Design of parabolic conic gas cyclones for coarse particle classification: A CFD study with Response Surface Methodology
Powder Technology, ISSN: 0032-5910, Vol: 433, Page: 119217
2024
- 4Citations
- 15Captures
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Article Description
Gas cyclones have traditionally been used as particle separators to remove dust from gas streams, with the goal of achieving a dust-free gas flow at the exit pipe and recovering particles to the dust outlet. Typically, the particle size for removal to the dust outlet is less than 1 μm. However, gas cyclones can also be targeted for particle classification rather than particle removal. In this study, the effect of the shape of the curved conical wall, specifically the parabolic concave and convex conic designs, on particle classification in a 31 mm diameter gas cyclone was evaluated using Computational Fluid Dynamics (CFD). The CFD model predictions for standard small-scale gas cyclones were validated using experimental data available in the literature for various inlet flow rates. The curvature of the conical wall varied from convex to concave, resulting in the observation of sharper and coarser cut sizes for the parabolic conic designs. The cut size increases to 4.91 μm for the concave design at a flow rate of 30 liters per minute, compared to 3.38 μm and 2.65 μm for the convex and standard design cyclones, respectively. The axial, tangential, pressure, and turbulent kinetic energy profiles were used to provide an explanation for the observed results. The interaction effects between the parameters were explored using the Response Surface Methodology. Further, Monte Carlo simulations are performed to observe the trends in predictions by exploring the design space.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0032591023010008; http://dx.doi.org/10.1016/j.powtec.2023.119217; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85178120815&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0032591023010008; https://dx.doi.org/10.1016/j.powtec.2023.119217
Elsevier BV
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