Mass transfer analysis in ozone bubble columns using artificial neural networks

M. S. Baawain, M. Gamal El-Din, D. W. Smith

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The design of ozone bubble columns is associated with accurate determination of some nonlinear parameters. The overall mass transfer coefficient (kLa) is the most important parameter as it dictates the efficiency of the bubble column. A multi-layer perceptron (MLP) artificial neural network (ANN) was used to simulate and predict the kLa in different ozone bubble columns by utilising simple inputs such as bubble column's geometry and operating conditions. The developed ANN model predicted kLa values in the training and validation data sets with a coefficient of multiple determination (R2) values that exceeded 0.87 and 0.85, respectively, which imply good model predictions.

Original languageEnglish
Title of host publicationCivil-Comp Proceedings
PublisherCivil-Comp Press
Volume82
ISBN (Print)1905088051, 9781905088058
Publication statusPublished - 2005
Event8th International Conference on the Application of Artificial Intelligence to Civil, Structural and Environmental Engineering, AICivil-Comp 2005 - Rome, Italy
Duration: Aug 30 2005Sep 2 2005

Other

Other8th International Conference on the Application of Artificial Intelligence to Civil, Structural and Environmental Engineering, AICivil-Comp 2005
CountryItaly
CityRome
Period8/30/059/2/05

Keywords

  • Artificial neural networks
  • Bubble columns
  • Modelling
  • Overall mass transfer coefficient
  • Ozone

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Civil and Structural Engineering
  • Artificial Intelligence
  • Environmental Engineering

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  • Cite this

    Baawain, M. S., El-Din, M. G., & Smith, D. W. (2005). Mass transfer analysis in ozone bubble columns using artificial neural networks. In Civil-Comp Proceedings (Vol. 82). Civil-Comp Press.