Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
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model_pointer


Identifier for model block to be used by a method

Topics

This keyword is related to the topics:

Specification

Alias: opt_model_pointer

Argument(s): STRING

Default: method use of last model parsed (or use of default model if none parsed)

Description

The model_pointer is used to specify which model block will be used to perform the function evaluations needed by the Dakota method.

Default Behavior

If not specified, a Dakota method will use the last model block parsed. If specified, there must be a model block in the Dakota input file that has a corresponding id_model with the same name.

Usage Tips

When doing advanced analyses that involve using multiple methods and multiple models, defining a model_pointer for each method is imperative.

See block_pointer for details about pointers.

Examples

environment
  tabular_graphics_data
  method_pointer = 'UQ'

method
  id_method = 'UQ'
  model_pointer = 'SURR'
  sampling,
    samples = 10
    seed = 98765 rng rnum2
    response_levels = 0.1 0.2 0.6
                      0.1 0.2 0.6
                            0.1 0.2 0.6
    sample_type lhs
    distribution cumulative

model
  id_model = 'SURR'
    surrogate global,
    dace_method_pointer = 'DACE'
    polynomial quadratic

method
  id_method = 'DACE'
    model_pointer = 'DACE_M'
    sampling sample_type lhs
    samples = 121 seed = 5034 rng rnum2

model
  id_model = 'DACE_M'
  single
  interface_pointer = 'I1'

variables
  uniform_uncertain = 2
    lower_bounds =  0.   0.
    upper_bounds =  1.   1.
    descriptors  = 'x1' 'x2'

interface
  id_interface = 'I1'
  system asynch evaluation_concurrency = 5
    analysis_driver = 'text_book'

responses
  response_functions = 3
  no_gradients
  no_hessians