Abstract
A new methodology for implementing radioactive particle tracking (RPT) in bubble columns with intense vertical rod internals was developed and implemented to investigate the effect of dense internals on hydrodynamics. The methodology utilizes a hybrid of Monte Carlo N-Particle (MCNP) simulation and an automated RPT calibration device to generate a large number of calibration points for accurate reconstruction of the instantaneous positions of radioactive particles using a similarity algorithm. Measurements were conducted in a 6-inch (15.24 cm) Plexiglas column using an air–water system at a superficial gas velocity of 40 cm/s. Vertical Plexiglas rods 0.5 in (1.27 cm) in diameter were used to cover ~25% of the total cross-sectional area of the column to represent the effect of a heat-exchanging tube in industrial Fisher–Tropsch synthesis. The results showed that the internals increased liquid velocity near the center of the column by more than 30%, resulting in enhanced liquid circulation and frequency of liquid eddy movement. In addition, turbulence parameters decreased noticeably when using vertical internals in the bubble column due to a reduction in velocity fluctuations. Reliable data can help validate computational fluid dynamics (CFD) models to predict hydrodynamic parameters at other various conditions.
Recommended Citation
O. J. Farid et al., "New Methodology For Benchmarking Hydrodynamics In Bubble Columns With Intense Internals Using The Radioactive Particle Tracking (RPT) Technique," Processes, vol. 11, no. 7, article no. 2107, MDPI, Jul 2023.
The definitive version is available at https://doi.org/10.3390/pr11072107
Department(s)
Chemical and Biochemical Engineering
Publication Status
Open Access
Keywords and Phrases
bubble column reactor; Co-60; Monte Carlo N-Particle (MCNP); RPT; similarity
International Standard Serial Number (ISSN)
2227-9717
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Jul 2023