Eigenvalue

Eigenvalue solves a standard/generalized linear or nonlinear eigenvalue problem

Input Parameters

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

Optional 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)
Options:picard, secant, steffensen
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_once1 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. Vector entries correspond to each nonlinear system.
Default:1
C++ Type:std::vector<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. Vector entries correspond to each nonlinear system.
ignore_variables_for_autoscalingList of variables that do not participate in autoscaling. Vector entries correspond to each nonlinear system.
C++ Type:std::vector<std::vector<std::string>>
Unit:(no unit assumed)
Controllable:No
Description:List of variables that do not participate in autoscaling. Vector entries correspond to each nonlinear system.
off_diagonals_in_auto_scaling0 Whether to consider off-diagonals when determining automatic scaling factors. Vector entries correspond to each nonlinear system.
Default:0
C++ Type:std::vector<bool>
Unit:(no unit assumed)
Controllable:No
Description:Whether to consider off-diagonals when determining automatic scaling factors. Vector entries correspond to each nonlinear system.
resid_vs_jac_scaling_param0 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. Vector entries correspond to each nonlinear system.
Default:0
C++ Type:std::vector<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. Vector entries correspond to each nonlinear system.
scaling_group_variablesName of variables that are grouped together for determining scale factors. (Multiple groups can be provided, separated by semicolon). Vector entries correspond to each nonlinear system.
C++ Type:std::vector<std::vector<std::vector<std::string, std::allocator<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). Vector entries correspond to each nonlinear system.

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)
Options:basic, bt, contact, cp, default, l2, none, project, shell
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)
Options:petsc, moose
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)
Options:HERMITIAN, NON_HERMITIAN, GEN_HERMITIAN, GEN_NON_HERMITIAN, GEN_INDEFINITE, POS_GEN_NON_HERMITIAN, SLEPC_DEFAULT
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)
Options:LARGEST_MAGNITUDE, SMALLEST_MAGNITUDE, LARGEST_REAL, SMALLEST_REAL, LARGEST_IMAGINARY, SMALLEST_IMAGINARY, TARGET_MAGNITUDE, TARGET_REAL, TARGET_IMAGINARY, ALL_EIGENVALUES, SLEPC_DEFAULT
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)
Options:wp, ds
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)
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
Controllable:No
Description:Singleton PETSc options
petsc_options_inameNames of PETSc name/value pairs
C++ Type:MultiMooseEnum
Unit:(no unit assumed)
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
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

multi_system_fixed_pointFalseWhether to perform fixed point (Picard) iterations between the nonlinear systems.
Default:False
C++ Type:bool
Unit:(no unit assumed)
Controllable:No
Description:Whether to perform fixed point (Picard) iterations between the nonlinear systems.
multi_system_fixed_point_convergenceConvergence object to determine the convergence of the multi-system fixed point iteration. If unspecified, defaults to checking that every system is converged (based on their own convergence criterion)
C++ Type:ConvergenceName
Unit:(no unit assumed)
Controllable:No
Description:Convergence object to determine the convergence of the multi-system fixed point iteration. If unspecified, defaults to checking that every system is converged (based on their own convergence criterion)
system_namesNames of the solver systems (both linear and nonlinear) that will be solved
C++ Type:std::vector<SolverSystemName>
Unit:(no unit assumed)
Controllable:No
Description:Names of the solver systems (both linear and nonlinear) that will be solved

Multiple Solver System 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
nonlinear_convergenceName of the Convergence object(s) to use to assess convergence of the nonlinear system(s) solve. If not provided, the default Convergence associated with the Problem will be constructed internally.
C++ Type:std::vector<ConvergenceName>
Unit:(no unit assumed)
Controllable:No
Description:Name of the Convergence object(s) to use to assess convergence of the nonlinear system(s) solve. If not provided, the default Convergence associated with the Problem will be constructed internally.
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_together0 Whether to compute the residual and Jacobian together. Vector entries correspond to each nonlinear system.
Default:0
C++ Type:std::vector<bool>
Unit:(no unit assumed)
Controllable:No
Description:Whether to compute the residual and Jacobian together. Vector entries correspond to each nonlinear system.
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)
Options:POWER, ARNOLDI, KRYLOVSCHUR, JACOBI_DAVIDSON, NONLINEAR_POWER, NEWTON, PJFNK, PJFNKMO, JFNK
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. Outer-vector of this vector-of-vector parameter correspond to each nonlinear system.
C++ Type:std::vector<std::vector<std::string>>
Unit:(no unit assumed)
Controllable:No
Description:Top-level splitting defining a hierarchical decomposition into subsystems to help the solver. Outer-vector of this vector-of-vector parameter correspond to each nonlinear system.
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

Eigenvalue

Input Parameters

Optional Parameters

Fixed Point Iterations Parameters

Eigenvector And Eigenvalue Initialization Parameters

Solver Variable Scaling Parameters

Matrix And Matrix-Free Parameters

Solver Line Search Parameters

Advanced Parameters

Eigen Solver Parameters

Linear Solver Parameters

Linear Solver Parameters

Xfem Fixed Point Iterations Parameters

Petsc Parameters

Multiple Solver System Parameters

Nonlinear Solver Parameters

Solution Normalization Parameters

Restart Parameters