(53aq) Thermodynamic Parameter Regression Using Open Source Optimizers
AIChE Spring Meeting and Global Congress on Process Safety
2017
2017 Spring Meeting and 13th Global Congress on Process Safety
Spring Meeting Poster Session and Networking Reception
2017 Spring Meeting and 13th GCPS Poster Reception
Monday, March 27, 2017 - 5:00pm to 7:00pm
Parameterization of activity models and equations of state for multicomponent systems is a complicated endeavor when the number of system components is high. Even when restricting interaction parameters to the binary level, the inherent non-linearity of thermodynamic models often leads to local solutions that are not globally optimal. In this talk, we examine the quality of open source optimizers when applied to thermodynamic parameter regression tasks, using the Python programming environment as a framework to drive Aspen Properties calculations. In particular, we consider techniques designed for discovering global optima (e.g., Particle Swarm Optimization). Finally, we provide practical examples relevant to Acid Gas Treating, such as multicomponent aqueous amine solvent systems.