Computational fluid dynamic modelling of FCC riser: A review

Shah, Milinkumar T.; Utikar, Ranjeet P.; Pareek, Vishnu; Evans, Geoffrey M.; Joshi, Jyeshtharaj B.

doi:10.1016/j.cherd.2016.04.017

Cited by 59 publications

(49 citation statements)

References 251 publications

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“…Gas–solid fluidization continues to receive interest as it is widely applied in industry, including petroleum, chemical, metallurgical, and energy industries . The gas–solid flows in fluidized bed are very complex, showing great variations in phase volume fraction and velocity, which makes it very challenging for reactor design, optimization, and scale up.…”

Section: Introductionmentioning

confidence: 99%

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

Gao

Rogers

2018

AIChE Journal

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This study focused on assessing the effect of mesoscale solid stress in the coarse grid two‐fluid model (TFM) simulation of gas–solid fluidized beds of Geldart Group A particles over a broad range of flow regimes, including bubbling, turbulent, fast, and pneumatic transport fluidization regimes. Particularly, the impact of mesoscale solid pressure, mesoscale solid viscosity, and mesoscale solid stress anisotropy were investigated by comparing six different coarse‐grid TFM settings. Compared with the available experimental data, it is found that both the kinetic theory‐based TFM with only drag correction and the filtered TFM can predict the flow behavior in all fluidization regimes. Mesoscale solid pressure and viscosity have the opposite impact on flow hydrodynamics; they compete and offset each other, which confirms the assumption employed in many previous studies that the mesoscale solid stress could be neglected in coarse‐grid TFM simulation. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. AIChE J, 64: 3565–3581, 2018

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Section: Introductionmentioning

confidence: 99%

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

Gao

Rogers

2018

AIChE Journal

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“…The gas flow was defined as continuous phase and the individual flexible filamentous particle was simulated with the chain model. Wang et al [5] investigated the particle behavior in a bubbling fluidized bed with non-spherical particles using discrete hard sphere method. Li et al [6] proposed a new algorithm to approximate real particles using multiple overlapping spheres as numerical models.…”

Section: Introductionmentioning

confidence: 99%

A Method for Analyzing the Radial Distribution of Flexible Ribbon Particles and Cluster in a Fluidized Bed Riser

Wu¹,

Li²,

Yuan³

2018

World Congress on Mechanical, Chemical, and Material Engineering

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Many biomass materials, such as herbage, tobacco leaf and seaweed are chopped into small strips and usually dried by fluidized bed dryer. These Flexible ribbon particles in the fluidized bed riser may have experienced a much more complicated process, such as heat & mass transfer, mixing and drying. They are easy to hold together due to the flexibility and the non-uniformity of ribbon shape. Thus, it is important to understand the distribution of this special particle and cluster in the riser. High-speed camera method has always been used in measurement. However, it is difficult to analyze the particle flow due to the overlaps of the flexible ribbon particle in the shot image. So this paper presented a new analyzing method in order to obtain more information of this special gas-solid flow. And the radial concentration distribution of flexible filamentous particle and cluster in gas-solid flow in were experimentally analyzed. It is found that the concentration distribution of the flexible filamentous cluster was completely different from that of the conventional spherical particles.

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“…Secondly, the interplay between flow structures and catalytic reactions should be considered in modeling. For the reactive simulation of a large reactor, various lumped-species kinetics models are widely used (Gan et al, 2011;Lopes et al, 2011;Lu et al, 2013a;Lu et al, 2016;Shah et al, 2016), where a group of components with similar chemical properties are treated as one lump to reduce computational demand. However, the reaction kinetics parameters, which are generally obtained from experiments over micro-scale reactors, are hardly termed the "intrinsic" ones where the influence of inner and outer diffusions should be strictly excluded in experiments.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of scale-up effects of methanol-to-olefins fluidized bed reactors

Zhāng

Luo

et al. 2017

Chemical Engineering Science

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Computational fluid dynamic modelling of FCC riser: A review

Cited by 59 publications

References 251 publications

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

Assessment of mesoscale solid stress in coarse‐grid TFM simulation of Geldart A particles in all fluidization regimes

A Method for Analyzing the Radial Distribution of Flexible Ribbon Particles and Cluster in a Fluidized Bed Riser

Numerical simulation of scale-up effects of methanol-to-olefins fluidized bed reactors

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