(371c) Modeling Air Separation Via Pressure-Swing Adsorption in Python for Use in Urea Production

Urea (CH₄N₂O) is an important component of synthetic fertilizers and animal feeds. To produce urea, a source of ammonia is required. Ammonia in turn requires a nitrogen source, and pressure-swing adsorption (PSA) is an increasingly common and low-energy cost method for performing air separation to produce the nitrogen required in the Haber-Bosch process. PSA is modeled in python via four steps: high-pressure adsorption, blow down, purge, and pressurization. These steps are modeled according to the system of PDEs suggested by Ahari et. al. [1]. These PDEs were discretized and solved using the orthogonal collocation method. This system of equations dynamically models air separation using PSA, allowing for easy scale-up and optimization of the cycle schedule. The use of python-based algorithms allows the models to be combined with other process models to create an open-source simulation.

1. S. Ahari*, S. Pakseresht, M. Mahdyarfar, S. Shokri, Y. Zamani, A. Nakhaeipour, and F. Naderi, “Predictive Dynamic Model of Air Separation by Pressure Swing Adsorption”. Chemical Engineering Technology. 29, (1), 2006.