Computational Fluid Dynamics (CFD) investigation on associated effect of classifier blades lengths and opening angles on coal classification efficiency in coal pulverizer. (December 2022)

• Record Type: Journal Article
• Authors: Ismail, Firas Basim; Al-Muhsen, Nizar F.O.; Hasini, Hasril; Kuan, Elaine Why Siew
• Is Part Of: Case studies in chemical and environmental engineering. Volume 6(2022)
• Publication Date: 2022-12
• Subjects: Coal pulverizer classifier -- Classifier blade length -- CFD -- Tromp curve -- Energy; Chemical engineering -- Periodicals; Environmental engineering -- Periodicals; Environmental chemistry -- Periodicals; 628.05
• DOI: 10.1016/j.cscee.2022.100266
• Languages: English
• ISSNs: 2666-0164

Abstract

Abstract: In order to achieve complete combustion of fuel in common thermal power plant, the process of coal fuel classification is crucial, which often governs by classifier in pulverizer. This is because smaller size of coal particle has higher surface area, and therefore able to produce higher combustion efficiency. This paper describes the Computational Fluid Dynamics (CFD) simulations of coal pulverizer were done for classifier with different blade length and at different opening angle. The objective of the work is to evaluate optimum classifier design with the highest coal fineness output and separation efficiencies. Preliminary work of validating simulation result with experimental result of classifier with initial geometry was done, and good agreement was obtained. Grade efficiencies and sharpness of cut of each different classifier model were determined by plotting of Tromp curves. Simulation studies showed that classifier blade length of 313.94 mm at 40° was found to be optimum, with 71.5% of particles passing fine size sieve (75 μm) and 0.1852 sharpness of cut. Classification of fine coal by the optimum classifier model is improved by 10%, as compared to original classifier model used in industry. Graphical abstract: Image 1 Highlights: Classifier geometry influenced classification efficiency and output energy. Increasing classifier blade length increased the amount coal fineness. Decreasing classifier blade opening angle increased the amount of coal fineness. An optimum classifier model with highest amount of coal fineness was determined. A coal fineness improvement of 7.25% was achieved.