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.