- Volumes 84-95 (2024)
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Volumes 72-83 (2023)
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Volume 83
Pages 1-258 (December 2023)
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Volume 82
Pages 1-204 (November 2023)
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Volume 81
Pages 1-188 (October 2023)
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Volume 80
Pages 1-202 (September 2023)
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Volume 79
Pages 1-172 (August 2023)
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Volume 78
Pages 1-146 (July 2023)
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Volume 77
Pages 1-152 (June 2023)
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Volume 76
Pages 1-176 (May 2023)
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Volume 75
Pages 1-228 (April 2023)
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Volume 74
Pages 1-200 (March 2023)
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Volume 73
Pages 1-138 (February 2023)
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Volume 72
Pages 1-144 (January 2023)
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Volume 83
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Volumes 60-71 (2022)
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Volume 71
Pages 1-108 (December 2022)
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Volume 70
Pages 1-106 (November 2022)
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Volume 69
Pages 1-122 (October 2022)
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Volume 68
Pages 1-124 (September 2022)
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Volume 67
Pages 1-102 (August 2022)
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Volume 66
Pages 1-112 (July 2022)
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Volume 65
Pages 1-138 (June 2022)
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Volume 64
Pages 1-186 (May 2022)
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Volume 63
Pages 1-124 (April 2022)
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Volume 62
Pages 1-104 (March 2022)
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Volume 61
Pages 1-120 (February 2022)
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Volume 60
Pages 1-124 (January 2022)
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Volume 71
- Volumes 54-59 (2021)
- Volumes 48-53 (2020)
- Volumes 42-47 (2019)
- Volumes 36-41 (2018)
- Volumes 30-35 (2017)
- Volumes 24-29 (2016)
- Volumes 18-23 (2015)
- Volumes 12-17 (2014)
- Volume 11 (2013)
- Volume 10 (2012)
- Volume 9 (2011)
- Volume 8 (2010)
- Volume 7 (2009)
- Volume 6 (2008)
- Volume 5 (2007)
- Volume 4 (2006)
- Volume 3 (2005)
- Volume 2 (2004)
- Volume 1 (2003)
• RPT measurements and DDPM simulations were performed in liquid–solids fluidized beds.
• DDPM simulations can predict mean velocities and mixing pattern with high accuracy.
• Particle–particle interactions became dominant in binary fluidized beds.
Liquid–solid binary fluidized beds are widely used in many industries. However, the flow behavior of such beds is not well understood due to the lack of accurate experimental and numerical data. In the current study, the behavior of monodisperse and binary liquid–solid fluidized beds of the same density but different sizes is investigated using radioactive particle tracking (RPT) technique and a dense discrete phase model (DDPM). Experiments and simulations are performed in monodisperse fluidized beds containing two different sizes of glass beads (0.6 and 1 mm) and a binary fluidized bed of the same particles for various bed compositions. The results show that both RPT and DDPM can predict the mixing and segregation pattern in liquid–solid binary fluidized beds. The mean velocity predictions of DDPM are in good agreement with the experimental findings for both monodisperse and binary fluidized beds. However, the axial root mean square velocity predictions are only reasonable for bigger particles. Particle–particle interactions are found to be critical for predicting the flow behavior of solids in liquid–solid binary fluidized beds.