VariableMapping System

Overview

The mapping system is dedicated to holding objects which map high-dimensional solution vectors to lower-dimensional spaces (latent spaces). These objects do not get executed on their own, but only used in other objects which need mapping functionality.

Creating a VariableMapping

A mapping object can be created by inheriting from VariableMappingBase and overriding the methods in the base class. These methods describe the mapping from high to low dimensional spaces and the corresponding inverse mapping procedures.

Using a Mapping

The VariableMappings block

In an input file, one can create Mapping Objects by specifying them in the [VariableMappings] block.

Mapping from high- to low-dimensional spaces

High-dimensional data can be mapped to lower-dimensional spaces using MappingReporter. This can either map the fields in a ParallelSolutionStorage or map multiple solution variables in a given nonlinear system. The results are stored in a standard vector format in the reporter data structure.

Inverse mapping from low- to high-dimensional spaces

Low-dimensional data can be mapped to higher-dimensional spaces using InverseMapping. This can either utilize surrogate models to determine the low-dimensional vectors given a specific set of model parameters or take a custom low-dimensional vector and use inverse mapping to populate AuxVariables with the reconstructed approximate fields.

MappingInterface

By inheriting from MappingInterface, classes can easily fetch mapping objects from the object warehouse using the helper functions. Good examples are the MappingReporter and InverseMapping.

Example Input File Syntax

[VariableMappings]
  [pod_mapping]
    type = PODMapping
    solution_storage = parallel_storage
    variables = "v"
    num_modes_to_compute = '2'
    extra_slepc_options = "-svd_monitor_all"
  []
[]

Available Objects

Stochastic Tools App
PODMappingClass which provides a Proper Orthogonal Decomposition-based mapping between full-order and reduced-order spaces.

Available Actions

Stochastic Tools App
AddVariableMappingActionAdds Mapping objects from a VariableMappings block.

(contrib/moose/modules/stochastic_tools/test/tests/variablemappings/pod_mapping/pod_mapping_main.i)

[StochasticTools]
[]

[Distributions]
  [S_dist]
    type = Uniform
    lower_bound = 0
    upper_bound = 10
  []
  [D_dist]
    type = Uniform
    lower_bound = 0
    upper_bound = 10
  []
[]

[Samplers]
  [sample]
    type = MonteCarlo
    num_rows = 4
    distributions = 'S_dist D_dist'
    execute_on = initial
    min_procs_per_row = 2
  []
[]

[MultiApps]
  [worker]
    type = SamplerFullSolveMultiApp
    input_files = sub.i
    sampler = sample
    mode = batch-restore
    min_procs_per_app = 2
  []
[]

[VariableMappings]
  [pod_mapping]
    type = PODMapping
    solution_storage = parallel_storage
    variables = "v"
    num_modes_to_compute = '2'
    extra_slepc_options = "-svd_monitor_all"
  []
[]

[Transfers]
  [param_transfer]
    type = SamplerParameterTransfer
    to_multi_app = worker
    sampler = sample
    parameters = 'Kernels/source_v/value BCs/right_v/value'
  []
  [solution_transfer]
    type = SerializedSolutionTransfer
    parallel_storage = parallel_storage
    from_multi_app = worker
    sampler = sample
    solution_container = solution_storage
    variables = 'v'
    serialize_on_root = true
  []
[]

[Reporters]
  [parallel_storage]
    type = ParallelSolutionStorage
    variables = 'v'
    outputs = none
  []
  [svd_output]
    type = SingularTripletReporter
    variables = 'v'
    pod_mapping = pod_mapping
    execute_on = FINAL
  []
[]

[Outputs]
  [out]
    type = JSON
    execute_on = FINAL
    execute_system_information_on = NONE
  []
[]

Overview
Creating a VariableMapping
Using a Mapping
Example Input File Syntax
Available Objects
Available Actions