.. _model-surrogate-ensemble-ordered_model_fidelities:

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


.. toctree::
   :hidden:
   :maxdepth: 1

   model-surrogate-ensemble-ordered_model_fidelities-correction


**Specification**

- *Alias:* model_fidelity_sequence 

- *Arguments:* STRINGLIST


**Child Keywords:**

+-------------------------+--------------------+--------------------+-----------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword     | Dakota Keyword Description                    |
|                         | Group              |                    |                                               |
+=========================+====================+====================+===============================================+
| Optional                                     | `correction`__     | Correction approaches for surrogate models    |
+----------------------------------------------+--------------------+-----------------------------------------------+

.. __: model-surrogate-ensemble-ordered_model_fidelities-correction.html



**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**



.. code-block::

    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'




