A review on computational fluid dynamic simulation for rotating packed beds

Yang, Yucheng; Ouyang, Yi; Zhang, Na; Yu, Qiangliang; Arowo, Moses

doi:10.1002/jctb.5880

Cited by 22 publications

(26 citation statements)

References 82 publications

(287 reference statements)

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“…CFD is an interdisciplinary topic that can be used to simulate flow characteristics and transport phenomena under certain conditions, and which includes mathematics, hydrodynamics, the computation of the conservation of mass, heat and momentum equations, and a discretizing method [173]. The velocity field in RPBs must be studied in order to determine heat and MT mechanisms, but the conditions in RPBs are complicated, turbulent, swirling and anisotropic [89], and CFD is a good tool in such situations.…”

Section: Methodsmentioning

confidence: 99%

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A Review of Modeling Rotating Packed Beds and Improving Their Parameters: Gas–Liquid Contact

2021

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The aim of this review is to investigate a kind of process intensification equipment called a rotating packed bed (RPB), which improves transport via centrifugal force in the gas—liquid field, especially by absorption. Different types of RPB, and their advantages and effects on hydrodynamics, mass transfer, and power consumption under available models, are analyzed. Moreover, different approaches to the modeling of RPB are discussed, their mass transfer characteristics and hydrodynamic features are compared, and all models are reviewed. A dimensional analysis showed that suitable dimensionless numbers could make for a more realistic definition of the system, and could be used for prototype scale-up and benchmarking purposes. Additionally, comparisons of the results demonstrated that Re, Gr, Sc, Fr, We, and shape factors are effective. In addition, a study of mass transfer models revealed that the contact zone was the main area of interest in previous studies, and this zone was not evaluated in the same way as packed beds. Moreover, CFD studies revealed that the realizable k-ε turbulence model and the VOF two-phase model, combined with experimental reaction or mass transfer equations for analyzing hydrodynamic and mass transfer coefficients, could help define an RPB system in a more realistic way.

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Section: Methodsmentioning

confidence: 99%

“…Sometimes CFD modeling requires user-defined functions (UDF) for explaining reactions or MT. As for geometry generation, one of the following methods may be employed [173]:…”

Section: Methodsmentioning

confidence: 99%

A Review of Modeling Rotating Packed Beds and Improving Their Parameters: Gas–Liquid Contact

2021

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“…Meanwhile, the Mixture Design (MD) is a special experiment tool that is used to determine the optimum proportions of feedstocks for enhanced H 2 yields [239,240]. Sekoai and Gueguim Kana [240] used the MD to assess the optimum proportions of corn stalk (CS), bean husk (BH), and organic Computational fluid dynamics (CFD) is a multi-dimensional tool that employs numerical methods to provide useful information about the hydrodynamics of processes [241][242][243][244][245][246]. CFD also provides in-depth information about the design of DF reactors and is used to evaluate the scalability of DF systems [247].…”

Section: Mathematical Toolsmentioning

confidence: 99%

Revising the dark fermentative H2 research and development scenario – An overview of the recent advances and emerging technological approaches

Sekoai

Daramola

Mogwase

et al. 2020

Biomass and Bioenergy

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The indiscriminate use of fossil fuels has led to several challenges such as greenhouse gas emissions, environmental degradation, and energy security. Establishment of clean fuels is at the forefront of science and innovation in today's society to curb these problems. Dark fermentation (DF) is widely regarded as the most promising clean energy technology of the 21st century due to its desirable properties such as high energy content, its non-polluting features, its ability to use a broad spectrum of feedstocks and inoculum sources, as well as its ability to use mild fermentation conditions. In developing nations, this technology could be instrumental in establishing effective waste disposal systems while boosting the production of clean fuels. However, DF is still hindered by the low yields which stagnate its commercialization. This paper reviews the recent and emerging technologies that are gaining prominence in DF based on information that has been gathered from recent scientific publications. Herein, novel enhancement methods such as cell immobilization, nanotechnology, mathematical optimization tools, and technologies for biogas upgrading using renewable H 2 are comprehensively discussed. Furthermore, a section which discusses the potential of bioenergy in Sub-Saharan Africa including South Africa is included. Finally, scientific areas that need further research and development in DF process are also presented.

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“…Compared with the experiments, CFD simulations have unique advantages, for example, they can visually present the detailed liquid hydrodynamic and mass transfer behaviour in the complex inner space of the chemical equipment, which is often difficult to obtain through experimental measurements (Lopes and Quinta-Ferreira, 2009;Yang et al, 2016). At present, CFD simulations of the RPB have been performed based on both the single and two-phase models (Yang et al, 2018). For the single-phase simulation, the porous media model based on empirical formulae have mostly been used to describe the resistance of the packing to the gas phase (Llerena-Chavez and Larachi, 2009;Wu et al, 2018;Yang et al, 2015b).…”

Section: Cfd Modelling Of the Rpbmentioning

confidence: 99%

A mesoscale 3D CFD analysis of the liquid flow in a rotating packed bed

Xie

Ding

et al. 2019

Chemical Engineering Science

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Rotating packed beds (RPBs), as a type of process intensification technology, are promising to be employed as high-efficiency CO 2 absorbers. However, the detailed understanding of the liquid flow in the RPB is still very limited. The complex and dense packing of the bed and the multiscale of the RPB make it very difficult to perform numerical simulations in detail, in particular for full 3D simulations. In this paper, a mesoscale 3D CFD modelling approach is proposed which can be used to investigate the liquid flow in both laboratory-and large-scale RPBs in detail and accuracy. A 3D representative elementary unit of the RPB has been built and validated with experimental observations, and then it is employed to investigate the gas-liquid flows at different locations, across a typical RPB, so that the overall characteristics of the liquid flow in the RPB can be assembled. The proposed approach enables the detailed prediction of the liquid holdup, droplets formation, effective interfacial area, wetted packing area and specific surface area of the liquid within real 3D packing structures throughout the bed. New correlations to predict the liquid holdup, effective interfacial area, and specific surface area of the liquid are proposed, and the sensitivities of these quantities to the rotational speed, liquid flow rate, viscosity and contact angle have been investigated. The results have been compared with experimental data, previous correlations and theoretical values and it shows that the new correlations have a good accuracy in predicting these critical quantities. Further, recommendations for scale-up and operation of an RPB for CO 2 capture are provided. This proposed model leads to a much better understanding of the liquid flow behaviours and can assist in the RPB optimisation design and scaling up.

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A review on computational fluid dynamic simulation for rotating packed beds

Cited by 22 publications

References 82 publications

A Review of Modeling Rotating Packed Beds and Improving Their Parameters: Gas–Liquid Contact

A Review of Modeling Rotating Packed Beds and Improving Their Parameters: Gas–Liquid Contact

Revising the dark fermentative H2 research and development scenario – An overview of the recent advances and emerging technological approaches

A mesoscale 3D CFD analysis of the liquid flow in a rotating packed bed

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