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Use of multiscale data-driven surrogate models for flowsheet simulation of an industrial zeolite production process
Citation Link: https://doi.org/10.15480/882.4672
Publikationstyp
Journal Article
Date Issued
2022-10-20
Sprache
English
TORE-DOI
Journal
Volume
10
Issue
10
Article Number
2140
Citation
Processes 10 (10): 2140 (2022)
Publisher DOI
Scopus ID
Publisher
Multidisciplinary Digital Publishing Institute
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.
Subjects
flowsheet simulation
zeolite production
data-driven modeling
synthesis
solid-liquid separation
spray drying
kiln
multiscale modeling
DDC Class
530: Physik
600: Technik
620: Ingenieurwissenschaften
660: Technische Chemie
Publication version
publishedVersion
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processes-10-02140-v2.pdf
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