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Prediction of Flooding in Packed Liquid‐Liquid and High‐Pressure Extraction Columns Using a Gaussian Process
Author(s) -
Brockkötter Johannes,
Ahndorf Johannes,
Jupke Andreas
Publication year - 2021
Publication title -
chemie ingenieur technik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 36
eISSN - 1522-2640
pISSN - 0009-286X
DOI - 10.1002/cite.202100073
Subject(s) - extraction (chemistry) , gaussian , gaussian process , sizing , range (aeronautics) , process (computing) , materials science , chromatography , mathematics , biological system , algorithm , mechanics , computer science , chemistry , physics , computational chemistry , organic chemistry , biology , composite material , operating system
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.