LAPSE:2023.4844
Published Article
LAPSE:2023.4844
Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process
Vasyl Skorych, Moritz Buchholz, Maksym Dosta, Helene Katharina Baust, Marco Gleiß, Johannes Haus, Dominik Weis, Simon Hammerich, Gregor Kiedorf, Norbert Asprion, Hermann Nirschl, Frank Kleine Jäger, Stefan Heinrich
February 23, 2023
The production of catalysts such as zeolites is a complex multiscale and multi-step process. Various material properties, such as particle size or moisture content, as well as operating parameters—e.g., temperature or amount and composition of input material flows—significantly affect the outcome of each process step, and hence determine the properties of the final product. Therefore, the design and optimization of such processes is a complex task, which can be greatly facilitated with the help of numerical simulations. This contribution presents a modeling framework for the dynamic flowsheet simulation of a zeolite production sequence consisting of four stages: precipitation in a batch reactor; concentration and washing in a block of centrifuges; formation of droplets and drying in a spray dryer; and burning organic residues in a chain of rotary kilns. Various techniques and methods were used to develop the applied models. For the synthesis in the reactor, a multistage strategy was used, comprising discrete element method simulations, data-driven surrogate modeling, and population balance modeling. The concentration and washing stage consisted of several multicompartment decanter centrifuges alternating with water mixers. The drying is described by a co−current spray dryer model developed by applying a two-dimensional population balance approach. For the rotary kilns, a multi-compartment model was used, which describes the gas−solid reaction in the counter−current solids and gas flows.
Keywords
data-driven modeling, flowsheet simulation, kiln, Multiscale Modelling, solid–liquid separation, spray drying, synthesis, zeolite production
Suggested Citation
Skorych V, Buchholz M, Dosta M, Baust HK, Gleiß M, Haus J, Weis D, Hammerich S, Kiedorf G, Asprion N, Nirschl H, Kleine Jäger F, Heinrich S. Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process. (2023). LAPSE:2023.4844
Author Affiliations
Skorych V: Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany [ORCID]
Buchholz M: Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany [ORCID]
Dosta M: Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany; Boehringer Ingelheim Pharma GmbH & Co., KG, 88400 Biberach an der Riss, Germany [ORCID]
Baust HK: Institute of Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany [ORCID]
Gleiß M: Institute of Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Haus J: BASF SE, 67056 Ludwigshafen, Germany
Weis D: BASF SE, 67056 Ludwigshafen, Germany
Hammerich S: BASF SE, 67056 Ludwigshafen, Germany
Kiedorf G: BASF SE, 67056 Ludwigshafen, Germany
Asprion N: BASF SE, 67056 Ludwigshafen, Germany
Nirschl H: Institute of Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Kleine Jäger F: BASF SE, 67056 Ludwigshafen, Germany
Heinrich S: Institute of Solids Process Engineering and Particle Technology, Hamburg University of Technology, 21073 Hamburg, Germany [ORCID]
Journal Name
Processes
Volume
10
Issue
10
First Page
2140
Year
2022
Publication Date
2022-10-20
Published Version
ISSN
2227-9717
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PII: pr10102140, Publication Type: Journal Article
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LAPSE:2023.4844
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doi:10.3390/pr10102140
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