Opyrability - Process Operability Analysis in Python.

Welcome to opyrability, a Python-based package for performing Process Operability analysis.

opyrability is developed and maintained by Victor Alves at Carnegie Mellon University. Its development began in the Control, Optimization and Design for Energy and Sustainability (CODES) Group at West Virginia University by Victor Alves and San Dinh.

Authors:

• Victor Alves
• San Dinh
• John Kitchin
• Vitor Gazzaneo
• Juan C. Carrasco
• Fernando V. Lima

Documentation and Process Operability Principles

Full documentation and discussion regarding process operability principles are available in opyrability's online portal.

Citing Us

To cite us, please use the following BibTeX entry below:

@article{Alves2024, 
doi = {10.21105/joss.05966}, 
url = {https://doi.org/10.21105/joss.05966}, 
year = {2024}, 
publisher = {The Open Journal}, 
volume = {9}, 
number = {94}, 
pages = {5966}, 
author = {Victor Alves and San Dinh and John R. Kitchin and Vitor Gazzaneo and Juan C. Carrasco and Fernando V. Lima}, 
title = {Opyrability: A Python package for process operability analysis}, journal = {Journal of Open Source Software} 
}

A paper describing opyrability's main functionalities is available in the Journal of Open Source Software (JOSS):

Installation

From PyPI (Windows, Linux and macOS):

pip install opyrability

This installs all required dependencies, including the default Pounce solver. The optional IPOPT backend (method='ipopt') needs cyipopt, which is easiest to install from conda:

conda install -c conda-forge cyipopt