Dakota vs Plato

Dakota provides software for optimization and uncertainty quantification using computational models. Its methods cover optimization, uncertainty quantification, parameter estimation, and sensitivity or variance analysis. These capabilities can be combined into strategies such as hybrid optimization, surrogate-based optimization and optimization under uncertainty. The C++ toolkit connects simulation codes with iterative systems-analysis methods, and Dakota lists MPI for parallel distributed-memory communication. The project describes engineering analysts using it to explore designs and assess confidence in computational predictions. Prebuilt binaries are available for macOS, Windows and Red Hat Enterprise Linux 7 and 8; other platforms require building from source. Installation instructions also describe an optional PYTHONPATH setup for the dakota.interfacing Python module. Dakota versions 5.0 and newer are available under the GNU Lesser General Public License. Some optional numerical libraries, including DOT, NLPQLP and NPSOL/NLSSOL, require separate commercial licenses. Documentation for releases 6.17 and later is available through the documentation site, with older manuals available for download. User support is directed to GitHub Discussions, and the project offers introductory and methods-focused screencasts.

Plato is a Linux command-line platform for topology optimization, helping designers develop geometry that meets functional requirements. It solves topology and shape design problems with adjoint methods for gradient-based optimization. Documented objectives include increasing stiffness or heat flow and reducing stress. Plato coordinates workflows involving geometry, meshing, and physics simulation packages. It includes the open-source physics code Plato Analyze and can also be used with a growing set of internal Sandia physics codes. Research features described for the platform include structural optimization across multiple materials, uncertainty-aware structural optimization, level-set methods, and a massively parallel kernel filter. A graphical interface is in development for selected applications. The open-source version is listed at free, with a limited set of objectives and constraints. A license is required to obtain an installation package.