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An artificial neural network for prediction of gas holdup in bubble columns with oily solutions

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Abstract

Gas holdup in a bubble column reactor filled with oil-based liquids was estimated by an artificial neural network (ANN). The ANN was trained using experimental data from the literature with various sparger pore diameters and a bubbly flow regime. The trained ANN was able to predict that the gas holdup of data did not seen during the training period over the studied range of physical properties, operating conditions, and sparger pore diameter with average normalized square error <0.05. Comparisons of the neural network predictions to correlations obtained from experimental data show that the neural network was properly designed and could powerfully estimate gas holdup in bubble column with oily solutions.

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Abbreviations

Ar :

Archimedes number

d C :

Column diameter (m)

d p :

Mean pore diameter (m)

d S :

Sparger diameter (m)

Eo :

Eotvos number

Fr :

Froude number

H L :

Liquid heights before gas injection (m)

H D :

Liquid heights after gas injection (m)

n 1 :

Dimension of the input vector

n 2 :

Number of hidden neurons

t :

Time (s)

U g :

Superficial gas velocity (m/s)

v ij :

The connection weights from input neuron i to hidden neuron j

V :

Volume (m3)

w :

The connection weights

w ij :

Connection weight from input neuron i to hidden neuron j

x :

Input variable

y :

Output variable

g :

Acceleration due to gravity (9.81 m/s2)

ε g :

Gas holdup

σ :

Surface tension (N/m)

μ :

Viscosity (Pa s)

ρ :

Density (kg/m3)

g:

Gas phase

L:

Liquid phase

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Authors and Affiliations

  1. Group of Biotechnology, School of Chemical Engineering, College of Engineering, University of Tehran, P.O. Box 11155-4563, Tehran, Iran

    Sahar Amiri, Mohammad Reza Mehrnia, Davood Barzegari & Aryan Yazdani

Authors
  1. Sahar Amiri
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  2. Mohammad Reza Mehrnia
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  3. Davood Barzegari
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  4. Aryan Yazdani
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Correspondence to Mohammad Reza Mehrnia.

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Amiri, S., Mehrnia, M.R., Barzegari, D. et al. An artificial neural network for prediction of gas holdup in bubble columns with oily solutions. Neural Comput & Applic 20, 487–494 (2011). https://doi.org/10.1007/s00521-011-0566-x

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