Dakota 6.18

Highlight: Generalized Approximate Control Variate Method for Multifidelity Sampling

Dakota can now search over directed acyclic graphs to identify the best model inter-relationships for multifidelity sampling.

Enabling / Accessing:

As part of the approximate_control_variate (ACV) method for multifidelity sampling, the new search_model_graphs option activates the generalized ACV capability that identifies the most performant set of control variate pairings among the models in the multifidelity ensemble.


Refer to DAG recursion types under search_model_graphs.

Highlight: Updated User Resources

Dakota’s website has received a refresh. Documentation has moved to GitHub.io and Dakota downloads are now offered as GitHub Releases.

Enabling / Accessing:


See the release notes for further details.