We released version 2.7 of OpenPNM this morning. The changelog can be found on Github.
The main point of note for this release is that it will be the last of the Version 2 line. We are planning to make some important changes, particularly to the way that transport conductances are calculated. Not sure when the official release will be ready, but you can always checkout the dev
The OpenPNM team has put a huge amount of effort into version 2.6, as can be seen by the very long list of changes below. Head over to https://github.com/PMEAL/OpenPNM to get the latest code, or do conda update openpnm
set_outflow_BCstitch_poresset_rate_BC now optionally accepts total_ratename to settings_uuid_validate_data_healthshow_histsettingsextendstitchload_projectplot_conns and plot_coords_get_solver behavior to fall back to spsolveMultiPhase't_schemes'SalomeReactiveTransientTransporttopotools.dimensionalityImportedReactiveTransportOur new automated release process does many nice things including generating the release notes based on merge commit messages. You can browse the change to version 2.5 (and 2.4 since we didn't post an announcement for that one) here.
Version 2.6 will also be landing soon, with some important upgrades to the conduit conductivity models.
Version 2.3 is now available on PyPI. You can upgrade to it using ``pip install --upgrade openpnm`` at your conda prompt.
This version is a significant update over its predecessor. Valuable features include automatic property dependency checking ACROSS objects, improvements in the Mixture class (though it's still considered a beta feature), full implementation of our Nernst-Planck-Poisson solvers (to be published in Computers & Geosciences soon), and massively improved documentation in the algorithms (particularly the settings). The full release notes can be found on Github.
OpenPNM has received a second round of funding from CANARIE! The funding will allow the continued development of OpenPNM's multiphysics capabilities. The previous mandate allowed us to include advection-diffusion and Nernst-Planck-Poisson solvers and much more. This new funding will continue along these lines by incorporating solid mechanics, solid-phase partitioning, and other advanced features. We will also focus more on supporting high-performance numerical solvers including GPU based options. The funding will last for 3 years, and it's exciting to see what the future holds!
The PMEAL team at U of Waterloo has just received funding through an NSERC Engage grant to start a collaboration with Object Research Systems to add OpenPNM to their Dragonfly visualization package. This grant provides $25k for a 6 month project, to pay students on the PMEAL team to code the interface. This a big development for OpenPNM as it will expose many new users to the package and allow a whole new way to work with pore networks. This 6 month project is just kicking off now, so stay tuned for further developments.
The Dragonfly software package is available to academics free of charge, and is shipped with all Zeiss Xradia tomography machines.
A full announcement of V2 is forthcoming very soon, but for now it's possible to download the beta version of 2.0 from Github (master branch) or from PyPI using "pip install openpnm==2.0.0-b0". The conversion to V2 has been a huge effort and we're very happy with the results, although we're glad to be finally finished! Enjoy.
The OpenPNM Team has recently received funding from the CANARIE agency. This significant amount of funding will pay for a software developer to build a GUI-frontend to the software, as well as a research associate to expand the back end capabilities to handle substantially larger networks. Our goal is to perform simulations on networks with billions of pores or more, and to easily handle multi-physics scenarios. The funding was received under the 'software reuse' program, which as the name suggests aims to support existing software platforms to become more user friendly and more widely applicable. This funding will last for 2 years and is an amazing opportunity for OpenPNM to continue to grow.
Congratulations to Amin Sadeghi, PhD candidate with Prof. Gostick, for his recently published work using OpenPNM model diffusion hierarchical, multiscale catalyst particles. This work was published in The Chemical Engineering Journal.
The OpenPNM team has prepared a paper outlining the architecture and capabilities of our software package. It is now officially available in the IEEE journal Computers in Science and Engineering. The developers would appreciate if people cited this article if they use OpenPNM in any publication.