FLOODING CAPACITY IN PACKED
Database, Correlations and Analysis
Faïçal Larachi,* Bernard P.A. Grandjean
I&EC Research , 40, 476-487 (2001)
Errata: Equation (2) and (3) should be read as:
Abstract: Experimental results on the flooding capacity of randomly dumped packed
beds were collected from the literature to generate a working database.
The reported measurements were first used to review the accuracy of existing
predicting tools in that field. A total of 14 correlations were extracted
from the literature and cross-examined with the database. Many
limitations, regarding the level of accuracy and generalization, came to light
with this investigation. Artificial neural network modeling is then
proposed to improve the broadness and accuracy in predicting the flooding
capacity, which is an important design parameter for packed towers. A
combination of 6 dimensionless groups, namely the Lockhart-Martinelli
parameter (X), the liquid Reynolds (ReL), Galileo (GaL) and Stokes (StL) numbers as
well as the packing sphericity (f) and one bed number
(SB) outlining the tower dimensions were used as the basis of the neural
network correlation. With an initial database containing 1,019
measurements, the correlation yielded an absolute average relative error (
Keywords: randomly packed bed, counter-current flow, flooding capacity, neural network, database
You can get the packedbedsimulator.zip file that contains an Excel worksheet simulator to compute pressure drop, liquid holdup along with loading and flooding capacities.
You may also download our Excel worksheets simulators for Trickle-bed or Flooded Bed reactors.
The neural correlation was developped with the software NNFit