Development of a methodology for predicting particle attrition in a cyclone by CFD-DEM

Fabio Fulchini (1, 2) , Mojtaba Ghadiri (1) , Antonia Borissova (1) , Benjamin Amblard (2) , Stéphane Bertholin (2) , Ann Cloupet (2) , Mahdi Yazdanpanah (3)

1 University of Leeds
2 IFPEN - IFP Energies nouvelles
3 TOTAL S.A.

Cyclones are commonly used in the process industry to separate entrained particles from gas streams. Particles entering a cyclone are subjected to a centrifugal force field, driving them to the cyclone walls, where they experience collisional and rapid shearing stresses. Consequently, particle attrition and erosion of the cyclone walls occur, depending on the mechanical properties of the particles and cyclone walls. In this work, the attrition of manganese oxide particles, intended for use in the Chemical Looping Combustion (CLC) process, flowing through a standard design cyclone (Stairmand design) is analysed as an example by considering surface damage processes of chipping and wear. A new methodology is developed, whereby Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) simulations are used to analyse the particle motion and interactions with the cyclone walls. The approach is then coupled with breakage models of chipping and wear to predict the extent of attrition. The impact breakage due to chipping is evaluated experimentally first as a function of particle size and impact angle and velocity. The data are fitted to the chipping model of Ghadiri and Zhang. The model is then coupled with the frequency of collisions and impact velocity, obtained from the CFD-DEM simulation, to work out the particle attrition by chipping. For surface wear the model of Archard is used to account for particle wear by shearing against the walls. The outcome of the work provides a methodology for describing the extent of attrition in different regions of the cyclone.

Domaines: Génie chimique

Fabio Fulchini, Mojtaba Ghadiri, Antonia Borissova, Benjamin Amblard, Stéphane Bertholin, et al.. Development of a methodology for predicting particle attrition in a cyclone by CFD-DEM. Powder Technology, 2019, 357, pp.21-32. ⟨10.1016/j.powtec.2019.08.101⟩. ⟨hal-02445565⟩