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The inverse methodology of parameter estimation for model adjustment, design, simulation, control and optimization of fluid catalytic cracking (FCC) risers
- Source :
- Journal of Chemical Technology & Biotechnology. 84:343-355
- Publication Year :
- 2009
- Publisher :
- Wiley, 2009.
-
Abstract
- BACKGROUND: A simple model is required to produce a fast computational code that is sufficiently precise to be used for the design, simulation, control and optimization of fluid catalytic cracking (FCC) risers. This work experimentally validates and adjusts a simplified FCC riser model using available experimental data, and proposes utilization of the inverse problem of the parameter estimation method to fit any existing kinetic model to a specific feedstock/catalyst set for general application. RESULTS: The model adjustment procedure was repeated for nine different experimental sets and the best fitting parameters were obtained statistically. The fitting parameters were utilized to predict the riser output conditions for the other 18 data sets. The numerical results are in good quantitative and qualitative agreement with the experimental data. The model was then utilized to simulate an industrial FCC riser, predicting concentrations and temperature profiles from the bottom to the top of the riser. CONCLUSIONS: The results suggest that the simplified model, combined with the proposed inverse methodology could produce accurate results for any feedstock/catalyst set, once the kinetic model is known for a particular feedstock/catalyst set. Therefore, a low computational time and accurate tool is made available for simulation, control, design and optimization of FCC risers. Copyright © 2008 Society of Chemical Industry
- Subjects :
- Work (thermodynamics)
Engineering
Renewable Energy, Sustainability and the Environment
business.industry
Estimation theory
General Chemical Engineering
Organic Chemistry
Experimental data
Inverse
Inverse problem
Raw material
Fluid catalytic cracking
Pollution
Inorganic Chemistry
Set (abstract data type)
Fuel Technology
Control theory
business
Waste Management and Disposal
Simulation
Biotechnology
Subjects
Details
- ISSN :
- 10974660 and 02682575
- Volume :
- 84
- Database :
- OpenAIRE
- Journal :
- Journal of Chemical Technology & Biotechnology
- Accession number :
- edsair.doi...........d3056c59ca7dce4defb376add928033d