Dakota 6.20

Announcing Dakota Version 6.20

Dakota 6.20 is officially available for download.

Highlight: Multilevel Best Linear Unbiased Estimator (ML BLUE)

ML BLUE ([SU20]) is a new multifidelity sampling-based approach for UQ, distinguished from other estimators through its use of sample allocations based on model groupings. It has motivated a number of other general extensions to Dakota’s MF sampling methods, including multi-batch concurrency and under-relaxation of predicted sample increments (see MLMF Sampling below), and it is full featured in its support for group size throttling, shared versus independent pilot sampling, online versus offline solution modes, and hyper-parameter model tuning.

Enabling / Accessing: new method specification option for multifidelity sampling: multilevel_blue.

Documentation: Refer to the reference documentation starting from multilevel_blue for additional information. A number of numerical examples using standard Dakota benchmarks are available under dakota/test in the release distribution.

Highlight: New options for using MCMC algorithms from the MUQ library

When selecting bayes_calibration muq under the method section of a Dakota input file, the user can now select the ‘mala’ MCMC algorithm (in addition to the already supported four algorithms). The user can now also select values for parameters in each of these algorithms.

Enabling / Accessing:

Dakota currently interfaces with five MCMC algorithms from MUQ: metropolis_hastings, adaptive_metropolis, delayed_rejection, dram, and mala. Dakota also allows the user to select values for seven parameters related to these five methods (the prefix in each parameter indicates which MCMC algorithm the parameter relates itself to): dr_num_stages, dr_scale_type, dr_scale, am_period_num_steps, am_starting_step, am_scale, and mala_step_size.

MUQ is an optional feature of Dakota and can be enabled when building from source by setting the HAVE_MUQ CMake variable to ON. In release 6.20, pre-built Linux binaries include MUQ.


See the eight keywords mala, am_period_num_steps, am_scale, am_starting_step, dr_num_stages, dr_scale, dr_scale_type, and mala_step_size.

For complete release notes, visit https://snl-dakota.github.io/docs/6.20.0/users/misc/releasenotes/620.html