2006 AIChE Annual Meeting
(301o) Evaluation of the Pure Component Parameterization Methodology on Mixture Property Predictions for Thermodynamic Equations of State Using Terrain Methodology
Authors
This research focuses on studying the predictive power of a complex thermodynamic equation of state (here, SAFT-VR EOS) that will, in turn, improve one's ability to model these complex systems in the future. This work attempts to characterize and maximize predictive power by mitigating spurious conclusions that are based on results from local minimization schemes and, thus, allow for more definitive conclusions on the properties of systems in the absence of experimental data. To this end, this work employs global terrain methodology [2] an advanced global optimization technique and applies it to the field of thermodynamic modeling. Additionally, analyses on the effects of multiple parameter-sets and binary interaction parameters on the prediction of mixture properties will be discussed. Through this work, parameter rules will be developed that will allow for the optimal prediction of pure component properties.
References:
1. Swaminathan, S. and Visco, D. P. Jr., (2004) "Exploring the Importance of Pure Component Parameterization Procedures in Predicting Mixture Phase Properties via Equations of State", presented at AIChE annual meeting at Austin, TX.
2. Lucia, A.; Feng, Y. (2002), Global terrain methods, Computers and Chemical Engineering, 26, 529-546.