Effect of sparger design on the flow in a bubble column: symbolic analysis of LDA data - Kulkarni, A. A.; Deshpande, Suvarna S.; Joshi, J. B.; Kumar, V. Ravi; Kulkarni, B. D. (Industrial & Engineering Chemistry Research, 2007)
This paper aims at developing a methodology that helps in the characterization of the effects of a single point and multipoint sparger on the flow patterns in a bubble column reactor. The methodology uses the simultaneously measured instantaneous velocity-time data (two orthogonal velocity components) using LDA at different measurement locations. The data sets are transformed into their equivalent description in terms of polar coordinates, viz., resultant velocity vector and angle. This information is further transformed in terms of symbolic representation in a binary number format. The covariance matrices obtained from the binary data are analyzed for their eigenvalues, and the spectrum is used for the identification of the dominant, energy containing modes in the data. In the vicinity of the sparger, the nature of covariance matrix and the eigenvalue spectrum for the single point sparger (SPS) data was significantly different from that of the multipoint sparger (MPS). In the bulk region, for both types of spargers, the nature of the eigenvalues and the number of dominant modes is seen to be different from the near sparger region. In general, more numbers of eigenvalues are required to capture the total energy in the data for a multipoint sparger when compared to a single point sparger. This suggests a higher level of complexities existing due to the intricate hydrodynamics for the multipoint sparger. The possible use of this methodology for practical purposes, e.g., identification of malfunctioning of gas-liquid sparger reactors is discussed.

SVR-based prediction of point gas hold-up for bubble column reactor through recurrence quantification analysis of LDA time-series - Gandhi, Ankit B.; Joshi, J. B.; Kulkarni, A. A.; Jayaraman, Valadi K.; Kulkarni, B. D. (International Journal of Multiphase Flow, 2008)
Recurrence quantification analysis (RQA) has emerged as a useful tool for detecting singularities in nonstationary time-series data. In this paper, we use RQA to analyze the velocity-time data acquired using laser doppler anemometry (LDA) signals in a bubble column reactor for Single point and Multipoint point spargers. The recurring dynamical states within the velocity-time-series occurring due to the bubble and the liquid passage at the point of measurement, are quantified by RQA features (namely % Recurrence, % Determinism, % Laminarity and Entropy), which in turn are regressed using support vector regression (SVR) to predict the point gas hold-up values. It has been shown that SVR-based model for the bubble column reactor can be potentially useful for online prediction and monitoring of the point gas hold-up for different sparging conditions. (C) 2008 Elsevier Ltd. All rights reserved.
Keywords: Bubble column; Gas hold-up; LDA; Recurrence quantification analysis (RQA); Support vector regression (SVR)

Reply to the ``comments to CFD simulation of stirred tanks: comparison of turbulence models. part I: radial flow impellers and part II: axial flow impellers, multiple impellers and multiphase dispersions'' - Joshi, J. B.; Nere, N. K.; Rane, C. V.; Murthy, B. N.; Mathpati, Channamallikarjun S.; Patwardhan, A. W.; Ranade, V. V. (Canadian Journal of Chemical Engineering, 2012)