Dakota 6.9

Released: November 15, 2018
Release Highlights:

  • Dakota can now output method results to HDF5
  • Dakota's graphical user interface (GUI) was updated with several new features including the Dakota Study Wizard.
  • Bayesian calibration capabilities received several enhancments, including model evidence calculation with Monte Carlo sampling and 2nd-order local Laplace approximation

Dakota 6.8

Released: May 15, 2018
Release Highlights:

  • dprepro was completely re-written and has many new features, including the ability to execute arbitrary Python scripting in templates
  • Dakota's graphical user interface (GUI) was updated with many new features and bugfixes
  • Dakota now includes a suite of gradient-based optimization algorithms from the SNL-developed Rapid Optimization Library (ROL).
  • Bayesian calibration capabilities received several enhancements, including improved concurrency in evaluating optimal experimental designs


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. The Dakota toolkit provides a flexible, extensible interface between such simulation codes and its iterative systems analysis methods, which include:

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