Permalink
Fetching contributors…
Cannot retrieve contributors at this time
181 lines (113 sloc) 5.02 KB

Logo ESPEI

.. toctree::
   :maxdepth: 1

   self
   installation
   quickstart


ESPEI, or Extensible Self-optimizing Phase Equilibria Infrastructure, is a tool for automated thermodynamic database development within the CALPHAD method. It uses pycalphad for calculating Gibbs free energies of thermodynamic models.

Cu-Mg phase diagram

Cu-Mg phase diagram from a database created with and optimized by ESPEI. See the :ref:`Cu-Mg Example`.

Goals

  1. Offer a free and open-source tool for users to develop multicomponent databases with quantified uncertainty
  2. Enable development of CALPHAD-type models for Gibbs energy, thermodynamic or kinetic properties
  3. Provide a platform to build and apply novel model selection and optimization methods

The implementation for ESPEI involves first fitting single-phase data by calculating parameters in thermodynamic models that are linearly described by the single-phase input data. Then Markov Chain Monte Carlo (MCMC) is used to optimize the candidate models from the single-phase fitting to multi-phase zero-phase fraction data. The benefit of this approach is the automated, simultaneous fitting for many parameters that yields uncertainty quantification, as shown in Otis and Liu High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME. Jom 69, (2017). Single-phase and multi-phase fitting methods are described in Chapter 3 of Richard Otis's thesis.

History

The ESPEI package is based on a fork of pycalphad-fitting. The name and idea of ESPEI are originally based off of Shang, Wang, and Liu, ESPEI: Extensible, Self-optimizing Phase Equilibrium Infrastructure for Magnesium Alloys Magnes. Technol. 2010 617-622 (2010).

Change log

.. toctree::
   :maxdepth: 1
   :hidden:
   :caption: What's new

   CHANGES

See what's new!

.. toctree::
   :maxdepth: 1
   :caption: Tutorials


   cu-mg-example
   input_data


.. toctree::
   :maxdepth: 1
   :caption: Reference

   writing_input
   theory
   recipes
   advanced_schedulers
   api/modules


.. toctree::
   :maxdepth: 1
   :caption: Developer

   contributing
   design


Getting Help

For help on installing and using ESPEI, please join the PhasesResearchLab/ESPEI Gitter room.

Bugs and software issues should be reported on GitHub.

License

ESPEI is MIT licensed.

The MIT License (MIT)

Copyright (c) 2015-2018 Richard Otis
Copyright (c) 2017-2018 Brandon Bocklund

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Citing ESPEI

A publication is in preparation. For now, ESPEI can be cited via the following publication:

R.A. Otis, Z.-K. Liu, High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME, JOM. 69 (2017) 886–892. doi:10.1007/s11837-017-2318-6.

.. only:: html

   Indices and tables
   ==================

   * :ref:`genindex`
   * :ref:`modindex`
   * :ref:`search`