantera_soln.P
# *can_t*, *can_p* should not differ (significantly) from user's initial data,
# but we want to ensure that we use exactly the same starting point as Cantera,
# so we use Cantera's version of these data.
# }}}
# {{{ Create Pyrometheus thermochemistry object & EOS
# Create a Pyrometheus EOS with the Cantera soln. Pyrometheus uses Cantera and
# generates a set of methods to calculate chemothermomechanical properties and
# states for this particular mechanism.
pyrometheus_mechanism = pyro.get_thermochem_class(cantera_soln)(actx.np)
eos = PyrometheusMixture(pyrometheus_mechanism,
temperature_guess=init_temperature)
# }}}
# {{{ MIRGE-Com state initialization
# Initialize the fluid/gas state with Cantera-consistent data:
# (density, pressure, temperature, mass_fractions)
print(f"Cantera state (rho,T,P,Y) = ({can_rho}, {can_t}, {can_p}, {can_y}")
velocity = np.zeros(shape=(dim, ))
initializer = MixtureInitializer(dim=dim,
nspecies=nspecies,
pressure=can_p,
temperature=can_t,
massfractions=can_y,
velocity=velocity)
my_boundary = AdiabaticSlipBoundary()
boundaries = {BTAG_ALL: my_boundary}
if rst_filename:
current_step = rst_step
current_t = rst_time
if logmgr:
from mirgecom.logging_quantities import logmgr_set_time
logmgr_set_time(logmgr, current_step, current_t)
if order == rst_order:
current_state = restart_data["state"]
else:
rst_state = restart_data["state"]
old_discr = EagerDGDiscretization(actx,
local_mesh,
order=rst_order,
mpi_communicator=comm)
from meshmode.discretization.connection import make_same_mesh_connection
connection = make_same_mesh_connection(
actx, discr.discr_from_dd("vol"),
old_discr.discr_from_dd("vol"))
current_state = connection(rst_state)
else:
# Set the current state from time 0
current_state = initializer(eos=eos, x_vec=nodes)
# Inspection at physics debugging time
if debug:
print("Initial MIRGE-Com state:")
print(f"{current_state=}")
print(f"Initial DV pressure: {eos.pressure(current_state)}")
print(f"Initial DV temperature: {eos.temperature(current_state)}")
# }}}
visualizer = make_visualizer(discr)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
# Cantera equilibrate calculates the expected end state @ chemical equilibrium
# i.e. the expected state after all reactions
cantera_soln.equilibrate("UV")
eq_temperature, eq_density, eq_mass_fractions = cantera_soln.TDY
eq_pressure = cantera_soln.P
# Report the expected final state to the user
if rank == 0:
logger.info(init_message)
logger.info(f"Expected equilibrium state:"
f" {eq_pressure=}, {eq_temperature=},"
f" {eq_density=}, {eq_mass_fractions=}")
def my_write_status(dt, cfl):
status_msg = f"------ {dt=}" if constant_cfl else f"----- {cfl=}"
if rank == 0:
logger.info(status_msg)
def my_write_viz(step,
t,
dt,
state,
ts_field=None,
dv=None,
production_rates=None,
cfl=None):
if dv is None:
dv = eos.dependent_vars(state)
if production_rates is None:
production_rates = eos.get_production_rates(state)
if ts_field is None:
ts_field, cfl, dt = my_get_timestep(t=t, dt=dt, state=state)
viz_fields = [("cv", state), ("dv", dv),
("production_rates", production_rates),
("dt" if constant_cfl else "cfl", ts_field)]
write_visfile(discr,
viz_fields,
visualizer,
vizname=casename,
step=step,
t=t,
overwrite=True,
vis_timer=vis_timer)
def my_write_restart(step, t, state):
rst_fname = rst_pattern.format(cname=casename, step=step, rank=rank)
if rst_fname == rst_filename:
if rank == 0:
logger.info("Skipping overwrite of restart file.")
else:
rst_data = {
"local_mesh": local_mesh,
"state": state,
"t": t,
"step": step,
"order": order,
"global_nelements": global_nelements,
"num_parts": nproc
}
from mirgecom.restart import write_restart_file
write_restart_file(actx, rst_data, rst_fname, comm)
def my_health_check(dv):
health_error = False
from mirgecom.simutil import check_naninf_local, check_range_local
if check_naninf_local(discr, "vol", dv.pressure) \
or check_range_local(discr, "vol", dv.pressure, 1e5, 2.4e5):
health_error = True
logger.info(f"{rank=}: Invalid pressure data found.")
if check_range_local(discr, "vol", dv.temperature, 1.498e3, 1.52e3):
health_error = True
logger.info(f"{rank=}: Invalid temperature data found.")
return health_error
def my_get_timestep(t, dt, state):
# richer interface to calculate {dt,cfl} returns node-local estimates
t_remaining = max(0, t_final - t)
if constant_cfl:
from mirgecom.inviscid import get_inviscid_timestep
ts_field = current_cfl * get_inviscid_timestep(
discr, eos=eos, cv=state)
from grudge.op import nodal_min
dt = nodal_min(discr, "vol", ts_field)
cfl = current_cfl
else:
from mirgecom.inviscid import get_inviscid_cfl
ts_field = get_inviscid_cfl(discr, eos=eos, dt=dt, cv=state)
from grudge.op import nodal_max
cfl = nodal_max(discr, "vol", ts_field)
return ts_field, cfl, min(t_remaining, dt)
def my_pre_step(step, t, dt, state):
try:
dv = None
if logmgr:
logmgr.tick_before()
from mirgecom.simutil import check_step
do_viz = check_step(step=step, interval=nviz)
do_restart = check_step(step=step, interval=nrestart)
do_health = check_step(step=step, interval=nhealth)
do_status = check_step(step=step, interval=nstatus)
if do_health:
dv = eos.dependent_vars(state)
from mirgecom.simutil import allsync
health_errors = allsync(my_health_check(dv), comm, op=MPI.LOR)
if health_errors:
if rank == 0:
logger.info("Fluid solution failed health check.")
raise MyRuntimeError("Failed simulation health check.")
ts_field, cfl, dt = my_get_timestep(t=t, dt=dt, state=state)
if do_status:
my_write_status(dt, cfl)
if do_restart:
my_write_restart(step=step, t=t, state=state)
if do_viz:
production_rates = eos.get_production_rates(state)
if dv is None:
dv = eos.dependent_vars(state)
my_write_viz(step=step,
t=t,
dt=dt,
state=state,
dv=dv,
production_rates=production_rates,
ts_field=ts_field,
cfl=cfl)
except MyRuntimeError:
if rank == 0:
logger.info("Errors detected; attempting graceful exit.")
my_write_viz(step=step, t=t, dt=dt, state=state)
my_write_restart(step=step, t=t, state=state)
raise
return state, dt
def my_post_step(step, t, dt, state):
# Logmgr needs to know about EOS, dt, dim?
# imo this is a design/scope flaw
if logmgr:
set_dt(logmgr, dt)
set_sim_state(logmgr, dim, state, eos)
logmgr.tick_after()
return state, dt
def my_rhs(t, state):
return (euler_operator(
discr, cv=state, time=t, boundaries=boundaries, eos=eos) +
eos.get_species_source_terms(state))
current_dt = get_sim_timestep(discr, current_state, current_t, current_dt,
current_cfl, eos, t_final, constant_cfl)
current_step, current_t, current_state = \
advance_state(rhs=my_rhs, timestepper=timestepper,
pre_step_callback=my_pre_step,
post_step_callback=my_post_step, dt=current_dt,
state=current_state, t=current_t, t_final=t_final)
# Dump the final data
if rank == 0:
logger.info("Checkpointing final state ...")
final_dv = eos.dependent_vars(current_state)
final_dm = eos.get_production_rates(current_state)
ts_field, cfl, dt = my_get_timestep(t=current_t,
dt=current_dt,
state=current_state)
my_write_viz(step=current_step,
t=current_t,
dt=dt,
state=current_state,
dv=final_dv,
production_rates=final_dm,
ts_field=ts_field,
cfl=cfl)
my_write_status(dt=dt, cfl=cfl)
my_write_restart(step=current_step, t=current_t, state=current_state)
if logmgr:
logmgr.close()
elif use_profiling:
print(actx.tabulate_profiling_data())
finish_tol = 1e-16
assert np.abs(current_t - t_final) < finish_tol
def main(ctx_factory=cl.create_some_context, use_leap=False):
"""Drive the example."""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
logger = logging.getLogger(__name__)
dim = 2
nel_1d = 16
order = 1
exittol = 2e-2
exittol = 100.0
t_final = 0.1
current_cfl = 1.0
vel = np.zeros(shape=(dim, ))
orig = np.zeros(shape=(dim, ))
# vel[:dim] = 1.0
current_dt = .01
current_t = 0
eos = IdealSingleGas()
initializer = Lump(dim=dim, center=orig, velocity=vel, rhoamp=0.0)
casename = "pulse"
boundaries = {BTAG_ALL: PrescribedBoundary(initializer)}
wall = AdiabaticSlipBoundary()
boundaries = {BTAG_ALL: wall}
constant_cfl = False
nstatus = 10
nviz = 10
rank = 0
checkpoint_t = current_t
current_step = 0
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
box_ll = -0.5
box_ur = 0.5
from mpi4py import MPI
comm = MPI.COMM_WORLD
nproc = comm.Get_size()
rank = comm.Get_rank()
num_parts = nproc
from meshmode.mesh.generation import generate_regular_rect_mesh
if num_parts > 1:
generate_mesh = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
local_mesh, global_nelements = generate_and_distribute_mesh(
comm, generate_mesh)
else:
local_mesh = generate_regular_rect_mesh(a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) *
dim)
global_nelements = local_mesh.nelements
local_nelements = local_mesh.nelements
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(actx, discr.nodes())
uniform_state = initializer(nodes)
acoustic_pulse = AcousticPulse(dim=dim,
amplitude=1.0,
width=.1,
center=orig)
current_state = acoustic_pulse(x_vec=nodes, cv=uniform_state, eos=eos)
visualizer = make_visualizer(discr)
initname = "pulse"
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
if rank == 0:
logger.info(init_message)
get_timestep = partial(inviscid_sim_timestep,
discr=discr,
t=current_t,
dt=current_dt,
cfl=current_cfl,
eos=eos,
t_final=t_final,
constant_cfl=constant_cfl)
def my_rhs(t, state):
return euler_operator(discr,
cv=state,
t=t,
boundaries=boundaries,
eos=eos)
def my_checkpoint(step, t, dt, state):
return sim_checkpoint(discr,
visualizer,
eos,
cv=state,
vizname=casename,
step=step,
t=t,
dt=dt,
nstatus=nstatus,
nviz=nviz,
exittol=exittol,
constant_cfl=constant_cfl,
comm=comm)
try:
(current_step, current_t, current_state) = \
advance_state(rhs=my_rhs, timestepper=timestepper,
checkpoint=my_checkpoint,
get_timestep=get_timestep, state=current_state,
t=current_t, t_final=t_final)
except ExactSolutionMismatch as ex:
current_step = ex.step
current_t = ex.t
current_state = ex.state
# if current_t != checkpoint_t:
if rank == 0:
logger.info("Checkpointing final state ...")
my_checkpoint(current_step,
t=current_t,
dt=(current_t - checkpoint_t),
state=current_state)
if current_t - t_final < 0:
raise ValueError("Simulation exited abnormally")
def main(ctx_factory=cl.create_some_context,
casename="autoignition",
use_leap=False,
restart_step=None,
restart_name=None):
"""Drive example."""
cl_ctx = ctx_factory()
queue = cl.CommandQueue(cl_ctx)
actx = PyOpenCLArrayContext(queue,
allocator=cl_tools.MemoryPool(
cl_tools.ImmediateAllocator(queue)))
dim = 2
nel_1d = 8
order = 1
# This example runs only 3 steps by default (to keep CI ~short)
# With the mixture defined below, equilibrium is achieved at ~40ms
# To run to equlibrium, set t_final >= 40ms.
t_final = 1e-8
current_cfl = 1.0
velocity = np.zeros(shape=(dim, ))
current_dt = 1e-9
current_t = 0
constant_cfl = False
nstatus = 1
nviz = 5
nrestart = 5
rank = 0
checkpoint_t = current_t
current_step = 0
if use_leap:
from leap.rk import RK4MethodBuilder
timestepper = RK4MethodBuilder("state")
else:
timestepper = rk4_step
box_ll = -0.005
box_ur = 0.005
error_state = False
debug = False
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
nproc = comm.Get_size()
restart_file_pattern = "{casename}-{step:04d}-{rank:04d}.pkl"
restart_path = "restart_data/"
if restart_step:
if not restart_name:
restart_name = casename
rst_filename = (restart_path + restart_file_pattern.format(
casename=restart_name, step=restart_step, rank=rank))
from mirgecom.restart import read_restart_data
restart_data = read_restart_data(actx, rst_filename)
local_mesh = restart_data["local_mesh"]
local_nelements = local_mesh.nelements
global_nelements = restart_data["global_nelements"]
assert restart_data["nparts"] == nproc
else:
from meshmode.mesh.generation import generate_regular_rect_mesh
generate_mesh = partial(generate_regular_rect_mesh,
a=(box_ll, ) * dim,
b=(box_ur, ) * dim,
nelements_per_axis=(nel_1d, ) * dim)
local_mesh, global_nelements = generate_and_distribute_mesh(
comm, generate_mesh)
local_nelements = local_mesh.nelements
discr = EagerDGDiscretization(actx,
local_mesh,
order=order,
mpi_communicator=comm)
nodes = thaw(actx, discr.nodes())
# {{{ Set up initial state using Cantera
# Use Cantera for initialization
# -- Pick up a CTI for the thermochemistry config
# --- Note: Users may add their own CTI file by dropping it into
# --- mirgecom/mechanisms alongside the other CTI files.
from mirgecom.mechanisms import get_mechanism_cti
mech_cti = get_mechanism_cti("uiuc")
cantera_soln = cantera.Solution(phase_id="gas", source=mech_cti)
nspecies = cantera_soln.n_species
# Initial temperature, pressure, and mixutre mole fractions are needed to
# set up the initial state in Cantera.
init_temperature = 1500.0 # Initial temperature hot enough to burn
# Parameters for calculating the amounts of fuel, oxidizer, and inert species
equiv_ratio = 1.0
ox_di_ratio = 0.21
stoich_ratio = 3.0
# Grab the array indices for the specific species, ethylene, oxygen, and nitrogen
i_fu = cantera_soln.species_index("C2H4")
i_ox = cantera_soln.species_index("O2")
i_di = cantera_soln.species_index("N2")
x = np.zeros(nspecies)
# Set the species mole fractions according to our desired fuel/air mixture
x[i_fu] = (ox_di_ratio * equiv_ratio) / (stoich_ratio +
ox_di_ratio * equiv_ratio)
x[i_ox] = stoich_ratio * x[i_fu] / equiv_ratio
x[i_di] = (1.0 - ox_di_ratio) * x[i_ox] / ox_di_ratio
# Uncomment next line to make pylint fail when it can't find cantera.one_atm
one_atm = cantera.one_atm # pylint: disable=no-member
# one_atm = 101325.0
# Let the user know about how Cantera is being initilized
print(f"Input state (T,P,X) = ({init_temperature}, {one_atm}, {x}")
# Set Cantera internal gas temperature, pressure, and mole fractios
cantera_soln.TPX = init_temperature, one_atm, x
# Pull temperature, total density, mass fractions, and pressure from Cantera
# We need total density, and mass fractions to initialize the fluid/gas state.
can_t, can_rho, can_y = cantera_soln.TDY
can_p = cantera_soln.P
# *can_t*, *can_p* should not differ (significantly) from user's initial data,
# but we want to ensure that we use exactly the same starting point as Cantera,
# so we use Cantera's version of these data.
# }}}
# {{{ Create Pyrometheus thermochemistry object & EOS
# Create a Pyrometheus EOS with the Cantera soln. Pyrometheus uses Cantera and
# generates a set of methods to calculate chemothermomechanical properties and
# states for this particular mechanism.
pyrometheus_mechanism = pyro.get_thermochem_class(cantera_soln)(actx.np)
eos = PyrometheusMixture(pyrometheus_mechanism,
temperature_guess=init_temperature)
# }}}
# {{{ MIRGE-Com state initialization
# Initialize the fluid/gas state with Cantera-consistent data:
# (density, pressure, temperature, mass_fractions)
print(f"Cantera state (rho,T,P,Y) = ({can_rho}, {can_t}, {can_p}, {can_y}")
initializer = MixtureInitializer(dim=dim,
nspecies=nspecies,
pressure=can_p,
temperature=can_t,
massfractions=can_y,
velocity=velocity)
my_boundary = AdiabaticSlipBoundary()
boundaries = {BTAG_ALL: my_boundary}
if restart_step:
current_t = restart_data["t"]
current_step = restart_step
current_state = restart_data["state"]
else:
# Set the current state from time 0
current_state = initializer(eos=eos, x_vec=nodes, t=0)
# Inspection at physics debugging time
if debug:
print("Initial MIRGE-Com state:")
print(f"{current_state=}")
print(f"Initial DV pressure: {eos.pressure(current_state)}")
print(f"Initial DV temperature: {eos.temperature(current_state)}")
# }}}
visualizer = make_visualizer(discr)
initname = initializer.__class__.__name__
eosname = eos.__class__.__name__
init_message = make_init_message(dim=dim,
order=order,
nelements=local_nelements,
global_nelements=global_nelements,
dt=current_dt,
t_final=t_final,
nstatus=nstatus,
nviz=nviz,
cfl=current_cfl,
constant_cfl=constant_cfl,
initname=initname,
eosname=eosname,
casename=casename)
# Cantera equilibrate calculates the expected end state @ chemical equilibrium
# i.e. the expected state after all reactions
cantera_soln.equilibrate("UV")
eq_temperature, eq_density, eq_mass_fractions = cantera_soln.TDY
eq_pressure = cantera_soln.P
# Report the expected final state to the user
if rank == 0:
logger.info(init_message)
logger.info(f"Expected equilibrium state:"
f" {eq_pressure=}, {eq_temperature=},"
f" {eq_density=}, {eq_mass_fractions=}")
get_timestep = partial(inviscid_sim_timestep,
discr=discr,
t=current_t,
dt=current_dt,
cfl=current_cfl,
eos=eos,
t_final=t_final,
constant_cfl=constant_cfl)
def my_rhs(t, state):
return (euler_operator(
discr, cv=state, t=t, boundaries=boundaries, eos=eos) +
eos.get_species_source_terms(state))
def my_checkpoint(step, t, dt, state):
if check_step(step, nrestart) and step != restart_step:
rst_filename = (restart_path + restart_file_pattern.format(
casename=casename, step=step, rank=rank))
rst_data = {
"local_mesh": local_mesh,
"state": current_state,
"t": t,
"step": step,
"global_nelements": global_nelements,
"num_parts": nproc
}
from mirgecom.restart import write_restart_file
write_restart_file(actx, rst_data, rst_filename, comm)
# awful - computes potentially expensive viz quantities
# regardless of whether it is time to viz
reaction_rates = eos.get_production_rates(state)
viz_fields = [("reaction_rates", reaction_rates)]
return sim_checkpoint(discr,
visualizer,
eos,
cv=state,
vizname=casename,
step=step,
t=t,
dt=dt,
nstatus=nstatus,
nviz=nviz,
constant_cfl=constant_cfl,
comm=comm,
viz_fields=viz_fields)
try:
(current_step, current_t, current_state) = \
advance_state(rhs=my_rhs, timestepper=timestepper,
checkpoint=my_checkpoint,
get_timestep=get_timestep, state=current_state,
t=current_t, t_final=t_final)
except ExactSolutionMismatch as ex:
error_state = True
current_step = ex.step
current_t = ex.t
current_state = ex.state
if not check_step(current_step, nviz): # If final step not an output step
if rank == 0:
logger.info("Checkpointing final state ...")
my_checkpoint(current_step,
t=current_t,
dt=(current_t - checkpoint_t),
state=current_state)
if current_t - t_final < 0:
error_state = True
if error_state:
raise ValueError("Simulation did not complete successfully.")