Experimental and CFD investigation of fractal distributor on a novel plate and frame ion‐exchanger

Abstract

Conventional pressure based flow distributors face challenges in the form of operational limits as their low outlet density and non-uniform flow distribution path, often act as bottleneck in the overall chemical equipment efficiency. Recently, a new distributor design inspired by the concept of fractal shows promising performance over a wide range of applications and operating conditions. The inherent scaling symmetry from such fractal distributors allows identical hydraulic flow path length to all outlets as well as much higher outlet density. In this study, we have designed a novel 12” by 12” plate and frame type ion-exchanger called “Fractal Pack” and tested it in pilot scale adopting fractal distributors with 256 outlets under operating flow rates ranging from 6.31x10-5 m3/s to 2.52x10-4m3/s. For comparison, ion-exchanger with 16 distributor outlets has also been assembled to mimic the performance of conventional pressure-based design. Both residence time distribution test and CFD investigations have been conducted. From CFD results, at highest flow rate, we found the overall pressure drop for ion-exchanger with 16 outlets is about 6 times larger than with fractal distributor and 78% of its pressure drop is caused by sudden expansion and contraction at 16 outlets. In addition, a key index, degree of heterogeneity which measures the percentage of maldistribution zones inside resin, has been defined to quantify flow distribution inside resin. The distributor equipped with 16 outlets shows 4 times more mal-distribution zones than 256 outlets at highest flow rate. This work demonstrates that fractal distributors can reliably provide superior performance over conventional distributors in a compact design framework; by introduction of symmetry, fractal distributors can aid process intensifications for many chemical processes that are plagued by heterogeneities and poor process efficiencies. The work also demonstrates how CFD can assist in avoiding ad-hoc design decision on dimensions and systematically explore the design space for optimum design decisions, using optimization criteria like coefficient of variation, degree of dispersion or heterogeneity.