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Methodological analysis of gamma tomography system for large random packed columns.

Pablo A S Vasquez1, Carlos H De Mesquita, Galo A C LeRoux

  • 1Instituto de Pesquisas Energéticas e Nucleares-IPEN/CNEN-SP, Cidade Universitária, São Paulo, Brazil.

Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine
|December 25, 2009
PubMed
Summary

Gamma ray tomography revealed spatial porosity variations in packed columns using steel Rashig rings. Porosity increased with ring size and was higher near the column wall due to wall effects.

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Area of Science:

  • Chemical Engineering
  • Nuclear Engineering
  • Physics

Background:

  • Packed beds are crucial in chemical processes, but their internal structure, particularly porosity, affects performance.
  • Understanding gas-solid flow dynamics is essential for optimizing reactor design and efficiency.

Purpose of the Study:

  • To investigate spatial porosity distribution in a packed column using gamma ray tomography.
  • To analyze the impact of different steel Rashig ring sizes on gas porosity and solid holdup.
  • To determine the influence of column wall effects on porosity.

Main Methods:

  • Gamma ray tomography experiments were conducted on a 0.27 m diameter column.
  • Steel Rashig rings of 12.6, 37.9, and 76 mm were used as packing material.
  • A first-generation CT system and a fast Fourier transform algorithm were employed for reconstruction and analysis.

Main Results:

  • Cross-sectional gas porosity and solid holdup distributions were determined.
  • Average gas porosities were 0.849, 0.938, and 0.966 for 12.6, 37.9, and 76 mm rings, respectively.
  • Higher porosity was observed in the column wall region compared to the bulk region.

Conclusions:

  • Gas porosity in packed columns increases with larger Rashig ring sizes.
  • The column wall effect significantly influences radial porosity distribution, leading to higher values near the wall.
  • Gamma ray tomography is effective for visualizing and quantifying porosity patterns in packed beds.