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Process Systems Engineering

A novel type of equipment for reactive distillation: Model development, simulation, sensitivity and error analysis

  1. Erik von Harbou1,*,
  2. Markus Schmitt2,
  3. Christoph Großmann2,
  4. Hans Hasse1

Article first published online: 15 NOV 2012

DOI: 10.1002/aic.13947

Issue

AIChE Journal

AIChE Journal

Volume 59, Issue 5, pages 1533–1543, May 2013

Additional Information

How to Cite

von Harbou, E., Schmitt, M., Großmann, C. and Hasse, H. (2013), A novel type of equipment for reactive distillation: Model development, simulation, sensitivity and error analysis. AIChE J., 59: 1533–1543. doi: 10.1002/aic.13947

Author Information

  1. 1

    Dept. of Mechanical and Process Engineering, Laboratory of Engineering Thermodynamics, University of Kaiserslautern, Kaiserslautern, Germany

  2. 2

    Global Process Technology, BASF SE, Ludwigshafen, Germany

*Correspondence concerning this article should be addressed to E. von Harbou at erik.vonharbou@mv.uni-kl.de.

Publication History

  1. Issue published online: 11 APR 2013
  2. Article first published online: 15 NOV 2012
  3. Accepted manuscript online: 16 OCT 2012 08:49AM EST
  4. Manuscript Revised: 5 OCT 2012
  5. Manuscript Received: 22 JUL 2012

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Keywords:

  • reactive distillation;
  • tray;
  • modeling and simulation;
  • data reconciliation;
  • sensitivity analysis

A simulation study of heterogeneously catalyzed reactive distillation experiments carried out with the D + R tray, a novel type of laboratory equipment, is presented. One advantage of the D + R tray is that reaction and distillation are alternating stage-wise, in a well-defined way that can be modeled straightforwardly. An equilibrium stage model is used to describe the distillation and a plug flow reactor model to describe the catalyst bed reactors. The model parameters are derived from a systematic experimental characterization of the D + R tray both as a reactor and as a distillation unit. A validated physicochemical fluid property model is used. The primary experimental data are reconciled. Results from the predictive simulations are in good agreement with the experimental results. The influence of errors in the input parameters on the simulation results is investigated by means of a sensitivity and error analysis. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1533–1543, 2013

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