Development and Application of the TUM-WelChem Cell Model for Prediction of Liquid Distribution in Random Packed Columns

Abstract

Liquid maldistribution is, next to the prediction of interfacial phase area and mass transfer coefficients, one of the bigger uncertainties in random packed column design. In a joint project, “Cell Model for Packed Column and Liquid Distributor Design” supported by the Bavarian Research Foundation, liquid maldistribution experiments were conducted in three packed columns with diameters of 0.4, 1.2 and 2.0 m at Technical University of Munich (TUM), RVT Process Equipment GmbH and Linde AG. Experiments covered varying experimental and operating parameters – gas/liquid system, type of packing, packing height, type of liquid distributor, liquid load, and gas load. An evaluation of the acquired database provided insight into influencing factors on liquid distribution (Hanusch et al., 2017). In 2007, Wild and Engel first presented their WelChem Cell Model. The original model predicted liquid distribution in random packing from cell layer to cell layer based on directional dispersion coefficients, deduced from virtual 3D irrigation simulations with a CAD model of one random packing element (Wild and Engel, 2007). Further development at TUM included implementation of the influencing factors liquid load and gas load, considering local loading effects and increasing liquid dispersion. Wall effects were refined by distinction of packing elements and voids at the column wall. Liquid distribution profiles predicted with the TUM-WelChem Cell Model are in good agreement with experimental data. WelChem GmbH implemented the TUM-WelChem Cell Model in their column design software TrayHeart, thus making the research results directly accessible for TrayHeart users. Application of the TUM-WelChem Cell Model ranges from prediction of maldistribution in random packed columns, through liquid distributor design, considering interactions with random packing, to process simulation, considering maldistribution in parallel column models (Schultes, 2000).