PeleLMeX controls
The input file specified on the command line is a free-format text file, one entry per row, that specifies input data processed by the AMReX ParmParse module.
This file needs to specified along with the executable as an argv option, for example:
mpirun -np 64 ./PeleLMeX2d.xxx.ex inputs
Also, any entry that can be specified in the inputs file can also be specified on the command line; values specified on the command line override values in the inputs file, e.g.:
mpirun -np 64 ./PeleLMeX2d.xxx.ex inputs amr.max_level=2
The available options are divided into groups: those that control primarily AMReX are prefaced with amr., those that are specific to the PeleLMeX are prefaced by peleLM., while those corresponding to the various pieces of the algorithm are prefaced with specific keys, such that diffusion, nodal_proj, … as described below.
Computational domain definition
#--------------------GEOMETRY DEFINITION-----------------------
geometry.is_periodic = 1 1 0 # For each dir, 0: non-perio, 1: periodic
geometry.coord_sys = 0 # 0 => cart, 1 => RZ
geometry.prob_lo = 0.0 0.0 0.0 # x_lo y_lo (z_lo)
geometry.prob_hi = 0.016 0.016 0.032 # x_hi y_hi (z_hi)
#-----------------------BNDY CONDITIONS------------------------
# Interior, Inflow, Outflow, Symmetry, SlipWallAdiab, NoSlipWallAdiab
# SlipWallIsotherm, NoSlipWallIsotherm
# Periodic direction must be set as Interior
peleLM.lo_bc = Interior Interior Inflow
peleLM.hi_bc = Interior Interior Inflow
If specifying boundaries as Inflow, the bcnormal function must be defined
in the pelelmex_prob.H file for the case to define the inflow conditions.
Inflow boundaries may also be augmented with spatially and temporally
varying turbulent fluctuations using the TurbInflow utility from
PelePhysics. See the Exec/RegTests/TurbInflow test for an example of how
to use this capability and the
PelePhysics documentation
for the relevant input file flags.
Grid/AMR parameters
#-------------------------AMR CONTROL--------------------------
amr.n_cell = 64 64 128 # Number of cells on Level 0 in each direction
amr.v = 1 # [OPT, DEF=0] AMR verbose
amr.max_level = 1 # maximum level number allowed
amr.ref_ratio = 2 2 2 2 # refinement ratio, one per refinement level
amr.regrid_int = 5 # how often to regrid
amr.n_error_buf = 1 1 2 2 # number of buffer cells in error est, one per refinement level
amr.grid_eff = 0.7 # what constitutes an efficient grid
amr.blocking_factor = 16 # block factor in grid generation (min box size)
amr.max_grid_size = 64 # max box size
peleLM.max_grid_size_chem = 32 # [OPT, DEF="None"] Max box size for the Chemistry BoxArray
Load balancing
PeleLMeX relies on two distribution maps (see Source code for more details).
peleLM.do_load_balancing = 1 # [OPT, DEF=0] Activate load balancing
peleLM.load_balancing_method = sfc # [OPT, DEF="sfc"] AmrCore dmap load balancing method
peleLM.load_balancing_cost_estimate = ncell # [OPT, DEF="ncell"] AmrCore dmap balancing cost
peleLM.chem_load_balancing_method = knapsack # [OPT, DEF="knapsack"] Chemistry dmap load balancing method
peleLM.chem_load_balancing_cost_estimate = chemfunctcall_sum # [OPT, DEF="chemfunctcall_sum"] Chemistry dmap balancing cost
peleLM.load_balancing_efficiency_threshold = 1.05 # What constitute a better dmap ?
The balancing method can be one of sfc, roundrobin or knapsack, while the cost estimate can be one of ncell, chemfunctcall_avg, chemfunctcall_max, chemfunctcall_sum, userdefined_avg or userdefined_sum. When using either of the last to option, the user must provide a definition for the derUserDefined. If multiple components are defined in the derUserDefined function, the first one is used for load balancing.
Time stepping parameters
#-------------------------TIME STEPPING------------------------
amr.max_step = 20 # Maximum number of steps
amr.stop_time = 0.001 # Maximum simulation time [s]
amr.max_wall_time = 1.0 # Maximum wall clock time [hr]
amr.cfl = 0.5 # [OPT, DEF=0.7] CFL for advection-controlled dt estimate
amr.fixed_dt = 1e-6 # [OPT] optional fixed dt (override CFL condition)
amr.min_dt = 1e-11 # [OPT, DEF=1e-12] small time step size limit triggering simulation termination
amr.init_dt = 1e-6 # [OPT] optional initial dt (override CFL condition upon initialization)
amr.dt_shrink = 0.0001 # [OPT, DEF=1.0] dt factor upon initialization
amr.dt_change_max = 1.1 # [OPT, DEF=1.1] maximum dt change between consecutive steps
Note
Note that one of amr.max_step, amr.stop_time, or amr.max_wall_time is required, and if more than one is specified, the first stopping criterion encountered will lead to termination of the simulation.
IO parameters
#--------------------------IO CONTROL--------------------------
amr.plot_int = 20 # [OPT, DEF=-1] Frequency (as step #) for writing plot file
amr.plot_per = 0.002 # [OPT, DEF=-1] Period (time in s) for writing plot file
amr.plot_per_exact = 1 # [OPT, DEF=0] Flag to enforce exactly plt_per by shortening dt
amr.plot_file = "plt_" # [OPT, DEF="plt_"] Plot file prefix
amr.check_int = 100 # [OPT, DEF=-1] Frequency (as step #) for writing checkpoint file
amr.check_per = 0.05 # [OPT, DEF=-1] Period (time in s) for writing checkpoint file
amr.check_file = "chk" # [OPT, DEF="chk"] Checkpoint file prefix
amr.file_stepDigits = 6 # [OPT, DEF=5] Number of digits when adding nsteps to plt and chk names
amr.derive_plot_vars = avg_pressure ...# [OPT, DEF=""] List of derived variable included in the plot files
amr.plot_speciesState = 0 # [OPT, DEF=0] Force adding state rhoYs to the plot files
amr.restart = chk00100 # [OPT, DEF=""] Checkpoint from which to restart the simulation
amr.initDataPlt = plt01000 # [OPT, DEF=""] Provide a plotfile from which to extract initial data
amr.regrid_on_restart = 1 # [OPT, DEF="0"] Trigger a regrid after the data from checkpoint are loaded
amr.n_files = 64 # [OPT, DEF="min(256,NProcs)"] Number of files to write per level
Refinement controls
Refinement in PeleLMeX is controlled by a set of ‘Tagging’ criterion listed under the amr.refinement_indicators key. For each criteriq, the user needs to supply a definition. For example, the following provides a complete overview of the available controls:
amr.refinement_indicators gthan lthan adjd box1
amr.gthan.max_level = 3
amr.gthan.value_greater = 0.005
amr.gthan.field_name = x_velocity
amr.lthan.max_level = 4
amr.lthan.value_less = 400.0
amr.lthan.field_name = temp
amr.lthan.start_time = 0.001
amr.lthan.end_time = 0.005
amr.adjd.max_level = 2
amr.adjd.adjacent_difference_greater = 0.05
amr.adjd.field_name = density
amr.box1.max_level = 1
amr.box1.in_box_lo = 0.0 0.0 0.0
amr.box1.in_box_hi = 0.01 0.01 0.05
The field_name can be any of the state or derived variables (see below) component. Additional controls specific to embedded boundaries are discussed below.
PeleLMeX derived variables
The following list of derived variables are available in PeleLMeX:
Key |
Size (nComp) |
Brief |
|---|---|---|
mass_fractions |
NUM_SPECIES |
Species mass fractions |
mole_fractions |
NUM_SPECIES |
Species mole fractions |
diffcoeff |
NUM_SPECIES |
Species mixture-averaged diffusion coefficients |
lambda |
1 |
Thermal diffusivity |
viscosity |
1 |
Mixture viscosity |
mixture_fraction |
1 |
Mixture fraction based on Bilger’s element formulation |
progress_variable |
1 |
Progress variable based on a linear combination of Ys, T |
avg_pressure |
1 |
Cell-averaged pressure (from the node-centered pressure) |
mag_vort |
1 |
Vorticity magnitude |
vorticity |
AMREX_SPACEDIM*2-3 |
VortZ (2D) or VortX, VortY, VortZ (3D) |
Qcrit |
1 |
Q-Criterion : \(0.5(|\boldsymbol{\Omega}|^2 - |\boldsymbol{S}|^2)\) |
kinetic_energy |
1 |
Kinetic energy: 0.5 * rho * (u^2+v^2+w^2) |
enstrophy |
1 |
enstrophy: 0.5 * rho * (omega_x^2+omega_y^2+omega_z^2) |
HeatRelease |
1 |
Heat release rate from chem. reactions |
rhominsumrhoY |
1 |
Rho minus sum of rhoYs, for debug purposes |
coordinates |
AMREX_SPACEDIM |
Cell-center coordinates |
DistributionMap |
1 |
The MPI-rank of each box |
derUserDefined |
? |
A user-defined derived which number of components is provided by the user (see below). |
Note that mixture_fraction and progress_variable requires additional inputs from the users as described below. The derUserDefined allow the user to define its own derived variable which can comprise several components. To do so, the user need to copy the Source/DeriveUserDefined.cpp file into his run folder and update the file. The number of components is defined based on the size of the vector returned by pelelmex_setuserderives().
PeleLMeX algorithm
#-----------------------PELE CONTROL-----------------------
peleLM.v = 1 # [OPT, DEF=0] Verbose
peleLM.run_mode = normal # [OPT, DEF=normal] Switch between time-advance mode (normal) or UnitTest (evaluate)
peleLM.use_wbar = 1 # [OPT, DEF=1] Enable Wbar correction in diffusion fluxes
peleLM.sdc_iterMax = 2 # [OPT, DEF=1] Number of SDC iterations
peleLM.num_init_iter = 2 # [OPT, DEF=3] Number of iterations to get initial pressure
peleLM.num_divu_iter = 1 # [OPT, DEF=1] Number of divU iterations to get initial dt estimate
peleLM.do_init_proj = 1 # [OPT, DEF=1] Control over initial projection
peleLM.advection_scheme = Godunov_BDS # [OPT, DEF=Godunov_PLM] Advection scheme: Godunov_PLM, Godunov_PPM or Godunov_BDS
peleLM.incompressible = 0 # [OPT, DEF=0] Enable to run fully incompressible, scalar advance is bypassed
peleLM.m_rho = 1.17 # [OPT, DEF=-1] If incompressible, density value [MKS]
peleLM.m_mu = 1.8e-5 # [OPT, DEF=-1] If incompressible, kinematic visc. value [MKS]
peleLM.gravity = 0.0 0.0 -9.81 # [OPT, DEF=Vec{0.0}] Gravity vector [MKS]
peleLM.gradP0 = 0.0 0.0 10.0 # [OPT, DEF=Vec{0.0}] Average background pressure gradient [Pa/m]
peleLM.do_periodic_channel = 0 # [OPT, DEF= 0] Add an automatic pressure gradient to maintain initial condition mass flow rate in periodic channel
peleLM.periodic_channel_dir = 2 # [OPT, DEF= -1] Required if do_periodic_channel != 0. Direction to apply pressure gradient.
peleLM.closed_chamber = 0 # [OPT] Override the automatic detection of closed chamber (based on Outflow(s))
peleLM.floor_species = 0 # [OPT, DEF=0] Crudely enforce mass fraction positivity
peleLM.deltaT_verbose = 0 # [OPT, DEF=0] Verbose of the deltaT iterative solve algorithm
peleLM.deltaT_iterMax = 5 # [OPT, DEF=10] Maximum number of deltaT iterations
peleLM.deltaT_tol = 1e-10 # [OPT, DEF=1.e-10] Tolerance of the deltaT solve
peleLM.evaluate_vars =... # [OPT, DEF=""] In evaluate mode, list unitTest: diffTerm, divU, instRR, transportCC
Transport coeffs and LES
#-----------------------DIFFUSION AND LES MODEL CONTROL-----------------------
peleLM.fixed_Le = 0 # [OPT, DEF=0] Use a fixed Lewis number approximation for species diffusivities
peleLM.fixed_Pr = 0 # [OPT, DEF=0] Use a fixed Prandtl number approximation for thermal diffusivity
peleLM.Prandtl = 0.7 # [OPT, DEF=0.7] If fixed_Pr or doing LES, specifies the Prandtl number
peleLM.Schmidt = 0.7 # [OPT, DEF=0.7] If doing LES, specifies the Schmidt number
peleLM.Lewis = 1.0 # [OPT, DEF=1.0] If fixed_Le, specifies the Lewis number
peleLM.les_model = "None" # [OPT, DEF="None"] Model to compute turbulent viscosity: None, Smagorinsky, WALE, Sigma
peleLM.les_cs_smag = 0.18 # [OPT, DEF=0.18] If using Smagorinsky LES model, provides model coefficient
peleLM.les_cm_wale = 0.60 # [OPT, DEF=0.60] If using WALE LES model, provides model coefficient
peleLM.les_cs_sigma = 1.35 # [OPT, DEF=1.35] If using Sigma LES model, provides model coefficient
peleLM.les_v = 0 # [OPT, DEF=0] Verbosity level for LES model
peleLM.plot_les = 0 # [OPT, DEF=0] If doing LES, whether to plot the turbulent viscosity
Chemistry integrator
#-----------------------CHEMISTRY CONTROL----------------------
peleLM.chem_integrator = "ReactorCvode" # Chemistry integrator, from PelePhysics available list
peleLM.use_typ_vals_chem = 1 # [OPT, DEF=1] Use Typical values to scale components in the reactors
peleLM.typical_values_reset_int = 5 # [OPT, DEF=10] Frequency at which the typical values are updated
ode.rtol = 1.0e-6 # [OPT, DEF=1e-10] Relative tolerance of the chem. reactor
ode.atol = 1.0e-6 # [OPT, DEF=1e-10] Absolute tolerance of the chem. reactor, or pre-factor of the typical values when used
cvode.solve_type = denseAJ_direct # [OPT, DEF=GMRES] Linear solver employed for CVODE Newton direction
cvode.max_order = 4 # [OPT, DEF=2] Maximum order of the BDF method in CVODE
cvode.max_substeps = 10000 # [OPT, DEF=10000] Maximum number of substeps for the linear solver in CVODE
Note that the last five parameters belong to the Reactor class of PelePhysics but are specified here for completeness. In particular, CVODE is the adequate choice of integrator to tackle PeleLMeX large time step sizes. Several linear solvers are available depending on whether or not GPU are employed: on CPU, dense_direct is a finite-difference direct solver, denseAJ_direct is an analytical-jacobian direct solver (preferred choice), sparse_direct is an analytical-jacobian sparse direct solver based on the KLU library and GMRES is a matrix-free iterative solver; on GPU GMRES is a matrix-free iterative solver (available on all the platforms), sparse_direct is a batched block-sparse direct solve based on NVIDIA’s cuSparse (only with CUDA), magma_direct is a batched block-dense direct solve based on the MAGMA library (available with CUDA and HIP. Different cvode.solve_type should be tried before increasing the cvode.max_substeps.
Embedded Geometry
PeleLMeX geometry relies on AMReX implementation of the EB method. Simple geometrical objects can thus be constructed using AMReX internal parser. For instance, setting up a sphere of radius 5 mm can be achieved:
eb2.geom_type = sphere
eb2.sphere_radius = 0.005
eb2.sphere_center = 0.0 0.0 0.0
eb2.sphere_has_fluid_inside = 0
eb2.small_volfrac = 1.0e-4
eb2.maxiter = 200
The eb2.small_volfrac controls volume fraction that are deemed too small and eliminated from the EB representation. This operation is done iteratively and the maximum number of iteration is prescribed by eb2.maxiter. For most applications, a single AMReX object is insufficient to represent the geometry. AMReX enable to combine objects using constructive solid geometry (CSG) in order to create complex geometry. It is up to users to define the combination of basic elements leading to their desired geometry. To switch to a user-defined EB definition, one must set:
eb2.geom_type = UserDefined
and then implement the actual geometry definition in a EBUserDefined.H file located in the run folder (and add
to the GNUmakefile using CEXE_headers += EBUserDefined.H). An example of such implementation is available in the
Exec/Case/ChallengeProblem folder. Example of more generic EB problems are also found in the Exec/RegTest/EB_*
folders.
In addition to the input keys presented above, a set of PeleLMeX-specific keys are available in order to control refinement at the EB:
peleLM.refine_EB_type = Static
peleLM.refine_EB_max_level = 1
peleLM.refine_EB_buffer = 2.0
By default, the EB is refined to the amr.max_level, which can lead to undesirably high number of cells close to the EB when the physics of interest might be elsewhere. The above lines enable to limit the EB-level to level 1 (must be below amr.max_level) and a derefinement strategy is adopted to ensure that fine-grid patches do not cross the EB boundary. The last parameter set a safety margin to increase how far the derefinement is applied in order to account for grid-patches diagonals and proper nesting constrains. Note that the parameter do not ensure explicitly coarse-fine/EB crossings are avoided and the code will fail when this happens.
It is also possible to change the default adiabatic EB wall condition to an isothermal EB. To do so, one need to switch the following flag:
peleLM.isothermal_EB = 1
The user is now responsible for providing the wall temperature on all the EB walls, but adiabtic wall can still be specified.
Control over the local EB thermal boundary condition is provided through the setEBState and setEBType functions, also
defined in the EBUserDefined.H already used above to provide a user-defined EB geometry. Example of isothermal EBs are provided
in Exec/RegTest/EB_BackwardStepFlame and Exec/RegTest/EB_FlowPastCylinder tests.
Note
Note that when using isothermal EB in combination with LES, the thermal diffusion coefficient employed to compute the EB boundary thermal flux only uses the molecular contribution.
Linear solvers
Linear solvers are a key component of PeleLMeX algorithm, separate controls are dedicated to the various solver (MAC projection, nodal projection, diffusion, …)
#-------------------------LINEAR SOLVERS-----------------------
nodal_proj.verbose = 1 # [OPT, DEF=0] Verbose of the nodal projector
nodal_proj.rtol = 1.0e-11 # [OPT, DEF=1e-11] Relative tolerance of the nodal projection
nodal_proj.atol = 1.0e-12 # [OPT, DEF=1e-14] Absolute tolerance of the nodal projection
nodal_proj.mg_max_coarsening_level = 5 # [OPT, DEF=100] Maximum number of MG levels (useful when using EB)
mac_proj.verbose = 1 # [OPT, DEF=0] Verbose of the MAC projector
mac_proj.rtol = 1.0e-11 # [OPT, DEF=1e-11] Relative tolerance of the MAC projection
mac_proj.atol = 1.0e-12 # [OPT, DEF=1e-14] Absolute tolerance of the MAC projection
mac_proj.mg_max_coarsening_level = 5 # [OPT, DEF=100] Maximum number of MG levels (useful when using EB)
diffusion.verbose = 1 # [OPT, DEF=0] Verbose of the scalar diffusion solve
diffusion.rtol = 1.0e-11 # [OPT, DEF=1e-11] Relative tolerance of the scalar diffusion solve
diffusion.atol = 1.0e-12 # [OPT, DEF=1e-14] Absolute tolerance of the scalar diffusion solve
tensor_diffusion.verbose = 1 # [OPT, DEF=0] Verbose of the velocity tensor diffusion solve
tensor_diffusion.rtol = 1.0e-11 # [OPT, DEF=1e-11] Relative tolerance of the velocity tensor diffusion solve
tensor_diffusion.atol = 1.0e-12 # [OPT, DEF=1e-14] Absolute tolerance of the velocity tensor diffusion solve
Active control
PeleLMeX includes an active control mechanism to enable statistically steady simulations of flames maintaining the flame at a fixed position in the domain. An example of this feature is provided in the triple flame tutorial A simple triple flame.
Note
To enable active control, a FlowControllerData FCData object must be added to the problem ProbParm!
During the course of the simulation, the FlowControllerData is updated based on the flame position to allow the user to set the inflow velocity. The following options are available when using active control:
#---------------------- AC CONTROL -------------------------------
active_control.on = 1 # [OPT, DEF=0] Use AC ?
active_control.use_temp = 1 # [OPT, DEF=1] Default in fuel mass, rather use iso-T position ?
active_control.temperature = 1400.0 # [OPT, DEF=-1] Value of iso-T ?
active_control.tau = 5.0e-4 # [OPT, DEF=0.0] Control tau (should ~ 10 dt)
active_control.height = 0.01 # [OPT, DEF=0.0] Where is the flame held ?
active_control.v = 1 # [OPT, DEF=0] verbose
active_control.method = 1 # [OPT, DEF=2] Controller: 1 - Linear, 2 - Quadratic, 3 - Weighted quadratic
active_control.velMax = 2.0 # [OPT, DEF=-1.0] limit inlet velocity, only used when positive
active_control.changeMax = 0.1 # [OPT, DEF=1.0] limit inlet velocity changes (absolute m/s)
active_control.flow_dir = 1 # [OPT, DEF=AMREX_SPACEDIM-1] flame main direction
active_control.AC_history = AChist # [OPT, DEF=AC_history] Control history file, read upon restart
active_control.npoints_average = 5 # [OPT, DEF=3] Number of previous steps using to estimate new velocity
active_control.pseudo_gravity = 1 # [OPT, DEF=0] add density proportional force to compensate for the acceleration
# of the gas due to inlet velocity changes
Run-time diagnostics
PeleLMeX provides a few diagnostics to check you simulations while it is running as well as adding basic analysis ingredients.
It is often useful to have an estimate of integrated quantities (kinetic energy, heat release rate, ,..), state extremas or other overall balance information to get a sense of the status and sanity of the simulation. To this end, it is possible to activate temporal diagnostics performing these reductions at given intervals:
#-------------------------TEMPORALS---------------------------
peleLM.do_temporals = 1 # [OPT, DEF=0] Activate temporal diagnostics
peleLM.temporal_int = 10 # [OPT, DEF=5] Temporal freq.
peleLM.do_extremas = 1 # [OPT, DEF=0] Trigger extremas, if temporals activated
peleLM.do_mass_balance = 1 # [OPT, DEF=0] Compute mass balance, if temporals activated
peleLM.do_species_balance = 1 # [OPT, DEF=0] Compute species mass balance, if temporals activated
peleLM.do_patch_mfr=1 # [OPT, DEF=0] Activate patch based species flux diagbostics
peleLM.bpatch.patchnames= <patch_name1 patch_name2 ..> # List of patchnames
bpatch.patch_name1.patchtype=full-boundary # patchtype one of "full-boundary", "circle, "rectangle", "circle-annular" or "rectangle-annular"
bpatch.patch_name1.boundary_direction=2 # patch normal direction
bpatch.patch_name1.boundary_lo_or_hi=0 # patch in low or high side of boundary
bpatch.patch_name1.species= O2 N2 # list of species names
bpatch.patch_name2.patchtype=circle # patchtype one of "full-boundary", "circle, "rectangle", "circle-annular" or "rectangle-annular"
bpatch.patch_name2.boundary_direction=2 # patch normal direction
bpatch.patch_name2.boundary_lo_or_hi=0 # patch in low or high side of boundary
bpatch.patch_name2.patch_circle_radius=0.1 # radius of the patch
bpatch.patch_name2.patch_circle_center=0.0 0.0 0.0 # coordinates of patch center
bpatch.patch_name2.species= O2 N2 # list of species names
bpatch.patch_name3.patchtype=rectangle
bpatch.patch_name3.boundary_direction=2 # patch normal direction
bpatch.patch_name3.boundary_lo_or_hi=0 # patch in low or high side of boundary
bpatch.patch_name3.patch_rectangle_lo=0.0 0.0 0.0 # coordinates of low corner of rectangle
bpatch.patch_name3.patch_rectangle_hi=1.0 1.0 1.0 # coordinates of high corner of rectangle
bpatch.patch_name3.species= O2 N2 # list of species names
bpatch.patch_name4.patchtype=circle-annular
bpatch.patch_name4.boundary_direction=2 # patch normal direction
bpatch.patch_name4.boundary_lo_or_hi=0 # patch in low or high side of boundary
bpatch.patch_name4.patch_circ_ann_center= 0.0 0.0 0.0 # center of annular circle
bpatch.patch_name4.patch_circ_ann_inner_radius=0.1 # coordinates of patch center
bpatch.patch_name4.patch_circ_ann_outer_radius=0.2 # coordinates of patch center
bpatch.patch_name4.species= O2 N2 # list of species names
bpatch.patch_name5.patchtype=rectangle-annular
bpatch.patch_name5.boundary_direction=2 # patch normal direction
bpatch.patch_name5.boundary_lo_or_hi=0 # patch in low or high side of boundary
bpatch.patch_name5.patch_rect_ann_outer_lo = -1.0 -1.0 -1.0 # coordinates of low corner of outer rectangle
bpatch.patch_name5.patch_rect_ann_outer_hi = 1.0 1.0 1.0 # coordinates of high corner of outer rectangle
bpatch.patch_name5.patch_rect_ann_inner_lo = -0.5 -0.5 -0.5 # coordinates of low corner of inner rectangle
bpatch.patch_name5.patch_rect_ann_inner_hi = 0.5 0.5 0.5 # coordinates of high corner of inner rectangle
bpatch.patch_name5.species= O2 N2 # list of species names
The do_temporal flag will trigger the creation of a temporals folder in your run directory and the following entries will be appended to an ASCII temporals/tempState file: step, time, dt, kin. energy integral, enstrophy integral, mean pressure , fuel consumption rate integral, heat release rate integral. Additionally, if the do_temporal flag is activated, one can turn on state extremas (stored in temporals/tempExtremas as min/max for each state entry), mass balance (stored in temporals/tempMass) computing the total mass, dMdt and advective mass fluxes across the domain boundaries as well as the error in the balance (dMdt - sum of fluxes), and species balance (stored in temporals/tempSpec) computing each species total mass, dM_Ydt, advective & diffusive fluxes across the domain boundaries, consumption rate integral and the error (dMdt - sum of fluxes - reaction). Users can also monitor species advective fluxes through specific regions of the domain boundaries (called as boundary patches). Patches can be defined on the low or high sides of non-embedded boundaries through the use of pre-defined shapes such as circle, rectangle,`circle-annular`, rectangle-annular and full-boundary. The zero AMR level, advective fluxes of each of the user-specified species will be reported in the ASCII temppatchmfr file in the temporals folder.
Combustion diagnostics often involve the use of a mixture fraction and/or a progress variable, both of which can be defined at run time and added to the derived variables included in the plotfile. If mixture_fraction or progress_variable is added to the amr.derive_plot_vars list, one need to provide input for defining those. The mixture fraction is based on Bilger’s element definition and one needs to provide the composition of the ‘fuel’ and ‘oxidizer’ tanks using a Cantera-like format (<species>:<value>) which assumes unspecified species at zero, or a list of floats, in which case all the species must be specified in the order they appear in the mechanism file. The progress variable definition in based on a linear combination of the species mass fractions and temperature, and can be specified in a manner similar to the mixture fraction, providing a list of weights and the prescription of a ‘cold’ and ‘hot’ state:
# ------------------- INPUTS DERIVED DIAGS ------------------
peleLM.fuel_name = CH4
peleLM.mixtureFraction.format = Cantera
peleLM.mixtureFraction.type = mass
peleLM.mixtureFraction.oxidTank = O2:0.233 N2:0.767
peleLM.mixtureFraction.fuelTank = H2:0.5 CH4:0.5
peleLM.progressVariable.format = Cantera
peleLM.progressVariable.weights = CO:1.0 CO2:1.0
peleLM.progressVariable.coldState = CO:0.0 CO2:0.0
peleLM.progressVariable.hotState = CO:0.000002 CO2:0.0666
Analysing the data a-posteriori can become extremely cumbersome when dealing with extreme datasets. PeleLMeX offers a set of diagnostics available at runtime and more are under development. Currently, the list of diagnostic contains:
DiagFramePlane : extract a plane aligned in the ‘x’,’y’ or ‘z’ direction across the AMR hierarchy, writing a 2D plotfile compatible with Amrvis, Paraview or yt. Only available for 3D simulations.
DiagPDF : extract the PDF of a given variable and write it to an ASCII file.
DiagConditional : extract statistics (average and standard deviation, integral or sum) of a set of variables conditioned on the value of given variable and write it to an ASCII file.
When using DiagPDF or DiagConditional, it is possible to narrow down the diagnostic to a region of interest by specifying a set of filters, defining a range of interest for a variable. Note also the for these two diagnostics, fine-covered regions are masked. The following provide examples for each diagnostic:
#--------------------------DIAGNOSTICS------------------------
peleLM.diagnostics = xnormP condT pdfTest
peleLM.xnormP.type = DiagFramePlane # Diagnostic type
peleLM.xnormP.file = xNorm5mm # Output file prefix
peleLM.xnormP.normal = 0 # Plane normal (0, 1 or 2 for x, y or z)
peleLM.xnormP.center = 0.005 # Coordinate in the normal direction
peleLM.xnormP.int = 5 # Frequency (as step #) for performing the diagnostic
peleLM.xnormP.interpolation = Linear # [OPT, DEF=Linear] Interpolation type : Linear or Quadratic
peleLM.xnormP.field_names = x_velocity mag_vort density # List of variables outputted to the 2D pltfile
peleLM.xnormP.n_files = 2 # [OPT, DEF="min(256,NProcs)"] Number of files to write per level
peleLM.condT.type = DiagConditional # Diagnostic type
peleLM.condT.file = condTest # Output file prefix
peleLM.condT.int = 5 # Frequency (as step #) for performing the diagnostic
peleLM.condT.filters = xHigh stoich # [OPT, DEF=None] List of filters
peleLM.condT.xHigh.field_name = x # Filter field
peleLM.condT.xHigh.value_greater = 0.006 # Filter definition : value_greater, value_less, value_inrange
peleLM.condT.stoich.field_name = mixture_fraction # Filter field
peleLM.condT.stoich.value_inrange = 0.053 0.055 # Filter definition : value_greater, value_less, value_inrange
peleLM.condT.conditional_type = Average # Conditional type : Average, Integral or Sum
peleLM.condT.nBins = 50 # Number of bins for the conditioning variable
peleLM.condT.condition_field_name = temp # Conditioning variable name
peleLM.condT.field_names = HeatRelease I_R(CH4) I_R(H2) # List of variables to be treated
peleLM.pdfTest.type = DiagPDF # Diagnostic type
peleLM.pdfTest.file = PDFTest # Output file prefix
peleLM.pdfTest.int = 5 # Frequency (as step #) for performing the diagnostic
peleLM.pdfTest.filters = innerFlame # [OPT, DEF=None] List of filters
peleLM.pdfTest.innerFlame.field_name = temp # Filter field
peleLM.pdfTest.innerFlame.value_inrange = 450.0 1500.0 # Filter definition : value_greater, value_less, value_inrange
peleLM.pdfTest.nBins = 50 # Number of bins for the PDF
peleLM.pdfTest.normalized = 1 # [OPT, DEF=1] PDF is normalized (i.e. integral is unity) ?
peleLM.pdfTest.volume_weighted = 1 # [OPT, DEF=1] Computation of the PDF is volume weighted ?
peleLM.pdfTest.range = 0.0 2.0 # [OPT, DEF=data min/max] Specify the range of the PDF
peleLM.pdfTest.field_name = x_velocity # Variable of interest
Run-time control
Following some of AMReX’s AmrLevel class implementation, PeleLMeX provides a couple of triggers to interact with the code while it is running. This can be done by adding an empty file to the folder where the simulation is currently running using for example:
touch plt_and_continue
The list of available triggers is:
File |
Function |
|---|---|
plt_and_continue |
Write a pltfile to disk and pursue the simulation |
chk_and_continue |
Write a chkfile to disk and pursue the simulation |
dump_and_stop |
Write both pltfile and chkfile to disk and stop the simulation |
By default, the code checks if these files exist every 10 time steps, but the user can either increase or decrease the frequency using:
amr.message_int = 20 # [OPT, DEF=10] Frequency for checking the presence of trigger files