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temp.txt
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[Executioner]
active = __all__ # If specified only the blocks named will be visited and made active
l_abs_step_tol = -1 # Linear Absolute Step Tolerance
l_max_its = 10000 # Max Linear Iterations
l_tol = 1e-05 # Linear Tolerance
line_search = default # Specifies the line search type (Note: none = basic)
nl_abs_step_tol = 1e-50 # Nonlinear Absolute step Tolerance
nl_abs_tol = 1e-50 # Nonlinear Absolute Tolerance
nl_max_funcs = 10000 # Max Nonlinear solver function evaluations
nl_max_its = 50 # Max Nonlinear Iterations
nl_rel_step_tol = 1e-50 # Nonlinear Relative step Tolerance
nl_rel_tol = 1e-08 # Nonlinear Relative Tolerance
no_fe_reinit = 0 # Specifies whether or not to reinitialize FEs
petsc_options = # Singleton PETSc options
petsc_options_iname = # Names of PETSc name/value pairs
petsc_options_value = # Values of PETSc name/value pairs (must correspond with "petsc_options_iname"
solve_type = # PJFNK: Preconditioned Jacobian-Free Newton Krylov JFNK: Jacobian-Free ...
# Newton Krylov NEWTON: Full Newton Solve FD: Use finite differences to ...
# compute Jacobian LINEAR: Solving a linear problem
[./<type>]
[./CoupledTransientExecutioner]
num_steps = 4294967295 # The number of timesteps in a transient run
restart_file_base = # File base name used for restart
splitting = # Top-level splitting defining a hierarchical decomposition into subsystems ...
# to help the solver.
type = CoupledTransientExecutioner
[../]
[./InversePowerMethod]
Chebyshev_acceleration_on = 1 # If Chebyshev acceleration is turned on
auto_initialization = 1 # True to ask the solver to set initial
bx_norm = (required) # To evaluate |Bx| for the eigenvalue
eig_check_tol = 1e-06 # Eigenvalue convergence tolerance
k0 = 1 # Initial guess of the eigenvalue
max_power_iterations = 300 # The maximum number of power iterations
min_power_iterations = 1 # Minimum number of power iterations
normal_factor = # Normalize x to make |x| equal to this factor
normalization = # To evaluate |x| for normalization
output_on_final = 0 # True to disable all the intemediate exodus outputs
output_pi_history = 0 # True to output solutions durint PI
pfactor = 0.01 # Reduce residual norm per power iteration by this factor
restart_file_base = # File base name used for restart
splitting = # Top-level splitting defining a hierarchical decomposition into subsystems ...
# to help the solver.
time = 0 # System time
type = InversePowerMethod
xdiff = # To evaluate |x-x_previous| for power iterations
[../]
[./NonlinearEigen]
auto_initialization = 1 # True to ask the solver to set initial
bx_norm = (required) # To evaluate |Bx| for the eigenvalue
free_power_iterations = 4 # The number of free power iterations
k0 = 1 # Initial guess of the eigenvalue
normal_factor = # Normalize x to make |x| equal to this factor
normalization = # To evaluate |x| for normalization
output_on_final = 0 # True to disable all the intemediate exodus outputs
output_pi_history = 0 # True to output solutions durint PI
pfactor = 0.01 # The factor of residual to be reduced per power iteration
restart_file_base = # File base name used for restart
source_abs_tol = 1e-06 # Absolute tolernance on residual norm
source_rel_tol = 1e-50 # Relative tolernance on residual norm after free power iterations
splitting = # Top-level splitting defining a hierarchical decomposition into subsystems ...
# to help the solver.
time = 0 # System time
type = NonlinearEigen
xdiff = # To evaluate |x-x_previous| for power iterations
[../]
[./Steady]
restart_file_base = # File base name used for restart
splitting = # Top-level splitting defining a hierarchical decomposition into subsystems ...
# to help the solver.
type = Steady
[../]
[./Transient]
abort_on_solve_fail = 0 # abort if solve not converged rather than cut timestep
dt = 1 # The timestep size between solves
dtmax = 1e+30 # The maximum timestep size in an adaptive run
dtmin = 2e-14 # The minimum timestep size in an adaptive run
end_time = 1e+30 # The end time of the simulation
n_startup_steps = 0 # The number of timesteps during startup
num_steps = 4294967295 # The number of timesteps in a transient run
picard_abs_tol = 1e-50 # The absolute nonlinear residual to shoot for during Picard iterations. ...
# This check is performed based on the Master app's nonlinear residual.
picard_max_its = 1 # Number of times each timestep will be solved. Mainly used when wanting ...
# to do Picard iterations with MultiApps that are set to execute_on timestep ...
# or timestep_begin
picard_rel_tol = 1e-08 # The relative nonlinear residual drop to shoot for during Picard iterations. ...
# This check is performed based on the Master app's nonlinear residual.
predictor_scale = # The scale factor for the predictor (can range from 0 to 1)
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
restart_file_base = # File base name used for restart
scheme = implicit-euler # Time integration scheme used.
splitting = # Top-level splitting defining a hierarchical decomposition into subsystems ...
# to help the solver.
ss_check_tol = 1e-08 # Whenever the relative residual changes by less than this the solution ...
# will be considered to be at steady state.
ss_tmin = 0 # Minimum number of timesteps to take before checking for steady state ...
# conditions.
start_time = 0 # The start time of the simulation
time_period_ends = # The end times of time periods
time_period_starts = # The start times of time periods
time_periods = # The names of periods
timestep_tolerance = 2e-14 # the tolerance setting for final timestep size and sync times
trans_ss_check = 0 # Whether or not to check for steady state conditions
type = Transient
use_multiapp_dt = 0 # If true then the dt for the simulation will be chosen by the MultiApps. ...
# If false (the default) then the minimum over the master dt and the MultiApps ...
# is used
verbose = 0 # Print detailed diagnostics on timestep calculation
[../]
[../]
[./Adaptivity]
active = __all__ # If specified only the blocks named will be visited and made active
coarsen_fraction = 0 # The fraction of elements or error to coarsen. Should be between 0 and ...
# 1.
cycles_per_step = 1 # The number of adaptivity cycles per step
error_estimator = KellyErrorEstimator # The class name of the error estimator you want to use.
initial_adaptivity = 0 # The number of adaptivity steps to perform using the initial conditions
max_h_level = 0 # Maximum number of times a single element can be refined. If 0 then infinite.
print_changed_info = 0 # Determines whether information about the mesh is printed when adaptivity ...
# occurs
refine_fraction = 0 # The fraction of elements or error to refine. Should be between 0 and ...
# 1.
show_initial_progress = 1 # Show the progress of the initial adaptivity
start_time = -1.79769e+308 # The time that adaptivity will be active after.
steps = 0 # The number of adaptivity steps to perform at any one time for steady ...
# state
stop_time = 1.79769e+308 # The time after which adaptivity will no longer be active.
weight_names = # List of names of variables that will be associated with weight_values
weight_values = # List of values between 0 and 1 to weight the associated weight_names ...
# error by
[../]
[./Predictor]
active = __all__ # If specified only the blocks named will be visited and made active
[./<type>]
[./AdamsPredictor]
order = 2 # The maximum reachable order of the Adams-Bashforth Predictor
scale = (required) # The scale factor for the predictor (can range from 0 to 1)
type = AdamsPredictor
[../]
[./SimplePredictor]
scale = (required) # The scale factor for the predictor (can range from 0 to 1)
type = SimplePredictor
[../]
[../]
[../]
[./Quadrature]
active = __all__ # If specified only the blocks named will be visited and made active
element_order = AUTO # Order of the quadrature for elements
order = AUTO # Order of the quadrature
side_order = AUTO # Order of the quadrature for sides
type = GAUSS # Type of the quadrature rule
[../]
[./TimePeriods]
[./*]
active = __all__ # If specified only the blocks named will be visited and made active
active_bcs = # The list of active boundary conditions during this time period (must ...
# not be used with "inactive_bcs")
active_kernels = # The list of active kernels during this time period (must not be used ...
# with "inactive_kernels")
inactive_bcs = # The list of inactive boundary conditions during this time period (must ...
# not be used with "active_bcs")
inactive_kernels = # The list of inactive kernels during this time period (must not be used ...
# with "active_kernels")
start = 0 # The start time for this time period
[../]
[../]
[./TimeStepper]
active = __all__ # If specified only the blocks named will be visited and made active
[./<type>]
[./AB2PredictorCorrector]
dt = (required) # Initial time step size
e_max = (required) # Maximum acceptable error.
e_tol = (required) # Target error tolerance.
max_increase = 1e+09 # Maximum ratio that the time step can increase.
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
scaling_parameter = 0.8 # scaling parameter for dt selection
start_adapting = 2 # when to start taking adaptive time steps
steps_between_increase = 1 # the number of time steps before recalculating dt
type = AB2PredictorCorrector
[../]
[./ConstantDT]
dt = (required) # Size of the time step
growth_factor = 2 # Maximum ratio of new to previous timestep sizes following a step that ...
# required the time step to be cut due to a failed solve.
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
type = ConstantDT
[../]
[./DT2]
dt = 1 # The initial time step size.
e_max = (required) # Maximum acceptable error.
e_tol = (required) # Target error tolerance.
max_increase = 1e+09 # Maximum ratio that the time step can increase.
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
type = DT2
[../]
[./FunctionDT]
growth_factor = 2 # Maximum ratio of new to previous timestep sizes following a step that ...
# required the time step to be cut due to a failed solve.
min_dt = 0 # The minimal dt to take.
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
time_dt = # The values of dt
time_t = # The values of t
type = FunctionDT
[../]
[./IterationAdaptiveDT]
cutback_factor = 0.5 # Factor to apply to timestep if difficult convergence (if 'optimal_iterations' ...
# is specified) or if solution failed.
dt = (required) # The default timestep size between solves
force_step_every_function_point = 0 # Forces the timestepper to take a step that is consistent with points ...
# defined in the function.
growth_factor = 2 # Factor to apply to timestep if easy convergence (if 'optimal_iterations' ...
# is specified) or if recovering from failed solve
iteration_window = # The size of the nonlinear iteration window for adaptive timestepping ...
# (default = 0.2*optimal_iterations)
linear_iteration_ratio = # The ratio of linear to nonlinear iterations to determine target linear ...
# iterations and window for adaptive timestepping (default = 25)
max_function_change = # The absolute value of the maximum change in timestep_limiting_function ...
# over a timestep
optimal_iterations = # The target number of nonlinear iterations for adaptive timestepping
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
time_dt = # The values of dt
time_t = # The values of t
timestep_limiting_function = # A function used to control the timestep by limiting the change in the ...
# function over a timestep
type = IterationAdaptiveDT
[../]
[./PostprocessorDT]
dt = # Initial value of dt
postprocessor = (required) # The name of the postprocessor that computes the dt
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
type = PostprocessorDT
[../]
[./SolutionTimeAdaptiveDT]
adapt_log = 0 # Output adaptive time step log
dt = (required) # The timestep size between solves
initial_direction = 1 # Direction for the first step. 1 for up... -1 for down.
percent_change = 0.1 # Percentage to change the timestep by. Should be between 0 and 1
reset_dt = 0 # Use when restarting a calculation to force a change in dt.
type = SolutionTimeAdaptiveDT
[../]
[../]
[../]
[]