Eigenvalue

Eigenvalue solves a standard/generalized linear or nonlinear eigenvalue problem

Input Parameters

  • auto_advanceFalseWhether to automatically advance sub-applications regardless of whether their solve converges.

    Default:False

    C++ Type:bool

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:HERMITIAN, NON_HERMITIAN, GEN_HERMITIAN, GEN_NON_HERMITIAN, GEN_INDEFINITE, POS_GEN_NON_HERMITIAN, SLEPC_DEFAULT

    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

    Options:

    Description:Relative Tolerance for Eigen Solver

  • extra_power_iterations0The number of extra free power iterations

    Default:0

    C++ Type:unsigned int

    Options:

    Description:The number of extra free power iterations

  • free_power_iterations4The number of free power iterations

    Default:4

    C++ Type:unsigned int

    Options:

    Description:The number of free power iterations

  • l_abs_tol1e-50Absolute Tolerances for Linear Solver

    Default:1e-50

    C++ Type:double

    Options:

    Description:Absolute Tolerances for Linear Solver

  • line_searchdefaultSpecifies the line search type (Note: none = basic)

    Default:default

    C++ Type:MooseEnum

    Options:basic, bt, contact, cp, default, l2, none, project, shell

    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

    Options:petsc, moose

    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

    Options:

    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

    Options:

    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

    Options:wp, ds

    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

    Options:

    Description:The dimension of eigen subspaces

  • n_eigen_pairs1The number of eigen pairs

    Default:1

    C++ Type:unsigned int

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    Description:The Number of Forced Nonlinear Iterations

  • normal_factorNormalize eigenvector to make a defined norm equal to this factor

    C++ Type:double

    Options:

    Description:Normalize eigenvector to make a defined norm equal to this factor

  • normalizationPostprocessor evaluating norm of eigenvector for normalization

    C++ Type:PostprocessorName

    Options:

    Description:Postprocessor evaluating norm of eigenvector for normalization

  • petsc_optionsSingleton PETSc options

    C++ Type:MultiMooseEnum

    Options:-dm_moose_print_embedding, -dm_view, -ksp_converged_reason, -ksp_gmres_modifiedgramschmidt, -ksp_monitor, -ksp_monitor_snes_lg-snes_ksp_ew, -ksp_snes_ew, -snes_converged_reason, -snes_ksp, -snes_ksp_ew, -snes_linesearch_monitor, -snes_mf, -snes_mf_operator, -snes_monitor, -snes_test_display, -snes_view

    Description:Singleton PETSc options

  • petsc_options_inameNames of PETSc name/value pairs

    C++ Type:MultiMooseEnum

    Options:-ksp_atol, -ksp_gmres_restart, -ksp_max_it, -ksp_pc_side, -ksp_rtol, -ksp_type, -mat_fd_coloring_err, -mat_fd_type, -mat_mffd_type, -pc_asm_overlap, -pc_factor_levels, -pc_factor_mat_ordering_type, -pc_hypre_boomeramg_grid_sweeps_all, -pc_hypre_boomeramg_max_iter, -pc_hypre_boomeramg_strong_threshold, -pc_hypre_type, -pc_type, -snes_atol, -snes_linesearch_type, -snes_ls, -snes_max_it, -snes_rtol, -snes_divergence_tolerance, -snes_type, -sub_ksp_type, -sub_pc_type

    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>

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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>>

    Options:

    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

    Options:

    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

    Options:POWER, ARNOLDI, KRYLOVSCHUR, JACOBI_DAVIDSON, NONLINEAR_POWER, NEWTON, PJFNK, JFNK

    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>

    Options:

    Description:Top-level splitting defining a hierarchical decomposition into subsystems to help the solver.

  • time0System time

    Default:0

    C++ Type:double

    Options:

    Description:System time

  • update_xfem_at_timestep_beginFalseShould XFEM update the mesh at the beginning of the timestep

    Default:False

    C++ Type:bool

    Options:

    Description:Should XFEM update the mesh at the beginning of the timestep

  • verboseFalseSet to true to print additional information

    Default:False

    C++ Type:bool

    Options:

    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

    Options:LARGEST_MAGNITUDE, SMALLEST_MAGNITUDE, LARGEST_REAL, SMALLEST_REAL, LARGEST_IMAGINARY, SMALLEST_IMAGINARY, TARGET_MAGNITUDE, TARGET_REAL, TARGET_IMAGINARY, ALL_EIGENVALUES, SLEPC_DEFAULT

    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

Optional Parameters

  • accept_on_max_picard_iterationFalseTrue to treat reaching the maximum number of Picard iterations as converged.

    Default:False

    C++ Type:bool

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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>

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    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

    Options:

    Description:Max Linear Iterations

  • l_tol0.01Linear Tolerance

    Default:0.01

    C++ Type:double

    Options:

    Description:Linear Tolerance

  • nl_abs_step_tol0Nonlinear Absolute step Tolerance

    Default:0

    C++ Type:double

    Options:

    Description:Nonlinear Absolute step Tolerance

  • nl_abs_tol1e-50Nonlinear Absolute Tolerance

    Default:1e-50

    C++ Type:double

    Options:

    Description:Nonlinear Absolute Tolerance

  • nl_max_funcs10000Max Nonlinear solver function evaluations

    Default:10000

    C++ Type:unsigned int

    Options:

    Description:Max Nonlinear solver function evaluations

  • nl_max_its50Max Nonlinear Iterations

    Default:50

    C++ Type:unsigned int

    Options:

    Description:Max Nonlinear Iterations

  • nl_rel_step_tol0Nonlinear Relative step Tolerance

    Default:0

    C++ Type:double

    Options:

    Description:Nonlinear Relative step Tolerance

  • nl_rel_tol1e-08Nonlinear Relative Tolerance

    Default:1e-08

    C++ Type:double

    Options:

    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

    Options:

    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

    Options:

    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>

    Options:

    Description:Adds user-defined labels for accessing object parameters via control logic.

  • enableTrueSet the enabled status of the MooseObject.

    Default:True

    C++ Type:bool

    Options:

    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>

    Options:

    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