Computational study of the bubbling-to-slugging transition in a laboratory-scale fluidized bed☆
Graphical abstract
Section snippets
Introduction and background
Gas-solid fluidized-bed reactors are widely used in the chemical industry, including biomass conversion [1], [2], [3], [4], petroleum refining [5], and pharmaceutical [6], [7] and commodity chemicals production [8]. For this reason, there is widespread interest in establishing a comprehensive understanding of the gas-solid hydrodynamics to optimize processes in which fluidized-bed reactors are key components. Three of the most important hydrodynamic states or flow regimes in fluidized-bed
Fluidized bed simulation conditions
To reflect a lab-scale reactor of current relevance, we assumed the geometry of an experimental laboratory reactor used for biomass processing research at the National Renewable Energy Laboratory (NREL). A schematic of the reactor is shown in Fig. 1. The inner diameter Dr and height of the reactor Hr are 0.0508 and 1.27 m, respectively. However, for simulation purposes, the computational domain was reduced to a height of 0.4 m. Operating conditions were chosen to match baseline experiments at
Results and discussion
The visual appearance of the bubbles generated by MFiX was observed graphically in terms of void fraction iso-surfaces using Paraview [86] as illustrated in the following section below. To systematically quantify the simulated bubble patterns, we evaluated bubble statistics derived from the MFiX void fraction output using MS3DATA. We then evaluated the pressure time series features at each level to determine how they relate to the observed bubble behavior.
Conclusions
Results from the three-dimensional computational simulations of a laboratory-scale fluidized bed indicate that the transition from bubbling-to-slugging is a complex process that occurs over a range of gas flows rather than abruptly at a single flow. The transition process appears to involve a cascade of bubble coalescences that produce size and speed changes which begin near the bed surface and then progress downward toward the distributor as gas flow increases. The state of maximum slugging
Acknowledgment
This work was supported by the Bioenergy Technology Office, US Department of Energy through the Computational Pyrolysis Consortium (CPC) project. The authors would like to thank program sponsors Jeremy Leong, Cynthia Tyler, and Kevin Craig for their support and guidance. More information about the CPC project can be found at http://cpcbiomass.org/. The authors acknowledge Akhilesh Bakshi for making MS3DATA available and See Hoon Lee for discussions through email about their work related to
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Particle flow characteristics in a gas-solid separation fluidized bed based on machine learning
2022, FuelCitation Excerpt :The dissipation and interactions of the bubble phase and dense phase lead to a heterogeneous flow structure, and local bubble dynamics are characterized by chaos, which is typical of a complex system [11–13], particularly with uncertainties in the relationships among mesoscale bubbles, cluster structures, cavities and gas-solid two-phase flow characteristics and the dynamic transformation and nonuniform fluidization of different flow patterns during fluidization. Furthermore, particles in different regions have different flow forms [14]; even under the same operating conditions, the flow structure and state of the gas phase, solid phase, and gas-solid phase also change with spatial position in the bed, resulting in abnormal fluidization states such as particle back mixing [15], regional dead zone, cavitation, bridging, gully flow, slug and so on [16–19]. A study of the effect of particle flow characteristics on fluidization and separation would be beneficial to the post-industrial application of gas-solid separation fluidized bed technology.
Fluidization dynamic characteristics of carbon nanotube particles in a tapered fluidized bed
2022, Chinese Journal of Chemical EngineeringOnset of slugging fluidization in supercritical water fluidized bed
2020, ParticuologyEffect of bed size on the gas–solid flow characterized by pressure fluctuations in bubbling fluidized beds
2019, ParticuologyCitation Excerpt :The standard deviation is usually used to represent pressure-fluctuation amplitudes and was used to determine the transition velocity from bubbling to turbulent fluidization (Bi, Ellis, Abba, & Grace, 2000; He et al., 2014) and the minimum fluidization velocity (Umf) (Felipe & Rocha, 2007), as well as to monitor the fluidization state (van Ommen, Korte, & Bleek, 2004). Skewness and kurtosis are also used to identify the transition from bubbling to slugging or turbulent fluidization (Lee & Kim, 1988; Lee, Sang, & Park, 2002; Ramirez et al., 2017). The frequency-domain analysis mainly concerns the physical interpretation of the main peak frequencies at lower frequencies (Kage, Agari, Ogura, & Matsuno, 2000) and the fall-off characteristics at higher frequencies (van der Schaaf, Johnsson, Schouten, & van den Bleek, 1999) in the power spectral density as well as the analysis of signal components in different frequency ranges corresponding to different scales by wavelet transform (Briens & Ellis, 2005; Zhao & Yang, 2003).
Assessment of the TFM in predicting the onset of turbulent fluidization
2019, Chinese Journal of Chemical Engineering
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Notice: This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for the United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).