Unraveling the multifaceted challenges and advances in validating tray efficiency prediction models

Industrial tray columns are widely used for distillation and absorption processes globally. They are known for high energy consumption, which is often overlooked due to unavailability of an equivalent industrially viable alternative. Rising energy costs and urgent need to control greenhouse gas emissions call for improvement in the performances of tray columns globally. This can be achieved by tuning the dynamics of the two-phase dispersion on individual trays for higher efficiencies via design modifications and revamping. To do so, it becomes necessary to understand how the two-phase flow evolves over a tray and relates to the tray efficiency. Such relation can be evaluated based on mathematical models called as tray efficiency prediction models. Hitherto, the existing models only provided black box estimations and ignored maldistributions in the vapor flow. These limitations were recently targeted by a new model referred to as ‘Refined Residence Time Distribution (RRTD) model’ [1].

The proof of concept of the RRTD model demands complete information pertaining to two-phase dispersion and mass transfer on a large-scale column tray. They are not available at desired resolution in the existing literature due to several limitations in the applied measurement techniques and systems. Thus, a recently-proposed multiplex flow profiler [2] was deployed inside an air-water column mockup (DN800) for characterizing the distributions of liquid holdup, residence time and mixing over a sieve tray for several loadings at high resolution. For the same operating conditions, the efficiency data over that tray was obtained based on air-led stripping of isobutyl acetate from the aqueous solution. Both hydrodynamic and efficiency data were applied together for assessing the validity of the new RRTD and other models. This works also sets new benchmarking standards for improved validation of CFD and efficiency prediction models in the future.

[1] Vishwakarma, V., Schubert, M. and Hampel, U., 2019. Development of a refined RTD-based efficiency prediction model for cross-flow trays. Industrial & Engineering Chemistry Research, 58(8), pp.3258-3268.
[2] Vishwakarma, V., Schleicher, E., Schubert, M., Tschofen, M. and Löschau, M., 2020. Sensor zur Vermessung von Strömungsprofilen in großen Kolonnen und Apparaten. Deutsches Patent und Markenamt, DE 10 2018 124 501.