Comparison of ML-EM algorithm and ART for reconstruction of gas hold-up profile in a bubble column

Algebraic reconstruction technique (ART) and maximum likelihood-expectation maximization (ML-EM) algorithm have been applied for image reconstruction using gamma-ray tomography. This methodology can be of immense help in establishing the hydrodynamics of several multiphase systems such as two-phase and three-phase bubble column reactors. The effect of various image processing parameters such as initial guess, grid size, stopping criteria and gamma-ray measurement parameters like beam configuration, number of projection, number of views on the quality of reconstructed image has been studied in present work. It has been observed that ML-EM algorithm shows more precise and faster results as compared to ART and it serve as a preferential tool in image reconstruction. These techniques were then used in the estimation of gas hold-up profile in a two-phase aqueous system. Average gas hold-up values in bubble column based on reconstructed local hold-up values based on the above two techniques were found to be in good agreement with the experimental data within 10% accuracy, however, ML-EM algorithm may be preferred due to better capability of incorporating the modalities of data collection. (C) 2006 Elsevier B.V. All rights reserved.