02293nas a2200193   4500008004100000022001400041245009100055210006900146260007100215300001400286490000700300520158200307100002101889700002701910700001801937700001601955700002101971856010701992       2007                        eng d  a0888-588500aEffect of sparger design on the flow in a bubble column: symbolic analysis of LDA data0 aEffect of sparger design on the flow in a bubble column symbolic  a1155 16TH ST, NW, WASHINGTON, DC 20036 USAbAMER CHEMICAL SOCcMAY  a2996-30070 v463 a<p>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.</p>1 aKulkarni, A., A.1 aDeshpande, Suvarna, S.1 aJoshi, J., B.1 aKumar, Ravi1 aKulkarni, B., D.  uhttps://library.ncl.res.in/content/effect-sparger-design-flow-bubble-column-symbolic-analysis-lda-data01902nas a2200253   4500008004100000022001400041245013400055210006900189260010600258300001400364490000700378520091400385653001801299653001601317653000801333653004501341653003601386100002201422700001801444700002101462700002601483700002101509856011801530       2008                        eng d  a0301-932200aSVR-based prediction of point gas hold-up for bubble column reactor through recurrence quantification analysis of LDA time-series0 aSVRbased prediction of point gas holdup for bubble column reacto  aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLANDbPERGAMON-ELSEVIER SCIENCE LTDcDEC  a1099-11070 v343 a<p>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.</p>10aBubble column10aGas hold-up10aLDA10aRecurrence quantification analysis (RQA)10aSupport vector regression (SVR)1 aGandhi, Ankit, B.1 aJoshi, J., B.1 aKulkarni, A., A.1 aJayaraman, Valadi, K.1 aKulkarni, B., D.  uhttps://library.ncl.res.in/content/svr-based-prediction-point-gas-hold-bubble-column-reactor-through-recurrence-000908nas a2200205   4500008004100000022001400041245021000055210006900265260007600334300000800410490000700418100001800425700001700443700001700460700001900477700003600496700002300532700001900555856012800574       2012                        eng d  a0008-403400aReply 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''0 aReply to the comments to CFD simulation of stirred tanks compari  aCOMMERCE PLACE, 350 MAIN ST, MALDEN 02148, MA USAbWILEY-BLACKWELLcFEB  a3-60 v901 aJoshi, J., B.1 aNere, N., K.1 aRane, C., V.1 aMurthy, B., N.1 aMathpati, Channamallikarjun, S.1 aPatwardhan, A., W.1 aRanade, V., V.  uhttps://library.ncl.res.in/content/reply-comments-cfd-simulation-stirred-tanks-comparison-turbulence-models-part-i-radial-0