Numerical study of a fluid catalytic cracking regenerator hydrodynamics

Tang, Guangwu; Silaen, Armin K.; Wu, Bin; Fu, Dong; Agnello-Dean, Dwight; Wilson, Joseph W.; Meng, Qingjun; Khanna, Samir; Zhou, Chenn Q.

doi:10.1016/j.powtec.2016.09.082

Cited by 11 publications

(2 citation statements)

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“…If coupled with DEM, it is usually called coarse grained particle method (CGPM); 14,15 and if coupled with TDHS, it is called coarse grained hard sphere method (CGHS). 16 The parcel based method reduces significantly the computation cost and has been used to simulate large-scale FCC riser, 17 FCC regenerator, 18 cyclones, 19 circulating fluidized bed, 20,21 liquid−solids leaching reactor, 22 and heat transfer in bubbling fluidized bed. 23 On the basis of the different methods to handle particle− particle interactions and whether tracking real particles or computation parcels, the current Euler−Lagrange methods can be summarized in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…If coupled with DEM, it is usually called coarse grained particle method (CGPM); , and if coupled with TDHS, it is called coarse grained hard sphere method (CGHS) . The parcel based method reduces significantly the computation cost and has been used to simulate large-scale FCC riser, FCC regenerator, cyclones, circulating fluidized bed, , liquid–solids leaching reactor, and heat transfer in bubbling fluidized bed …”

Section: Introductionmentioning

confidence: 99%

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Assessment of Different Discrete Particle Methods Ability To Predict Gas-Particle Flow in a Small-Scale Fluidized Bed

Gopalan

Benyahia

2017

Ind. Eng. Chem. Res.

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Several discrete particle methods exist in the open literature to simulate fluidized bed systems, such as discrete element method (DEM), time-driven hard sphere (TDHS), coarse-grained particle method (CGPM), coarse grained hard sphere (CGHS), and multiphase particle-in-cell (MP-PIC). The main difference between these methods is in the treatment of particle–particle interactions: by calculating collision forces (DEM and CGPM), using momentum conservation laws (TDHS and CGHS), or based on the particle stress model (MP-PIC). Here, these methods are compared by simulating the same small-scale fluidized bed with the same open-source code MFIX. The results indicate that both modeling the particle–particle collision by TDHS and lumping a few particles in a parcel increase the computation speed with little loss in accuracy. However, the MP-PIC method predicts an unphysical particle–particle overlap, which results in incorrect overall bed hydrodynamics. These results suggest using the CGHS method for fluidized bed simulations owing to its accuracy and efficiency.

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