CFD simulation and optimization of an industrial cement gas–solid air classifier--颗粒学报PARTICUOLOGY

Esmaeilpour, M., Mohebbi, A., & Ghalandari, V. (2024). CFD simulation and optimization of an industrial cement gas–solid air classifier. Particuology, 89, 172-184. https://doi.org/10.1016/j.partic.2023.10.011

CFD simulation and optimization of an industrial cement gas–solid air classifier

Mohamadreza Esmaeilpour^a, Ali Mohebbi ^a *, Vahab Ghalandari ^b

a Department of Chemical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
b Kerman Momtazan Cement Company, Kerman, Iran

10.1016/j.partic.2023.10.011

Volume 89, June 2024, Pages 172-184

Received 13 June 2023, Revised 9 October 2023, Accepted 25 October 2023, Available online 3 November 2023, Version of Record 6 December 2023.

E-mail: amohebbi@uk.ac.ir

Highlights

• An industrial cement air classifier performance was studied by CFD simulation.

• Cement quality and production were inspected based on particle size distribution (PSD) analysis.

• Classifier feeding was modified based on flow analyzing inside the classifier.

• The effect of the pressure difference was investigated for the first time.

• The effect of inlet air temperature on the performance of the device was clarified.

Abstract

An air classifier is one of the main and effective devices in cement industry. In this study, a three-dimensional, steady and two-phase (solid-gas) computational fluid dynamics (CFD) simulation was performed to optimize the performance of this device in the Kerman Momtazan cement plant, Iran. After the validation of CFD results, the air flow field and air path lines between fixed blades were checked carefully and the non-uniformity in velocity distribution and the formation of vortex flows between the blades close to particle inlets were observed. The study tried to improve the device efficiency by changing the method of entering particles into the device, resulting in a reduction in air classifier electrical energy consumption (from 41 to 35 (kW h)/t) and an increase in production rate (from 203 to 214 t/h). Additionally, the study investigated the effects of other modifiable operating conditions like rotary cage rotation speed, pressure difference, and inlet air temperature on the particle size distribution and classifier efficiency. The results showed that increasing the cage rotation speed decreased the product rate and the product particles mean diameter while increasing pressure difference or increasing temperature increased the product rate and the product particles mean diameter. It was concluded that these modifiable operating conditions can significantly affect the performance of the air classifier in the cement industry.

Graphical abstract

Keywords

Cement air classifier; Computational fluid dynamics; Gas–solid two-phase flow; Optimization; Eulerian–Lagrangian method; Efficiency

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