Estimation of kinetic parameters for glycerol/alcohol dehydration reaction systems with incomplete chromatography data sets

Jyh Shyong Chang*, Jin Han Deng, Gow Bin Wang

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

4 Scopus citations

Abstract

There is a shortage of pure ethers available for quantizing the gas chromatograph (GC) peaks that appear during the dehydration reactions of glycerol with alcohols. This problem can be overcome computationally by embedding the carbon-hydrogen-oxygen (CHO) balance optimization in the parameters estimation of the reaction system. A two-stage (TS) parameter estimation method was used to identify ordinary differential equation (ODE) models. This approach minimizes the squared residuals between the derivatives of the fitted values of available measurements and the rate changes of the states, used to estimate the unknown parameters. In this way, the problem of ill-conditioning, encountered in integrating the system equations, can be overcome. The resulting estimates are used as initial guesses for the next stage, in which the final estimated parameters are obtained by traditional minimization of the squared residuals between the estimated states and the measurements. Two examples were examined whose results confirmed the utility of the developed TS parameter estimation method and showed it to be easily implemented with a low requirement for computation time. The first example is a simulation (glycerol ether synthesis from glycerol with TBA) and the second example examines glycerol ether synthesis from glycerol with tert-butyl alcohol at elevated temperatures.

Original languageEnglish
Pages (from-to)185-198
Number of pages14
JournalJournal of the Taiwan Institute of Chemical Engineers
Volume60
DOIs
StatePublished - 01 03 2016

Bibliographical note

Publisher Copyright:
© 2015 Taiwan Institute of Chemical Engineers.

Keywords

  • Dehydration reaction systems
  • Incomplete chromatography data sets
  • Ordinary differential equation models
  • Parameter estimation

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