release

Post, May 17, 2022 • Highlight: Multifidelity UQ Methods Dakota 6.16 significantly extends capabilities for multifidelity uncertainty quantification (MF UQ) based on random sampling, including iterated versions of approximate control variate (ACV) and multifidelity Monte Carlo (MFMC), new solution modes (online pilot, offline pilot, and pilot projection), new final statistics goals supporting estimator selection and tuning, online cost recovery...

Post, November 15, 2022 • Highlight: Integrated User Manual Dakota 6.17 includes a beta version of a new Sphinx-based integrated user manual. It aggregates content from the historical User’s, Theory, and Reference manuals, as well as the Dakota website. Feedback on this new compendium is invited. Enabling / Accessing: Primarily from https://dakota.sandia.gov, also in <dakota_src>/docs/user....

Post, May 24, 2023 • 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...

Post, November 14, 2023 • Announcing Dakota Version 6.19 Dakota 6.19 is officially available for download. Highlight: New sampling-based method for Sobol’ main effects Based on [LM16], Dakota can now obtain estimates of first order Sobol’ indices (main effects) from sampling studies. Previous versions of Dakota could estimate main and total effects using a “pick...