- auto_advanceFalseWhether to automatically advance sub-applications regardless of whether their solve converges.
Default:False
C++ Type:bool
Description:Whether to automatically advance sub-applications regardless of whether their solve converges.
- auto_initializationTrueIf true, we will set an initial eigen vector in moose, otherwise EPS solver will initial eigen vector
Default:True
C++ Type:bool
Description:If true, we will set an initial eigen vector in moose, otherwise EPS solver will initial eigen vector
- 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
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
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
- custom_abs_tol1e-50The absolute nonlinear residual to shoot for during Picard iterations. This check is performed based on postprocessor defined by picard_custom_pp residual.
Default:1e-50
C++ Type:double
Description:The absolute nonlinear residual to shoot for during Picard iterations. This check is performed based on postprocessor defined by picard_custom_pp residual.
- custom_rel_tol1e-08The relative nonlinear residual drop to shoot for during Picard iterations. This check is performed based on postprocessor defined by picard_custom_pp residual.
Default:1e-08
C++ Type:double
Description:The relative nonlinear residual drop to shoot for during Picard iterations. This check is performed based on postprocessor defined by picard_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 picard iterations.
Default:False
C++ Type:bool
Description:True to use direct postprocessor value (scaled by value on first iteration). False (default) to use difference in postprocessor value between picard iterations.
- eigen_max_its10000Max Iterations for Eigen Solver
Default:10000
C++ Type:unsigned int
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
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
Description:Relative Tolerance for Eigen Solver
- extra_power_iterations0The number of extra free power iterations
Default:0
C++ Type:unsigned int
Description:The number of extra free power iterations
- free_power_iterations4The number of free power iterations
Default:4
C++ Type:unsigned int
Description:The number of free power iterations
- l_abs_tol1e-50Absolute Tolerances for Linear Solver
Default:1e-50
C++ Type:double
Description:Absolute Tolerances for Linear Solver
- line_searchdefaultSpecifies the line search type (Note: none = basic)
Default:default
C++ Type:MooseEnum
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
Description:The solver package to use to conduct the line-search
- 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
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.
- max_xfem_update4294967295Maximum number of times to update XFEM crack topology in a step due to evolving cracks
Default:4294967295
C++ Type:unsigned int
Description:Maximum number of times to update XFEM crack topology in a step due to evolving cracks
- 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
Description:Specifies the finite differencing type for Jacobian-free solve types. Note that the default is wp (for Walker and Pernice).
- n_basis_vectors3The dimension of eigen subspaces
Default:3
C++ Type:unsigned int
Description:The dimension of eigen subspaces
- n_eigen_pairs1The number of eigen pairs
Default:1
C++ Type:unsigned int
Description:The number of eigen pairs
- n_max_nonlinear_pingpong100The maximum number of times the non linear residual can ping pong before requesting halting the current evalution and requesting timestep cut
Default:100
C++ Type:unsigned int
Description:The maximum number of times the non linear residual can ping pong before requesting halting the current evalution and requesting timestep cut
- nl_abs_div_tol1e+50Nonlinear Absolute Divergence Tolerance. A negative value disables this check.
Default:1e+50
C++ Type:double
Description:Nonlinear Absolute Divergence Tolerance. A negative value disables this check.
- nl_div_tol1e+10Nonlinear Relative Divergence Tolerance. A negative value disables this check.
Default:1e+10
C++ Type:double
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
Description:The Number of Forced Nonlinear Iterations
- normal_factorNormalize eigenvector to make a defined norm equal to this factor
C++ Type:double
Description:Normalize eigenvector to make a defined norm equal to this factor
- normalizationPostprocessor evaluating norm of eigenvector for normalization
C++ Type:PostprocessorName
Description:Postprocessor evaluating norm of eigenvector for normalization
- petsc_optionsSingleton PETSc options
C++ Type:MultiMooseEnum
Description:Singleton PETSc options
- petsc_options_inameNames of PETSc name/value pairs
C++ Type:MultiMooseEnum
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>
Description:Values of PETSc name/value pairs (must correspond with "petsc_options_iname"
- 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
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
Description:Whether or not to include eigen kernels in the preconditioning matrix. If true, the preconditioning matrix will include eigen kernels.
- 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
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 to for determing scale factors. (Multiple groups can be provided, separated by semicolon)
C++ Type:std::vector<std::vector<std::string>>
Description:Name of variables that are grouped together to for determing scale factors. (Multiple groups can be provided, separated by semicolon)
- skip_exception_checkFalseSpecifies whether or not to skip exception check
Default:False
C++ Type:bool
Description:Specifies whether or not to skip exception check
- 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-Kyrlov
Default:PJFNK
C++ Type:MooseEnum
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-Kyrlov
- splittingTop-level splitting defining a hierarchical decomposition into subsystems to help the solver.
C++ Type:std::vector<std::string>
Description:Top-level splitting defining a hierarchical decomposition into subsystems to help the solver.
- time0System time
Default:0
C++ Type:double
Description:System time
- update_xfem_at_timestep_beginFalseShould XFEM update the mesh at the beginning of the timestep
Default:False
C++ Type:bool
Description:Should XFEM update the mesh at the beginning of the timestep
- verboseFalseSet to true to print additional information
Default:False
C++ Type:bool
Description:Set to true to print additional information
- 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
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
Eigenvalue
Eigenvalue solves a standard/generalized linear or nonlinear eigenvalue problem
Input Parameters
- accept_on_max_picard_iterationFalseTrue to treat reaching the maximum number of Picard iterations as converged.
Default:False
C++ Type:bool
Description:True to treat reaching the maximum number of Picard iterations as converged.
- disable_picard_residual_norm_checkFalseDisable the Picard residual norm evaluation thus the three parameters picard_rel_tol, picard_abs_tol and picard_force_norms.
Default:False
C++ Type:bool
Description:Disable the Picard residual norm evaluation thus the three parameters picard_rel_tol, picard_abs_tol and picard_force_norms.
- picard_abs_tol1e-50The absolute nonlinear residual to shoot for during Picard iterations. This check is performed based on the Master app's nonlinear residual.
Default:1e-50
C++ Type:double
Description:The absolute nonlinear residual to shoot for during Picard iterations. This check is performed based on the Master app's nonlinear residual.
- picard_custom_ppPostprocessor for custom picard convergence check.
C++ Type:PostprocessorName
Description:Postprocessor for custom picard convergence check.
- picard_force_normsFalseForce the evaluation of both the TIMESTEP_BEGIN and TIMESTEP_END norms regardless of the existance of active MultiApps with those execute_on flags, default: false.
Default:False
C++ Type:bool
Description:Force the evaluation of both the TIMESTEP_BEGIN and TIMESTEP_END norms regardless of the existance of active MultiApps with those execute_on flags, default: false.
- picard_max_its1Specifies the maximum number of Picard iterations. Mainly used when wanting to do Picard iterations with MultiApps that are set to execute_on timestep_end or timestep_begin. Setting this parameter to 1 turns off the Picard iterations.
Default:1
C++ Type:unsigned int
Description:Specifies the maximum number of Picard iterations. Mainly used when wanting to do Picard iterations with MultiApps that are set to execute_on timestep_end or timestep_begin. Setting this parameter to 1 turns off the Picard iterations.
- picard_rel_tol1e-08The relative nonlinear residual drop to shoot for during Picard iterations. This check is performed based on the Master app's nonlinear residual.
Default:1e-08
C++ Type:double
Description:The relative nonlinear residual drop to shoot for during Picard iterations. This check is performed based on the Master app's nonlinear residual.
- relaxation_factor1Fraction of newly computed value to keep.Set between 0 and 2.
Default:1
C++ Type:double
Description:Fraction of newly computed value to keep.Set between 0 and 2.
- relaxed_variablesList of variables to relax during Picard Iteration
C++ Type:std::vector<std::string>
Description:List of variables to relax during Picard Iteration
Picard Parameters
- automatic_scalingFalseWhether to use automatic scaling for the variables.
Default:False
C++ Type:bool
Description:Whether to use automatic scaling for the variables.
- compute_initial_residual_before_preset_bcsFalseUse the residual norm computed *before* preset BCs are imposed in relative convergence check
Default:False
C++ Type:bool
Description:Use the residual norm computed *before* preset BCs are imposed in relative convergence check
- 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
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.
- l_max_its10000Max Linear Iterations
Default:10000
C++ Type:unsigned int
Description:Max Linear Iterations
- l_tol0.01Linear Tolerance
Default:0.01
C++ Type:double
Description:Linear Tolerance
- nl_abs_step_tol0Nonlinear Absolute step Tolerance
Default:0
C++ Type:double
Description:Nonlinear Absolute step Tolerance
- nl_abs_tol1e-50Nonlinear Absolute Tolerance
Default:1e-50
C++ Type:double
Description:Nonlinear Absolute Tolerance
- nl_max_funcs10000Max Nonlinear solver function evaluations
Default:10000
C++ Type:unsigned int
Description:Max Nonlinear solver function evaluations
- nl_max_its50Max Nonlinear Iterations
Default:50
C++ Type:unsigned int
Description:Max Nonlinear Iterations
- nl_rel_step_tol0Nonlinear Relative step Tolerance
Default:0
C++ Type:double
Description:Nonlinear Relative step Tolerance
- nl_rel_tol1e-08Nonlinear Relative Tolerance
Default:1e-08
C++ Type:double
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
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
- snesmf_reuse_baseTrueSpecifies whether or not to reuse the base vector for matrix-free calculation
Default:True
C++ Type:bool
Description:Specifies whether or not to reuse the base vector for matrix-free calculation
Solver Parameters
- control_tagsAdds user-defined labels for accessing object parameters via control logic.
C++ Type:std::vector<std::string>
Description:Adds user-defined labels for accessing object parameters via control logic.
- enableTrueSet the enabled status of the MooseObject.
Default:True
C++ Type:bool
Description:Set the enabled status of the MooseObject.
- outputsVector of output names were you would like to restrict the output of variables(s) associated with this object
C++ Type:std::vector<OutputName>
Description:Vector of output names were you would like to restrict the output of variables(s) associated with this object
Advanced Parameters
Restart Parameters
Input Files
- (test/tests/problems/eigen_problem/eigensolvers/ne_deficient_b.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne_hmg.i)
- (test/tests/problems/eigen_problem/eigensolvers/dg_krylovschur.i)
- (test/tests/tag/eigen_tag.i)
- (test/tests/problems/eigen_problem/eigensolvers/gipm_ibc.i)
- (test/tests/problems/eigen_problem/preconditioners/ne_pbp.i)
- (test/tests/problems/eigen_problem/eigensolvers/ipm.i)
- (test/tests/problems/eigen_problem/initial_condition/ne_ic.i)
- (test/tests/problems/eigen_problem/initial_condition/ne_ic_no_free.i)
- (test/tests/problems/eigen_problem/eigensolvers/scalar.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne-coupled-resid-scaling.i)
- (test/tests/problems/eigen_problem/arraykernels/ne_array_kernels.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne_coupled_picard_subT_sub.i)
- (test/tests/problems/eigen_problem/eigensolvers/gipm.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne_coupled_scaled.i)
- (test/tests/problems/eigen_problem/eigensolvers/ane.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne-coupled-scaling.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne_coupled.i)
- (test/tests/problems/eigen_problem/arraykernels/ne_two_variables.i)
- (test/tests/problems/eigen_problem/eigensolvers/ne_coupled_picard.i)