1547-5905/asset/AIC_left.gif?v=1&s=43a3d567c64d3d5d712c0af6c2cacb1e1bcc1a2b)
1547-5905/asset/AIC_right.gif?v=1&s=518efadeedca9ceeef271499f690fdebd2ed9164)
Reactors, Kinetics, and Catalysis
Optimal design of nonlinear temperature programmed reduction experiments
Article first published online: 19 JAN 2011
DOI: 10.1002/aic.12485
Copyright © 2011 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Heidebrecht, P., Sundmacher, K. and Biegler, L. T. (2011), Optimal design of nonlinear temperature programmed reduction experiments. AIChE J., 57: 2888–2901. doi: 10.1002/aic.12485
Publication History
- Issue published online: 9 SEP 2011
- Article first published online: 19 JAN 2011
- Accepted manuscript online: 3 NOV 2010 07:59AM EST
- Manuscript Revised: 19 OCT 2010
- Manuscript Received: 2 JUL 2010
Funded by
- Postdoc-Programme of the German Academic Exchange Service (DAAD)
- Abstract
- Article
- References
- Cited By
Keywords:
- temperature programmed reduction;
- experimental design;
- optimal control;
- model reduction
Abstract
We propose the application of nonconstant temperature gradients to improve the quality of temperature programmed reduction (TPR) experiments with respect to parameter estimation and model discrimination. This leads to TPR experiments with nonlinear temperature profiles (N-TPR). To determine optimal profiles for the temperature gradient, optimal control problems are set up and solved numerically. The results show that N-TPR experiments can be significantly better than traditional linear TPR experiments for many different scenarios. To implement these results in practice, we develop and demonstrate reduced optimization problem formulations, which can be solved faster and more reliably than the original formulation, with very similar results. © 2011 American Institute of Chemical Engineers AIChE J, 2011