Simulation and Multi‐criteria Optimization under Uncertain Model Parameters of a Cumene Process

Since experimentation is expensive with increasing computation power the significance of modeling, simulation, and optimization in process development has grown. Quite often in such models some parameters are uncertain, e.g., due to high variance in experimental data used for their estimation. Metho...

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Bibliographic Details
Published in:Chemie ingenieur technik 2017-05, Vol.89 (5), p.665-674
Main Authors: Asprion, Norbert, Blagov, Sergej, Böttcher, Roger, Schwientek, Jan, Burger, Jakob, Harbou, Erik, Bortz, Michael
Format: Article
Language:English
Subjects:
Computer simulation
Cumene
Decision support
Mathematical models
Multi‐criteria optimization
Optimization
Parameter uncertainty
Parameters
Robust optimization
Robustness
Sensitivity analysis
Stochastic optimization
Uncertainty
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Summary:Since experimentation is expensive with increasing computation power the significance of modeling, simulation, and optimization in process development has grown. Quite often in such models some parameters are uncertain, e.g., due to high variance in experimental data used for their estimation. Methods for investigating the impact of uncertain model parameters in the simulation and a new extension of an adaptive multi‐criteria optimization method to account for these uncertainties are described and demonstrated based on a cumene process. The application of methods to investigate the impact of uncertainty on simulation and multi‐criteria optimization results is demonstrated and discussed for the cumene process. Results for stochastic and robust optimization are compared with optimization results of individual uncertainty scenarios.
ISSN:0009-286X
1522-2640
DOI:10.1002/cite.201600098