Document Type
Conference Item
Publication Date
1-1-2009
Abstract
In this work, an artificial neural network approach is used to capture the reactor characteristics in terms of heat and mass transfer based on published experimental data. The developed ANN-based heat and mass transfer coefficients relations were used in a conventional FCR model and simulated under industrial operating conditions. The hybrid model predictions of the melt-flow index and the emulsion temperature were compared to industrial measurements as well as published models. The predictive quality of the hybrid model was superior to other models. This modeling approach can be used as an alternative to conventional modeling methods.
Keywords
fluidized bed reactor, heat transfer, mass transfer, three phase, catalytic reactor, neural networks
Divisions
sch_che
Event Title
International Engineering Convention
Event Location
Damascus, Syria.
Event Dates
11-14 May 2009
Event Type
conference