FCCU simulation based on first principle and artificial neural network models

Maria Miheţ, Vasile Mircea Cristea, Paul Şerban Agachi

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


A first principle model has been developed for the reactor-regenerator system based on construction and operating data from an industrial fluid catalytic cracking unit (FCCU). The first principle model takes into account the main FCCU subsystems: reactor riser, regenerator, stripper, catalyst circulation lines, air blower, wet gas compressor and main fractionator. A five-lump kinetic scheme has been considered for the reactions taking place in the reactor riser. Subsequently, an artificial neural network (ANN) model has been built for the complex FCCU system. The dynamic simulator, based on the previously developed first principle model, served as the source of reliable data for ANN design, training and testing. The ANN developed model was successfully trained and tested. Comparison between first principle and neural network based model leads to a very good match between the two models. Results show the substantial reduction of the computation time featured by the ANN model compared to the first principle model, demonstrating its potential use for real-time implementation in model-based control algorithms.

Original languageEnglish
Pages (from-to)878-884
Number of pages7
JournalAsia-Pacific Journal of Chemical Engineering
Issue number6
Publication statusPublished - Nov 2009

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Renewable Energy, Sustainability and the Environment
  • Waste Management and Disposal


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