Dakota vs OpenPISCO

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.

OpenPisco is an open source research and development platform for topology optimization using the level-set method. It combines optimization algorithms, direct and adjoint analyses, remeshing tools and level-set algorithms, with methods for fixed-mesh shape capturing and body-fitted mesh shape tracking. The design process supports grids, unstructured meshes and body-fitted meshes, and includes an interface to MMG3D for remeshing. Users can work through a Python library and API, the OpenPiscoCL command-line application, or a graphical application. The Python interface targets developers and advanced users; the command line supports automation, batch processing and HPC execution, while the GUI is suited to visualization. Plugins allow custom mesh readers, optimization algorithms and physics solvers to be added without changing existing source code. Documented external solver options include Code_Aster, FreeFem, ZSet and OpenFOAM; an internal finite element solver is also available. Built on the Muscat library, OpenPisco is intended for industrial and academic research, including rapid prototyping of topology optimization methods. Documentation reports installation on Ubuntu Linux, macOS, Windows 10 and WSL 20.04.