Neural network-based heat and mass transfer coefficients for the hybrid modeling of fluidized reactors

• Main Authors: Mjalli, Farouq Sabri, Al-Mfargi, A.
• Format: Article
• Published: Taylor & Francis 2010
• Subjects: Q Science (General)
• Online Access: http://eprints.um.edu.my/15355/; https://doi.org/10.1080/00986440903088819

The complex flow patterns induced in fluidized bed catalytic reactors and the competing parameters affecting the mass and heat transfer characteristics make the design of such reactors a challenging task to accomplish. The models of such processes rely heavily on predictive empirical correlations fo...