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Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process
Authors:Johannes Brockkötter  Johannes Ahndorf  Andreas Jupke
Affiliation:RWTH Aachen University, Fluid Process Engineering (AVT.FVT), Forckenbeckstraße 51, 52074 Aachen, Germany
Abstract:Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.
Keywords:Flooding  Gaussian process regression  Packed high-pressure extraction column  Packed liquid-liquid extraction column  Supercritical CO2
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