Dakota Reference Manual: ordered_model_fidelities

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ordered_model_fidelities

Specification of an hierarchy of model fidelities, ordered from low to high.

## Specification

Alias: model_fidelity_sequence

Argument(s): STRINGLIST

## Description

A hierarchical surrogate model manages an ordered set of model fidelities, each of which may in turn involve multiple discretization levels (in the case of a simulation model) or additional model recursions.

The ordering is assumed to be from lowest fidelity to highest fidelity, as dictated by an accuracy versus cost trade-off. 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 this model order.

Additional Discussion

Internal to the model, only one low fidelity model instance and one high fidelity model instance are active at any given time, although various optimization and UQ algorithms can be used to traverse deep multilevel and multifidelity hierarchies by activating different model combinations and different response modes within the hierarchical model infrastructure.

## Examples

    model,
        id_model = 'HIERARCH'
        surrogate hierarchical
          ordered_model_fidelities = 'LF' 'MF 'HF'
          correction additive zeroth_order

    model,
        id_model = 'LF'
        simulation
          interface_pointer = 'LF_DRIVER'

    model,
        id_model = 'MF'
        simulation
          interface_pointer = 'MF_DRIVER'

    model,
        id_model = 'HF'
        simulation
          interface_pointer = 'HF_DRIVER'

## See Also

These keywords may also be of interest:

- multilevel_sampling
- polynomial_chaos
- stoch_collocation
- surrogate_based_local