Hydrodynamics and mass
transfer in trickle-bed reactors:
Ion Iliuta*, Arturo Ortiz-Arroyo, Faïçal Larachi (corresponding
author), Bernard P.A. Grandjean
Department of Chemical Engineering & CERPIC, Laval University, Québec, Canada G1K 7P4
*on leave from Department of Chemical Engineering, Faculty of Industrial Chemistry,
University Politehnica of Bucharest, Polizu 1, 78126 Bucharest, Romania
Laboratoire des Sciences du Génie Chimique, CNRS-ENSIC
1 Rue Grandville, BP 451, 54001 Nancy, France
Chem. Eng. Sci., 54, 5329-5337 (1999)
Errata: In Equations 16-19-22 of Table 2, ReL and/or ReG should have read as ReL' , ReG'
Abstract: The fluid dynamic and the gas-liquid mass transfer characteristics of trickle-bed reactors were revisited and their quantification methods reevaluated based on extensive experimental historic flow data bases (22,000 experiments) set up from the open literature published over the last forty years. The state-of-the-art of trickle bed fluid dynamics was summarized and a set of unified and updated estimation methods relying on neural-network-dimensional analysis-phenomenological hybrid approaches were discussed.
You can get the code.zip file to compute (Fortran) with neural models given in Table 2 of the paper
You may also download our Excel worksheet Trickle-bed simulator to simulate mass transfer, pressure drop, liquid holdup and flow regime transition.
The neural correlations were developped with the software NNFit