Measurement of Local Phase Holdups in a Two- and Three-Phase Bubble Column

Fischer–Tropsch Synthesis in Slurry Bubble Column Reactors: Experimental Investigations and Modeling – A Review

This paper presents an extensive review of the kinetics, hydrodynamics, mass transfer, heat transfer and mathematical as well as computational fluid dynamics (CFD) modeling of Low-Temperature Tropsch Synthesis (LTFT) synthesis in Slurry Bubble Column Reactors (SBCRs), with the aim of identifying potential research and development areas in this particular field. The kinetic expressions developed for F-T synthesis over iron and cobalt catalysts along with the water gas shift (WGS) reactions are summarized and compared. The experimental data and empirical correlations to predict the hydrodynamics (gas holdup, Sauter mean bubble diameter, and bubble rise velocity), mass transfer coefficients and heat transfer coefficients are presented. The effects of various operating variables, including pressure, temperature, gas velocity, catalyst concentration, reactor geometry, and reactor internals on the hydrodynamic and transport parameters as well as the performance of SBCRs are discussed. Additionally, modeling efforts of SBCRs, using axial dispersion models (ADM), multiple cell recirculation models (MCCM) and computational fluid dynamics (CFD), are addressed. This review revealed the following: (1)

Error analysis of tomographic reconstructions in the absence of projection data

Error estimates for tomographic reconstructions (using Fourier transform-based algorithm) are available for cases where projection data are available. These data are used for reconstructions with different filter functions and the reliability of these reconstructions can be checked as per guidelines of those error estimates. There are cases where projection data are large (in gigabytes or terabytes) so storage of these data becomes an issue. It leads to storing of only the reconstructed images. Error estimation in such cases is presented here. Second-level projection data are calculated from the given reconstructed images ('first-level' images). These 'second-level' data are now used to generate 'second-level' reconstructed images. Different filter functions are employed to check the fidelity of these 'second-level' images. This inference is extended to first-level images in view of the characteristics of the convolution operator. This approach is validated with experimental data obtained by the X-ray micro-CT scanner installed at IIT Kanpur. Five specimens (of same material) have been scanned. Data are available in this case thus we have performed a comparative error estimate analysis for the 'first-level' reconstructions (data obtained from CT machine) and second-level reconstructions (data generated from first-level reconstructions). We observe that both approaches show similar outcome. It indicates that error estimates can also be applied to images when data are not available.