280674 Process Simulation of a Bi-Phasic Reaction: Hydrogenation of p-Hydroxybenzaldehyde

Tuesday, October 30, 2012: 3:55 PM
322 (Convention Center )
C. E. Odafin1, S. B. Gebreyohannes1, T. N. Pham2, Jimmy A. Faria2, B. J. Neely1 and K. A. M. Gasem1, (1)School of Chemical Engineering, Oklahoma State University, Stillwater, OK, (2)School of Chemical, Biological and Materials Engineering, University of Oklahoma, Norman, OK

Bi-phasic catalytic reactions provide an efficient method for the conversion of pyrolysis oil to usable biofuel. The simulation of the hydrogenation of p-hydroxybenzaldehyde was used as a prototype to develop a bi-phasic reactor model describing both reaction kinetics and phase separation. The effects of phase behavior modeling on bi-phasic reactor model predictions were then investigated. Specifically, case studies were conducted to examine the prediction accuracy of the Non-Random, Two-Liquid (NRTL) activity coefficient model equipped with parameters from: UNIversal Functional Activity Coefficient (UNIFAC) group contributions, Quantitative Structure–Property Relationships (QSPR) generalized NRTL parameters (NRTL-QSPR), and regressed NRTL model parameters (NRTL_R). Further, sensitivity analyses were conducted to evaluate the influence of the kinetic parameters on reactor model predictions.

Kinetic data on the p-hydroxybenzaldehyde system from the OU CIRE research group was used in the simulation. Aspen Plus and Visual Basic for Application (VBA) were used to model the biphasic reaction process, accounting for both the reaction and phase separation. A user-defined MS Excel (VBA) reaction model was designed, and Aspen Simulation Workbook (ASW) was used to link the reaction model to the phase separation model on Aspen Plus. The NRTL model parameters estimated from the NRTL-QSPR model demonstrate better phase equilibria property predictions than those generated using the UNIFAC–predicted models parameters. The sensitivity analyses indicate that the adsorption and deactivation constants have significant impact on the bi-phasic model predictions of p-hydroxybenzaldehyde hydrogenation.

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See more of this Session: Catalytic Biofuels Refining II
See more of this Group/Topical: Fuels and Petrochemicals Division