(133c) Next Generation Scalable Models for Mass Transfer in Packed Column | AIChE

(133c) Next Generation Scalable Models for Mass Transfer in Packed Column


Nandakumar, K. - Presenter, Louisiana State University
Chuang, K. T. - Presenter, University of Alberta

It has been a great honor and privilege for me to have had the opportunity to work closely with Professor Karl Chuang for more than a decade. He has been a great mentor to me and we have worked together on advancing the computer modeling techniques for mass transfer in distillation columns. In celebrations of his life time contributions to the field, I present an over view of our work together in this area. Many key ideas are his and I only helped in implementing them. In this talk we present our results on modelling the hydraulics and mass transfer in random and structured packed columns. Two distinctly different approaches are discussed. The first one is based on computational fluid dynamics wherein volume averaged equations for gas-liquid flow in a packed bed are used. The concept of volume averaging, its merits and limitations will be reviewed. This is done in the framework of interpenetrating continua and it requires closure relations to capture the interface transport processes such as drag and mass transfer. Hence predictions from such models must be validated against data from well controlled experiments. In our laboratory we measure the liquid distributions over Pall rings under various conditions and compare such data against CFD predictions. HETP data from Fractionation Research Inc. are used to validate mass transfer models. The main advantage of such an approach is that the model predictions can remain scale invariant over a certain range. Hence CFD models can help in minimizing scale up studies at the pilot plant scale. In an alternate approach, we simulate the random packing of complex shaped packing elements like Pall rings or Super Raschig rings in a container using collision detection algorithms. Once the position and orientation of each packing element is determined, we can interrogate the data to get porosity and surface area distribution within the bed. Such data can then be used in the CFD simulations or cell based models. We have explored both and these results will be discussed. The same approach is also used for studying not only performance of existing structured packings, but also in the design of new structured packings.


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