MODELING OF UREA DRYING AND GRANULATION PROCESS IN FLUIDIZED BED

Authors

Jalolitdin Pakhritdinovich Mukhitdinov, Doctor of Technical Sciences, Professor of "Automation of Production Processes" Chair, Tashkent State Technical University. Adress: Uzbekistan, Tashkent city, University street 2. Phone: +998946042380;
Aleksey Viktorovich Schulz, PhD student of "Automation of production processes" department, TashSTU. Adress: Uzbekistan, Tashkent city, University street 2. E-mail: schulz_alex@list.ru. Phone: +998337333211.Follow

Abstract

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a particle population balance model, and a numerical algorithm for solving the differential equations is outlined. The initial and calculated parameters of process streams are summarized in tabular form. Particle size distribution curves are presented for granules at the granulator outlet and for final granules after classification, crushing, and cooling stages. An analysis is performed for key variables influencing process efficiency, such as granulator cross-sectional area, water content in the feed solution, spray gas temperature, and operating parameters of the screen and crusher. The modeling results are compared against industrial specifications. This article may be useful for researchers and professionals in the fields of chemical process engineering and automation.

First Page

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Last Page

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References

1. Ministry of Justice of the Republic of Uzbekistan. (2025, June 19). Certificate of Software Registration No. DGU 53175.
2. Toyo Engineering Corp. (1980s). Urea granulation technology: Spout fluid bed granulation process. Retrieved from https://www.toyo-eng.com/jp/en/solution/urea_granulation/
3. Xiang, Y., Miao, R., Liu, Y.-Q., & Zhao, G. (2022). Preparation and properties of urea-formaldehyde slow-release fertilizer by high-temperature polycondensation of paraformaldehyde and urea. Journal of Plant Nutrition and Fertilizers, 28(9), 1699–1707. https://doi.org/10.11674/zwyf.2022203
4. Lu, H., Liu, G., Zhang, Q., & Jiang, X. (2025). Computational transport phenomena of multiphase systems and fluidization: Formulation and application of kinetic theory of granular flow. Springer Nature.
5. Zhao, B., Shi, K., He, M., & Wang, J. (2023). Hydrodynamics of polydisperse gas–solid flows: Kinetic theory and multifluid simulation. Chemical Engineering Science.
6. Que, H., & Chen, C.-C. (2011). Thermodynamic modeling of the NH₃–CO₂–H₂O system with electrolyte NRTL model. Industrial & Engineering Chemistry Research, 50(19), 11406–11421.
7. Wang, P., Anderko, A., & Young, R. D. (2021). A speciation-based mixed-solvent electrolyte model for urea process simulation. Fluid Phase Equilibria, 529, 112824.
8. Pérez-Calvo, J.-F., Sutter, D., Gazzani, M., & Mazzotti, M. (2017). Solid formation in ammonia-based CO₂ capture processes. Chemical Engineering Journal, 328, 368–386.
9. Ojong, O. E., Akpa, J. G., Dagde, K. K., & Amadi, D. (2024). Rate expression model from thermodynamics application and optimal kinetic parameters determination for urea synthesis and production process. Results in Engineering, 24, 102885.
10. Eghbal, A. H., & Mazloumi, S. H. (2023). Thermodynamic modeling of aqueous electrolyte solutions using nonelectrolyte UNIQUAC-NRF. Journal of Solution Chemistry, 52, 499–529. https://doi.org/10.1007/s10953-022-01244-1
11. Krum, K., et al. (2021). Kinetic modeling of urea decomposition and byproduct formation. Chemical Engineering Science, 230. https://doi.org/10.1016/j.ces.2020.116138
12. Nasri, Z., et al. (2007). Applications of the Soave–Redlich–Kwong equation of state using Mathematica®. Journal of Chemical Engineering of Japan, 40(6), 534–538.
13. Chen, X., & Li, H. (2023). A novel four-phase equilibrium calculation algorithm for water/hydrocarbon systems containing gas hydrates. Chemical Engineering Science, 267.
14. Bakhshi, H., & Mobalegholeslam, P. (2020). A modification of UNIQUAC model for electrolyte solutions based on the local composition concept. Journal of Solution Chemistry.
15. AO “NAVOIYAZOT.” (2023). Postoyannyy tekhnologicheskiy reglament № 117 proizvodstva karbamida [Permanent technological regulation No. 117 for urea production].
16. Design Institute for Physical Properties (DIPPR® Project 801 Database). (2025). AIChE database. Retrieved from https://www.aiche.org/dippr
17. National Institute of Standards and Technology. (2025). NIST Chemistry WebBook (Standard Reference Database No. 69). Retrieved from https://webbook.nist.gov/
18. Reid, R. C., Prausnitz, J. M., & Poling, B. E. (2001). The properties of gases and liquids (5th ed.). McGraw-Hill.
19. Ho, N., Dinh, H., Dau, N., & Nguyen, B. (2024). A numerical study on the flow field and classification performance of an industrial-scale micron air classifier under various outlet mass airflow rates. Processes, 12, 2035. https://doi.org/10.3390/pr12092035
20. Powell, M. S., & Morrison, R. D. (2007). The future of comminution modelling. International Journal of Mineral Processing, 84(1–4), 228–239. https://doi.org/10.1016/j.minpro.2006.08.003
21. Müller, W. (2014). Mechanische Verfahrenstechnik und ihre Gesetzmäßigkeiten (1st ed.). Springer Vieweg. ISBN 978-3-8348-1916-9.
22. Bayat, H., et al. (2015). Particle size distribution models, their characteristics and fitting capability. Journal of Hydrology, 529(3), 872–889. https://doi.org/10.1016/j.jhydrol.2015.08.067
23. Verein Deutscher Ingenieure (VDI). (2011). VDI 3678 Blatt 1: Elektrofilter; Prozessgas- und Abgasreinigung [VDI 3678 Part 1: Electrostatic precipitators; process gas and exhaust gas cleaning]. VDI Verlag.
24. Yang, W.-C. (2003). Handbook of fluidization and fluid-particle systems. CRC Press.
25. Schifftner, K. C., & Hesketh, H. E. (1996). Wet scrubbers (2nd ed.). Technomic Publishing.
26. Dong, K., Wang, B., & Yu, A. (2013). Modeling of particle flow and sieving behavior on a vibrating screen: From discrete particle simulation to process performance prediction. Industrial & Engineering Chemistry Research, 52, 11333–11343. https://doi.org/10.1021/ie3034637
27. Sen, M., Barrasso, D., Singh, R., & Ramachandran, R. (2014). A multi-scale hybrid CFD–DEM–PBM description of a fluid-bed granulation process. Processes, 2(1), 89–111.

Recommended Citation

Mukhitdinov, Jalolitdin Pakhritdinovich and Schulz, Aleksey Viktorovich (2025) "MODELING OF UREA DRYING AND GRANULATION PROCESS IN FLUIDIZED BED," Chemical Technology, Control and Management: Vol. 2025: Iss. 4, Article 1.
DOI: https://doi.org/10.59048/2181-1105.1692