(485f) Packing Algorithms to Study Loading Methodologies in Trickle Bed Reactors

Trickle bed reactors are highly preferred in chemical industry owing to the ease of maintenance and operation, absence of moving parts, and minimal operational constraints. However the random nature of packing results in complex fluid flow patterns which lead to maldistribution of fluid and associated effects like that of catalyst deactivation and hotspot formation. Most of the studies ¹ propose local variations in porosity to play a key role in fluid maldistribution. Experimental studies ^2,3 performed on laboratory scale demonstrate better fluid distribution to be dependent on shape of particles and loading methodologies used.

In this study packing algorithms have been developed and applied to poly-disperse spheres packing and extrudates packing. Statistically significant numbers of beds are generated. Impact of loading methodologies on evolution of axial and radial porosity features is evaluated using these algorithms. Effect of particle size distribution on the packing configuration is studied. Impact of these configurations on fluid spreading in trickle beds is elucidated. These investigations help in developing tools to manipulate the heterogeneities in packed beds to mitigate mal-distribution and enhance reactor performance.

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2.        Bazmi, M., Hashemabadi, S. H. & Bayat, M. Flow Maldistribution in Dense- and Sock-Loaded Trilobe Catalyst Trickle-Bed Reactors: Experimental Data and Modeling Using Neural Network. Transp. Porous Media 97, 119–132 (2013).

3.        Salimi, M., Hashemabadi, S. H., Noroozi, S., Heidari, a. & Bazmi, M. Numerical and Experimental Study of Catalyst Loading and Body Effects on a Gas-Liquid Trickle-Flow Bed. Chem. Eng. Technol. 36, 43–52 (2013).