Dakota Reference Manual  Version 6.15
Explore and Predict with Confidence
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unordered_model_fidelities


Specification of an unordered ensemble of low-fidelity approximations

Specification

Alias: approximation_models

Argument(s): STRINGLIST

Description

A non_hierarchical surrogate model manages an unordered set of low-fidelity model approximations, each of which may include hyper-parameter resolution controls (in the case of a simulation model) or additional model recursions.

Any corresponding sequence specifications within methods (e.g., quadrature_order_sequence, sparse_grid_level_sequence, expansion_order_sequence, etc. within stochastic expansion methods) should be synchronized with the order in the model listing.

Internal to the non-hierarchical model, subsets of the model ensemble may be active for any given evaluation, as dictated by the iterative algorithm in use.

Examples

model,
    id_model = 'NONHIERARCH'
    surrogate non_hierarchical
      unordered_model_fidelities = 'LF1' 'LF2'
      truth_model_pointer = 'HF'

model,
    id_model = 'LF1'
    simulation
      interface_pointer = 'LF1_DRIVER'
          solution_level_cost = 1.

model,
    id_model = 'LF2'
    simulation
      interface_pointer = 'LF2_DRIVER'
          solution_level_cost = 2.4

model,
    id_model = 'HF'
    simulation
      interface_pointer = 'HF_DRIVER'
          solution_level_cost = 256.

See Also

These keywords may also be of interest: