The Dakota project delivers both state-of-the-art research and robust, usable software for optimization and UQ. Broadly, the Dakota software’s advanced parametric analyses enable design exploration, model calibration, risk analysis, and quantification of margins and uncertainty with computational models. Read More.
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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 […]
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Dakota 6.17
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. Highlight: User Support Moves to […]
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Dakota 6.16
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 through metadata, and improved numerical solution […]
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USNCCM 17
The Dakota team is organizing a minisymposium at the upcoming 17th U.S. National Congress on Computational Mechanics, which will be held in Albuquerque, NM during the week of July 23-27, 2023. Driven by Sandia National Laboratories’ applications, the Dakota project (http://dakota.sandia.gov) invests in both state-of-the-art research and robust, usable software for optimization and uncertainty quantification […]
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Retirement of dakota-users
The Dakota team is excited to announce that user support has moved to GitHub Discussions. The dakota-users listserv is now officially retired. Although dakota-users has served our community well over the years, GitHub Discussions has numerous features that we believe warrant this change. Some of these include: Searchable history Threaded discussions markdown formatting LaTeX style mathematical expressions Voting, best answer […]