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Internal Age Distribution inside Trickle Bed Reactors Using an Eulerian Two-Fluid Approach

Internal Age Distribution inside Trickle Bed Reactors Using an Eulerian Two-Fluid Approach

Authors: 
Augier, F. - Presenter, IFP Energies Nouvelles
Fourati, M. - Presenter, IFP Energies Nouvelles
Haroun, Y. - Presenter, IFP Energies Nouvelles






Internal age
distribution inside Trickle Bed Reactors using an eulerian
two-fluid approach

Ing Yii Tang, Yacine
Haroun, Manel Fourati, Frédéric Augier

Keywords : Trickle Bed Reactors, CFD, Mal-distribution,
Age distribution, two-fluid model

ABSTRACT

Trickle Bed Reactors
(TBRs) are well known for decades, as they are simple, cheap and
easy-to-scale-up1. In the competitive field of fuel hydroprocessing, a major challenge is to develop compact
but efficient distribution technologies in order to maximize the catalytic
conversion. As a consequence, a key point is to predict and control
hydrodynamics in the catalyst bed below distribution plates, in order to remain
close enough to a plug flow for not deteriorating performances of the reaction.
Several studies have been done in the past to investigate experimentally mal-distributions
inside TBRs2,3, as well as numerically4,5. In this
context, the present study is divided in 3 steps :

a) Validation of a
CFD model recently developed by comparison with original in-house g-tomography experiments. The CFD
model is based on Eulerian-Eulerian two-fluid
approach coupled with a porous medium description. Closure laws as regards
porous resistances, gas-liquid interaction, capillary and mechanical dispersion
are implemented as body source terms in momentum equations within ANSYS Fluent
14.5 environment. Simulation results are compared to experimental data
obtained with g-tomography experiments within a 4m
height TBR mockup equiped with distribution chimneys. A good
agreement between simulation and experiments is observed as reported in figure 1.

 

Figure 1 : Comparison between g-tomography and CFD modeling in a
600mm TBR, 3m below the distribution plate.

b) The CFD model are
used to perform a 2D and 3D Simulations of a reactive TBR (1st and 2nd
order kinetics on liquid) in presence of different inlet liquid non ideal
distributions. A comparison of performances with an ideal 1D plug flow is
discussed. A relation between the rate of mal-distribution and loss of
conversion is proposed.

c) Characterization
of the age distribution inside the TBR by solving its different moments6.This
last step of the study is an original way to investigate internal flows inside
reactors, much less CPU-time consuming than a classical transient simulation of
Residence Time Distribution. After calculation of internal age distribution
presented in figure 2, a simplified 1D model is proposed to take the
distribution into account. Unlike the classical approach that consists to use
an apparent axial dispersion to represent hydrodynamic defects, it is proposed
to use the distribution of ages at the outlet of the reactor to develop a 1D
multi-outlet reactor. Comparisons between the 1D model and 2-3 CFD simulations
performed during step b) show that the developed simplified model reproduces
accurately the loss of conversion induced by mal-distribution.

This work shows that the internal
age distribution modeling by CFD is a powerful approach to relate the quality
of distribution to the catalytic performance inside TBRs.


Figure 2 :
CFD-Snapshot of the internal mean age distribution inside the 4m-TBR

below a
distribution plate with Chimneys.

REFERENCES

[1] Maiti R.N., Nigam K.D.P, Gas-Liquid Distributors for Trickle-Bed Reactors:
A Review. Ind. Eng. Chem. Res., 46, 6164-6182, 2007.

[2] Bazer-Bachi F., Haroun Y., Augier
F., Boyer C., Experimental evaluation of distributor technologies for
trickle-bed reactors, Ind.Eng.Chem.Res, 2013, 52, 11189−11197.

[3] Marcandelli C., Lamine
A.S., Bernard J.R., WILD G., Liquid distribution in trickle-bed reactor, Oil &
Gas Science and Technology, Rev. IFP 55, 407-415, 2000.

[4] Lappaleinen K., Manninen
M., Alopeus V., CFD modeling
of radial spreading of flow in trickle-bed reactors due to mechanical and
capillary dispersion, Chem. Eng. Sci, 64, 207-218,
2009.

[5] Boyer C., Koudil A., Chen P., Dudukovic M.P., Study of liquid spreading from a point
source in a trickle bed via gamma-ray tomography and CFD simulation, Chem.Eng.Sci. 60, 6279-6288, 2005.

[6] Liu, M., Tilton, J.N., Spatial distributions of mean
age and higher moments in steady continuous flows. AIChE
J. 56, 2561, 2010.

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