ordered_model_fidelities

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

Specification

• Alias: model_fidelity_sequence

• Arguments: STRINGLIST

Child Keywords:

Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
Optional		correction	Correction approaches for surrogate models

Description

An ensemble surrogate model can manage 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 hierarchical usage of an ensemble surrogate 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 ensemble
   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'