- nonlinear_convergenceName of Convergence object to use to assess convergence of the nonlinear solve. If not provided, the default Convergence associated with the Problem will be constructed internally.
C++ Type:ConvergenceName
Unit:(no unit assumed)
Controllable:No
Description:Name of Convergence object to use to assess convergence of the nonlinear solve. If not provided, the default Convergence associated with the Problem will be constructed internally.
- time0System time
Default:0
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:System time
- verboseFalseSet to true to print additional information
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Set to true to print additional information
Eigenvalue
Eigenvalue solves a standard/generalized linear or nonlinear eigenvalue problem
Input Parameters
- accept_on_max_fixed_point_iterationFalseTrue to treat reaching the maximum number of fixed point iterations as converged.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:True to treat reaching the maximum number of fixed point iterations as converged.
- auto_advanceFalseWhether to automatically advance sub-applications regardless of whether their solve converges, for transient executioners only.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether to automatically advance sub-applications regardless of whether their solve converges, for transient executioners only.
- custom_abs_tol1e-50The absolute nonlinear residual to shoot for during fixed point iterations. This check is performed based on postprocessor defined by the custom_pp residual.
Default:1e-50
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:The absolute nonlinear residual to shoot for during fixed point iterations. This check is performed based on postprocessor defined by the custom_pp residual.
- custom_ppPostprocessor for custom fixed point convergence check.
C++ Type:PostprocessorName
Unit:(no unit assumed)
Controllable:No
Description:Postprocessor for custom fixed point convergence check.
- custom_rel_tol1e-08The relative nonlinear residual drop to shoot for during fixed point iterations. This check is performed based on the postprocessor defined by custom_pp residual.
Default:1e-08
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:The relative nonlinear residual drop to shoot for during fixed point iterations. This check is performed based on the postprocessor defined by custom_pp residual.
- direct_pp_valueFalseTrue to use direct postprocessor value (scaled by value on first iteration). False (default) to use difference in postprocessor value between fixed point iterations.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:True to use direct postprocessor value (scaled by value on first iteration). False (default) to use difference in postprocessor value between fixed point iterations.
- disable_fixed_point_residual_norm_checkFalseDisable the residual norm evaluation thus the three parameters fixed_point_rel_tol, fixed_point_abs_tol and fixed_point_force_norms.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Disable the residual norm evaluation thus the three parameters fixed_point_rel_tol, fixed_point_abs_tol and fixed_point_force_norms.
- fixed_point_abs_tol1e-50The absolute nonlinear residual to shoot for during fixed point iterations. This check is performed based on the main app's nonlinear residual.
Default:1e-50
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:The absolute nonlinear residual to shoot for during fixed point iterations. This check is performed based on the main app's nonlinear residual.
- fixed_point_algorithmpicardThe fixed point algorithm to converge the sequence of problems.
Default:picard
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:The fixed point algorithm to converge the sequence of problems.
- fixed_point_force_normsFalseForce the evaluation of both the TIMESTEP_BEGIN and TIMESTEP_END norms regardless of the existence of active MultiApps with those execute_on flags, default: false.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Force the evaluation of both the TIMESTEP_BEGIN and TIMESTEP_END norms regardless of the existence of active MultiApps with those execute_on flags, default: false.
- fixed_point_max_its1Specifies the maximum number of fixed point iterations.
Default:1
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Specifies the maximum number of fixed point iterations.
- fixed_point_min_its1Specifies the minimum number of fixed point iterations.
Default:1
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Specifies the minimum number of fixed point iterations.
- fixed_point_rel_tol1e-08The relative nonlinear residual drop to shoot for during fixed point iterations. This check is performed based on the main app's nonlinear residual.
Default:1e-08
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:The relative nonlinear residual drop to shoot for during fixed point iterations. This check is performed based on the main app's nonlinear residual.
- relaxation_factor1Fraction of newly computed value to keep.Set between 0 and 2.
Default:1
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Fraction of newly computed value to keep.Set between 0 and 2.
- transformed_postprocessorsList of main app postprocessors to transform during fixed point iterations
C++ Type:std::vector<PostprocessorName>
Unit:(no unit assumed)
Controllable:No
Description:List of main app postprocessors to transform during fixed point iterations
- transformed_variablesList of main app variables to transform during fixed point iterations
C++ Type:std::vector<std::string>
Unit:(no unit assumed)
Controllable:No
Description:List of main app variables to transform during fixed point iterations
Fixed Point Iterations Parameters
- auto_initializationTrueIf true, we will set an initial eigen vector in moose, otherwise EPS solver will initial eigen vector
Default:True
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:If true, we will set an initial eigen vector in moose, otherwise EPS solver will initial eigen vector
- initial_eigenvalue1Initial eigenvalue
Default:1
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Initial eigenvalue
Eigenvector And Eigenvalue Initialization Parameters
- automatic_scalingFalseWhether to use automatic scaling for the variables.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether to use automatic scaling for the variables.
- compute_scaling_onceTrueWhether the scaling factors should only be computed once at the beginning of the simulation through an extra Jacobian evaluation. If this is set to false, then the scaling factors will be computed during an extra Jacobian evaluation at the beginning of every time step.
Default:True
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether the scaling factors should only be computed once at the beginning of the simulation through an extra Jacobian evaluation. If this is set to false, then the scaling factors will be computed during an extra Jacobian evaluation at the beginning of every time step.
- ignore_variables_for_autoscalingList of variables that do not participate in autoscaling.
C++ Type:std::vector<std::string>
Unit:(no unit assumed)
Controllable:No
Description:List of variables that do not participate in autoscaling.
- off_diagonals_in_auto_scalingFalseWhether to consider off-diagonals when determining automatic scaling factors.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether to consider off-diagonals when determining automatic scaling factors.
- resid_vs_jac_scaling_param0A parameter that indicates the weighting of the residual vs the Jacobian in determining variable scaling parameters. A value of 1 indicates pure residual-based scaling. A value of 0 indicates pure Jacobian-based scaling
Default:0
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:A parameter that indicates the weighting of the residual vs the Jacobian in determining variable scaling parameters. A value of 1 indicates pure residual-based scaling. A value of 0 indicates pure Jacobian-based scaling
- scaling_group_variablesName of variables that are grouped together for determining scale factors. (Multiple groups can be provided, separated by semicolon)
C++ Type:std::vector<std::vector<std::string>>
Unit:(no unit assumed)
Controllable:No
Description:Name of variables that are grouped together for determining scale factors. (Multiple groups can be provided, separated by semicolon)
Solver Variable Scaling Parameters
- constant_matricesFalseWhether or not to use constant matrices so that we can use them to form residuals on both linear and nonlinear iterations
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether or not to use constant matrices so that we can use them to form residuals on both linear and nonlinear iterations
- matrix_freeFalseWhether or not to use a matrix free fashion to form operators. If true, shell matrices will be used and meanwhile a preconditioning matrixmay be formed as well.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether or not to use a matrix free fashion to form operators. If true, shell matrices will be used and meanwhile a preconditioning matrixmay be formed as well.
- precond_matrix_freeFalseWhether or not to use a matrix free fashion for forming the preconditioning matrix. If true, a shell matrix will be used for preconditioner.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether or not to use a matrix free fashion for forming the preconditioning matrix. If true, a shell matrix will be used for preconditioner.
- precond_matrix_includes_eigenFalseWhether or not to include eigen kernels in the preconditioning matrix. If true, the preconditioning matrix will include eigen kernels.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether or not to include eigen kernels in the preconditioning matrix. If true, the preconditioning matrix will include eigen kernels.
Matrix And Matrix-Free Parameters
- contact_line_search_allowed_lambda_cuts2The number of times lambda is allowed to be cut in half in the contact line search. We recommend this number be roughly bounded by 0 <= allowed_lambda_cuts <= 3
Default:2
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The number of times lambda is allowed to be cut in half in the contact line search. We recommend this number be roughly bounded by 0 <= allowed_lambda_cuts <= 3
- contact_line_search_ltolThe linear relative tolerance to be used while the contact state is changing between non-linear iterations. We recommend that this tolerance be looser than the standard linear tolerance
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:The linear relative tolerance to be used while the contact state is changing between non-linear iterations. We recommend that this tolerance be looser than the standard linear tolerance
- line_searchdefaultSpecifies the line search type (Note: none = basic)
Default:default
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Specifies the line search type (Note: none = basic)
- line_search_packagepetscThe solver package to use to conduct the line-search
Default:petsc
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:The solver package to use to conduct the line-search
Solver Line Search Parameters
- control_tagsAdds user-defined labels for accessing object parameters via control logic.
C++ Type:std::vector<std::string>
Unit:(no unit assumed)
Controllable:No
Description:Adds user-defined labels for accessing object parameters via control logic.
- enableTrueSet the enabled status of the MooseObject.
Default:True
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Set the enabled status of the MooseObject.
- outputsVector of output names where you would like to restrict the output of variables(s) associated with this object
C++ Type:std::vector<OutputName>
Unit:(no unit assumed)
Controllable:No
Description:Vector of output names where you would like to restrict the output of variables(s) associated with this object
- skip_exception_checkFalseSpecifies whether or not to skip exception check
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Specifies whether or not to skip exception check
Advanced Parameters
- eigen_max_its10000Max Iterations for Eigen Solver
Default:10000
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Max Iterations for Eigen Solver
- eigen_problem_typeGEN_NON_HERMITIANType of the eigenvalue problem we are solving HERMITIAN: Hermitian NON_HERMITIAN: Non-Hermitian GEN_HERMITIAN: Generalized Hermitian GEN_NON_HERMITIAN: Generalized Non-Hermitian GEN_INDEFINITE: Generalized indefinite Hermitian POS_GEN_NON_HERMITIAN: Generalized Non-Hermitian with positive (semi-)definite B SLEPC_DEFAULT: Use whatever SLEPC has by default
Default:GEN_NON_HERMITIAN
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Type of the eigenvalue problem we are solving HERMITIAN: Hermitian NON_HERMITIAN: Non-Hermitian GEN_HERMITIAN: Generalized Hermitian GEN_NON_HERMITIAN: Generalized Non-Hermitian GEN_INDEFINITE: Generalized indefinite Hermitian POS_GEN_NON_HERMITIAN: Generalized Non-Hermitian with positive (semi-)definite B SLEPC_DEFAULT: Use whatever SLEPC has by default
- eigen_tol0.0001Relative Tolerance for Eigen Solver
Default:0.0001
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Relative Tolerance for Eigen Solver
- extra_power_iterations0The number of extra free power iterations
Default:0
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The number of extra free power iterations
- free_power_iterations4The number of free power iterations
Default:4
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The number of free power iterations
- n_basis_vectors3The dimension of eigen subspaces
Default:3
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The dimension of eigen subspaces
- n_eigen_pairs1The number of eigen pairs
Default:1
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The number of eigen pairs
- which_eigen_pairsWhich eigenvalue pairs to obtain from the solution LARGEST_MAGNITUDE SMALLEST_MAGNITUDE LARGEST_REAL SMALLEST_REAL LARGEST_IMAGINARY SMALLEST_IMAGINARY TARGET_MAGNITUDE TARGET_REAL TARGET_IMAGINARY ALL_EIGENVALUES SLEPC_DEFAULT
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Which eigenvalue pairs to obtain from the solution LARGEST_MAGNITUDE SMALLEST_MAGNITUDE LARGEST_REAL SMALLEST_REAL LARGEST_IMAGINARY SMALLEST_IMAGINARY TARGET_MAGNITUDE TARGET_REAL TARGET_IMAGINARY ALL_EIGENVALUES SLEPC_DEFAULT
Eigen Solver Parameters
- l_abs_tol1e-50Absolute Tolerances for Linear Solver
Default:1e-50
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Absolute Tolerances for Linear Solver
Linear Solver Parameters
- l_max_its10000Max Linear Iterations
Default:10000
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Max Linear Iterations
- l_tol0.01Linear Relative Tolerance
Default:0.01
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Linear Relative Tolerance
- reuse_preconditionerFalseIf true reuse the previously calculated preconditioner for the linearized system across multiple solves spanning nonlinear iterations and time steps. The preconditioner resets as controlled by reuse_preconditioner_max_linear_its
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:If true reuse the previously calculated preconditioner for the linearized system across multiple solves spanning nonlinear iterations and time steps. The preconditioner resets as controlled by reuse_preconditioner_max_linear_its
- reuse_preconditioner_max_linear_its25Reuse the previously calculated preconditioner for the linear system until the number of linear iterations exceeds this number
Default:25
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Reuse the previously calculated preconditioner for the linear system until the number of linear iterations exceeds this number
Linear Solver Parameters
- max_xfem_update4294967295Maximum number of times to update XFEM crack topology in a step due to evolving cracks
Default:4294967295
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Maximum number of times to update XFEM crack topology in a step due to evolving cracks
- update_xfem_at_timestep_beginFalseShould XFEM update the mesh at the beginning of the timestep
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Should XFEM update the mesh at the beginning of the timestep
Xfem Fixed Point Iterations Parameters
- mffd_typewpSpecifies the finite differencing type for Jacobian-free solve types. Note that the default is wp (for Walker and Pernice).
Default:wp
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Specifies the finite differencing type for Jacobian-free solve types. Note that the default is wp (for Walker and Pernice).
- petsc_optionsSingleton PETSc options
C++ Type:MultiMooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Singleton PETSc options
- petsc_options_inameNames of PETSc name/value pairs
C++ Type:MultiMooseEnum
Unit:(no unit assumed)
Controllable:No
Description:Names of PETSc name/value pairs
- petsc_options_valueValues of PETSc name/value pairs (must correspond with "petsc_options_iname"
C++ Type:std::vector<std::string>
Unit:(no unit assumed)
Controllable:No
Description:Values of PETSc name/value pairs (must correspond with "petsc_options_iname"
Petsc Parameters
- n_max_nonlinear_pingpong100The maximum number of times the nonlinear residual can ping pong before requesting halting the current evaluation and requesting timestep cut for transient simulations
Default:100
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The maximum number of times the nonlinear residual can ping pong before requesting halting the current evaluation and requesting timestep cut for transient simulations
- nl_abs_div_tol1e+50Nonlinear Absolute Divergence Tolerance. A negative value disables this check.
Default:1e+50
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Absolute Divergence Tolerance. A negative value disables this check.
- nl_abs_step_tol0Nonlinear Absolute step Tolerance
Default:0
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Absolute step Tolerance
- nl_abs_tol1e-50Nonlinear Absolute Tolerance
Default:1e-50
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Absolute Tolerance
- nl_div_tol1e+10Nonlinear Relative Divergence Tolerance. A negative value disables this check.
Default:1e+10
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Relative Divergence Tolerance. A negative value disables this check.
- nl_forced_its0The Number of Forced Nonlinear Iterations
Default:0
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The Number of Forced Nonlinear Iterations
- nl_max_funcs10000Max Nonlinear solver function evaluations
Default:10000
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Max Nonlinear solver function evaluations
- nl_max_its50Max Nonlinear Iterations
Default:50
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:Max Nonlinear Iterations
- nl_rel_step_tol0Nonlinear Relative step Tolerance
Default:0
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Relative step Tolerance
- nl_rel_tol1e-08Nonlinear Relative Tolerance
Default:1e-08
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Nonlinear Relative Tolerance
- num_grids1The number of grids to use for a grid sequencing algorithm. This includes the final grid, so num_grids = 1 indicates just one solve in a time-step
Default:1
C++ Type:unsigned int
Unit:(no unit assumed)
Controllable:No
Description:The number of grids to use for a grid sequencing algorithm. This includes the final grid, so num_grids = 1 indicates just one solve in a time-step
- residual_and_jacobian_togetherFalseWhether to compute the residual and Jacobian together.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether to compute the residual and Jacobian together.
- snesmf_reuse_baseTrueSpecifies whether or not to reuse the base vector for matrix-free calculation
Default:True
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Specifies whether or not to reuse the base vector for matrix-free calculation
- solve_typePJFNKPOWER: Power / Inverse / RQI ARNOLDI: Arnoldi KRYLOVSCHUR: Krylov-Schur JACOBI_DAVIDSON: Jacobi-Davidson NONLINEAR_POWER: Nonlinear Power NEWTON: Newton PJFNK: Preconditioned Jacobian-free Newton-KyrlovJFNK: Jacobian-free Newton-KyrlovPJFNKMO: Preconditioned Jacobian-free Newton-Kyrlov with Matrix Only
Default:PJFNK
C++ Type:MooseEnum
Unit:(no unit assumed)
Controllable:No
Description:POWER: Power / Inverse / RQI ARNOLDI: Arnoldi KRYLOVSCHUR: Krylov-Schur JACOBI_DAVIDSON: Jacobi-Davidson NONLINEAR_POWER: Nonlinear Power NEWTON: Newton PJFNK: Preconditioned Jacobian-free Newton-KyrlovJFNK: Jacobian-free Newton-KyrlovPJFNKMO: Preconditioned Jacobian-free Newton-Kyrlov with Matrix Only
- splittingTop-level splitting defining a hierarchical decomposition into subsystems to help the solver.
C++ Type:std::vector<std::string>
Unit:(no unit assumed)
Controllable:No
Description:Top-level splitting defining a hierarchical decomposition into subsystems to help the solver.
- use_pre_SMO_residualFalseCompute the pre-SMO residual norm and use it in the relative convergence check. The pre-SMO residual is computed at the begining of the time step before solution-modifying objects are executed. Solution-modifying objects include preset BCs, constraints, predictors, etc.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Compute the pre-SMO residual norm and use it in the relative convergence check. The pre-SMO residual is computed at the begining of the time step before solution-modifying objects are executed. Solution-modifying objects include preset BCs, constraints, predictors, etc.
Nonlinear Solver Parameters
- normal_factorNormalize eigenvector to make a defined norm equal to this factor
C++ Type:double
Unit:(no unit assumed)
Controllable:No
Description:Normalize eigenvector to make a defined norm equal to this factor
- normalizationPostprocessor evaluating norm of eigenvector for normalization
C++ Type:PostprocessorName
Unit:(no unit assumed)
Controllable:No
Description:Postprocessor evaluating norm of eigenvector for normalization