Sobol

The Sobol sampler object generates the necessary matrices of samples to perform a variance-based sensitivity analysis, refer to Saltelli (2002) for complete details.

Input Parameters

  • sampler_aThe 'sample' matrix.

    C++ Type:SamplerName

    Controllable:No

    Description:The 'sample' matrix.

  • sampler_bThe 're-sample' matrix.

    C++ Type:SamplerName

    Controllable:No

    Description:The 're-sample' matrix.

Required Parameters

  • execute_onLINEARThe list of flag(s) indicating when this object should be executed, the available options include FORWARD, ADJOINT, HOMOGENEOUS_FORWARD, ADJOINT_TIMESTEP_BEGIN, ADJOINT_TIMESTEP_END, NONE, INITIAL, LINEAR, NONLINEAR, POSTCHECK, TIMESTEP_END, TIMESTEP_BEGIN, MULTIAPP_FIXED_POINT_END, MULTIAPP_FIXED_POINT_BEGIN, FINAL, CUSTOM.

    Default:LINEAR

    C++ Type:ExecFlagEnum

    Options:FORWARD, ADJOINT, HOMOGENEOUS_FORWARD, ADJOINT_TIMESTEP_BEGIN, ADJOINT_TIMESTEP_END, NONE, INITIAL, LINEAR, NONLINEAR, POSTCHECK, TIMESTEP_END, TIMESTEP_BEGIN, MULTIAPP_FIXED_POINT_END, MULTIAPP_FIXED_POINT_BEGIN, FINAL, CUSTOM, PRE_MULTIAPP_SETUP

    Controllable:No

    Description:The list of flag(s) indicating when this object should be executed, the available options include FORWARD, ADJOINT, HOMOGENEOUS_FORWARD, ADJOINT_TIMESTEP_BEGIN, ADJOINT_TIMESTEP_END, NONE, INITIAL, LINEAR, NONLINEAR, POSTCHECK, TIMESTEP_END, TIMESTEP_BEGIN, MULTIAPP_FIXED_POINT_END, MULTIAPP_FIXED_POINT_BEGIN, FINAL, CUSTOM.

  • limit_get_global_samples429496729The maximum allowed number of items in the DenseMatrix returned by getGlobalSamples method.

    Default:429496729

    C++ Type:unsigned long

    Controllable:No

    Description:The maximum allowed number of items in the DenseMatrix returned by getGlobalSamples method.

  • limit_get_local_samples429496729The maximum allowed number of items in the DenseMatrix returned by getLocalSamples method.

    Default:429496729

    C++ Type:unsigned long

    Controllable:No

    Description:The maximum allowed number of items in the DenseMatrix returned by getLocalSamples method.

  • limit_get_next_local_row429496729The maximum allowed number of items in the std::vector returned by getNextLocalRow method.

    Default:429496729

    C++ Type:unsigned long

    Controllable:No

    Description:The maximum allowed number of items in the std::vector returned by getNextLocalRow method.

  • max_procs_per_row4294967295This will ensure that the sampler is partitioned properly when 'MultiApp/*/max_procs_per_app' is specified. It is not recommended to use otherwise.

    Default:4294967295

    C++ Type:unsigned int

    Controllable:No

    Description:This will ensure that the sampler is partitioned properly when 'MultiApp/*/max_procs_per_app' is specified. It is not recommended to use otherwise.

  • min_procs_per_row1This will ensure that the sampler is partitioned properly when 'MultiApp/*/min_procs_per_app' is specified. It is not recommended to use otherwise.

    Default:1

    C++ Type:unsigned int

    Controllable:No

    Description:This will ensure that the sampler is partitioned properly when 'MultiApp/*/min_procs_per_app' is specified. It is not recommended to use otherwise.

  • resampleTrueCreate the re-sample matrix for second-order indices.

    Default:True

    C++ Type:bool

    Controllable:No

    Description:Create the re-sample matrix for second-order indices.

  • seed0Random number generator initial seed

    Default:0

    C++ Type:unsigned int

    Controllable:No

    Description:Random number generator initial seed

Optional Parameters

  • control_tagsAdds user-defined labels for accessing object parameters via control logic.

    C++ Type:std::vector<std::string>

    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

    Controllable:No

    Description:Set the enabled status of the MooseObject.

Advanced Parameters

References

  1. Andrea Saltelli. Making best use of model evaluations to compute sensitivity indices. Computer Physics Communications, 145(2):280–297, 2002. URL: https://doi.org/10.1016/S0010-4655(02)00280-1.[BibTeX]